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Willy C. Kriz, Tanja Eiselen, Werner Manahl

The Shift from Teaching to Learning: Individual, Collective and Organizational Learning Through Gaming Simulation Proceedings of the 45th Conference of the International Simulation and Gaming Association

Dornbirn, 2014

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Table of Contents

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“Simulation for Strategy Courses: Comparing US and EU Courses” 105 Larry Chasteen

“Building Urban Gaming Simulation Tools for Community Self–Planning: A Case Study in Yomjinda Old Town” 115

Preface 16

Chaweewan Denpaiboon

“The Knowledge Creation Process in New Product Development Teams in Simulation Games — A Literature Review” 130

Papers “Simulations and Games for Crisis Management: A Journal-Based Literature Review” 20

Yanan Feng, Johann Riedel

“Measuring Game Experience and Learning Effects of Business Games” 140 Susann Fink, Kristian Kiili, Angelika C. Bullinger

Megan L. Anderson

“The Instructor Role during Educational WarGaming” 153 “Gaming in Higher Education: Students’ Assesment on Game-Based Learning” 33 M a Ángeles Andreu-Andrés, Miguel García-Casas

“Student Perceptions of Gain in Telematic Simulation” 44

Anders Frank

“Team processes in Interdisciplinary Projects — The C²–Business Game for Project Management and Soft Skill Development” 167 Silke Geithner; Daniela Menzel; Stefan Donath

M. Laura Angelini, Amparo García-Carbonell, Frances Watts

“Modeling Knowledge Co-Creation Games as Activity Systems” 186 “The Impact of Business Simulations as a Teaching Method on Entrepreneurial Competencies and Motivation — A Review of 10 Years of Evaluation Research in Entrepreneurship Education” 55

Otso Hannula, Olivier Irrmann, Riitta Smeds

“Finding the Game in Decision–Making: A Preliminary Investigation” 199

Eberhard Auchter; Willy Christian Kriz

Casper Harteveld; Steven Sutherland

“A Design and Implementation of Interactive Visualizations and Simulation in Transportation” 66

“From Reality to Game and back — A view on the Teambuilding Aspects of a New Concept for Game Design Workshops Through a Game Designer’s Lens” 210

Mohammad Azhari; Jayanth Raghothama; Sebastiaan Meijer

Andrea Heinecke

“Distributed Asymmetric Simulation — Enhancing Participatory Simulation Using the Concept of Habitus” 75 Nicolas Becu, Nathalie Frascaria-Lacoste, Julie Latune

“Flexible and User-Oriented Development of Haptic Management Simulation Games in Maritime Container Logistics” 86 Johann Bergmann

“Long-term Effect of Gaming Simulation as Community Flood Management Training for Trainer Tools: A Case Study of Donmuang District Communities, Bangkok, Thailand” 221 Pongpisit Huyakorn

“Early Japanese Policy Games” 236 Arata Ichikawa

“Innovation Facilitation: Scaling Project-Oriented Teaching and Learning in Engineering Education” 98

“Designing Gamified Course for Students – Framework and Examples” 248

Arno Bitzer, Gabriele Koeppe, Siegfried Stumpf, Paul Bagiu, Stefanie Gruttauer

Michal Jakubowski

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“Developing Market Analysis Models Based on Decision Making in Business Games” 256

“Townlands: Designing an Online Game to Support a Cross–Community Local–History Project, Bygones and Byways.” 387

Christian K. Karl

Adrian Mallon

“Roles of play: The implications of Roles in Games” 268

“Threshold as Metaphor, Metaphor as Threshold” 398

Toshiko Kikkawa

Ivar Männamaa

“The Influence of Formal Mindsets on Decision Maker Attitudes When Confronted with Difficult Problems: A View of Gaming Simulation “Lost in Space” Using Inner Measurement” 276

“A Prototype Prediction Market Game for Enhancing Knowledge Sharing Among Salespeople” 406 Hajime Mizuyama; Kazuto Yamamiya

Shinobu Kitani; Tadashi Hasebe

“Predictive Analytics in Business Games and Simulations” 415 “From Simulation Games to Smart Learning Systems” 288

Mihail R. Motzev

Wilhelm Klat, Karl-Heinz Gerholz, Christian Stummer

“What Makes Simulation Games Motivating? Design–Based Research on Learners’ Motivation in Simulation Gaming.” 301

“Process Model for the Development of Simulation Games for Training Purposes” 429 Jan-Jasper Mühle, Johannes Schweizer, Markus Klevers

Maximilian Knogler; Doris Lewalter

“Designing a Serious Game for Military Ethics” 445 “Using Business Simulation to Analyse Project Management Decision Making” 313 Igor Kokcharov

Tijmen Muller, Gillian Visschedijk

“Glitches, Players, and MetaGames: Another family Conversation” 455 James Darrel Murff, Elizabeth Jane Tipton

“Comparing Learning Gain and Flow Induced by a 2D Educational and a 3D Entertainmentt Game” 319 Martijn Koops; Ineke Verheul; Rinus Tiesma; Cees-Willem de Boer; R. Koeweide

“Adaptation of Business Game for Learning of Geographic Information Systems in Debriefing Stage” 466 Irena Patasienė, Martynas Patasius, Grazvidas Zaukas

“MicroGames in Practice: A Case Study in Container Terminal Operations” 333 Shalini Kurapati; Daan Groen; Heide Lukosch; Alexander Verbraeck

“Can Communication Save The Commons? Lessons from Repeated Role–Playing Game Sessions” 347

“Business Simulation Vial+ — An Interactive Learning Environment for Developing Management Skills” 476 Vitalii Pazdrii, Oleksandr Gryschenko, Petr Banschykov

“What Is Being Simulated” 362

“Conceptualizing the Essential Role of Gaming Simulation as a Risk Communication Technique for Enhancing Urban Resilience Against Natural Disaster” 489

Elyssebeth Leigh, Elizabeth Tipton

Sarunwit Promsaka Na Sakonnakron; Paola Rizzi

“Economic Evaluation of Serious Games with the Comparative Assessment Framework COSEGA” 374

“The Windmill Product Life Cycle Game” 501

Christophe Le Page; Anne Dray; Pascal Perez; Claude Garcia

Laura Lenz, Martin R. Wolf

Rosa Garcia Sanchez, Jannicke Baalsrud Hauge, Hendrik Kraume

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“Business Games — An Analysis of Rowth in the Knowledge of Business Administration Skills in Non Business Administrators” 511

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“Business Games for Assurance of Learning Purposes” 666 Joseph Allen Wolfe

Simone Six

“Regulatory Focus Insights Into Business Game Engagement” 686 “Using the “Stakeholders” Simulation Game to Understand Social Problem: an Application of a Frame Game to Assess Environmental and Health Conflict Resolution” 523

Joseph Allen Wolfe

“Web Services for Simulation and Training Games Communities” 703

Junkichi Sugiura

Gee Kin Yeo, Erbin Lim, Abel Paschal Tay

“Fundamentals of Game Design” 531

“Innovative Methods of Training and Their Integration in Business Education” 713

Richard Teach; Joan K. Teach

Elena Zarukina, Mila Novik, Olga Akimova

“GamEducation — A Game for Learning to Create Game” 549 Sun-Teck Tan

“Global Systems Science and Integrated Policymaking: Why Games?” 721 Qiqi Zhou, Igor Mayer

“The Relation Between Individual, Collective and Organisational Learning Through Business Games in the Management Field” 562 Luiz Antonio Titton

Posters “Gaming Simulation for Community–Based Disaster Reduction” 584 Yusuke Toyoda; Hidehiko Kanegae; Kohei Sakai

“The Debriefing of Research Games: A Structured Approach for the Validation of Gaming Simulation Outcomes” 599 Jop van den Hoogen; Julia Lo; Sebastiaan Meijer

“Game Narrative for Situating Ethical Dilemmas in Virtual Disaster Response Work” 611 Didin Wahyudin, Shinobu Hasegawa

“Gaming Simulation for Water Management: Considering Desalination Plants Powered by Renewable Energies in Protected Areas” 736 Marcia Alessia, Paola Rizzi

“Bridging the Gap between Continuous and Round Based Management Simulations” 743 Nils Axel Hoegsdal, Felix Daul, Manuel Pflumm

“Tangible Board Game for Learning Basic Inventory Control” 746 Tomomi Kaneko, Ryoju Hamada, Masahiro Hiji

“Hotel Stars — Development of the Simulation Game-Based Teaching Programme for the Secondary Schools Students as the Introduction to Business and Economics” 624

“Framework for the Design of Competency–Oriented Business Simulations (COBS)” 750

Marcin Wardaszko

Christian K. Karl

“Genuine Guitars and Game Enjoyment in Music Games” 639

“Serious Games for Military Cultural Training” 754

Ulrich Wechselberger

Hanne Fagerjord Karlsen

“‘Life Is Just a Game’: Turning Systems Analysis as well as Simulations and Gaming Into Accessible Craft for Decision Makers” 653 Christoph David Weinmann

“Mixed Reality Media Player for Authoring Rich Location-Based Interactions” 759 Thomas Katzlberger, Armin Pfurtscheller

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“Developing Individual Seminar Concepts That Arouse Curiosity by Using The Input of The Participating Students” 761

“HERAKLIT PUBLISHER Authoring System for Simulation and Gaming of Decision Making and Strategy Optimization” 784

Samir Khezzar

Christoph David Weinmann

“priME–Cup Game–Based Contests for Management, Innovation and Entrepreneurship” 763

“Community Currency Game: A Tool for Introducing the Concept of Community Currencies” 788

Willy C. Kriz, Eberhard Auchter, Helmut Wittenzellner

Masayuki Yoshida, Shigeto Kobayashi

“Entrepreneurial thinking development. How to change people mindset With the Game? Russian Experience of FreshBiz.” 765

“Playing Games as a Method in Adult Education” 795 Erich Ziegler

Ekaterina Molodykh, Inna Pevzner

“From Teaching Knowledge to Gaming for Understanding: Using a Management Role Playing Game as Learning Tool ” 768 Lena Maureen Reibelt, Patrick Olivier Waeber, Lucienne Wilmé, Claude Garcia, Anne Dray, Antje Rendigs, Torsten Richter, Jasmin Mantilla Contreras

“How Do You Evaluate Corporate Strategy Through Gamification?” 770

Workshops “Wat–A–Game an Open Toolkit for Building Your Own Tailored Low Tech Serious Games About Natural Resources Management” 799 Geraldine Abrami, Nils Ferrand, Wanda Aquae-gaudi

Ryo Sato

“cs-i ISO Puzzle” 803 “Grosses Königs-Spiel by Johann Weickhmann: First Steps Into Direction of Today’s Simulation Games” 778 Sebastian Schwägele

Helmut Berger

“Wifuzitake” 804 Renate M. Birgmayer-Baier

“Business Management Game by Gerd Andlinger and Jay Greene: The First Business Board Game” 779 Sebastian Schwägele, Eric Treske

“TeamUp (Authorization) Track: Theory, GamePlay & TechTalk (Full Track = Authorization)” 806 Dirk Jan Bolderheij

“Learning a Business Language in a Simulated Business Environment” 780 Thomas Temme

“Fort Fantastic Simulation Demo and Workshop” 807 Roland Böttcher, Frank Hofmann

“The Simulation Game “PROFICODE” — A New Way to Deal With Professionalism?” 781

“Simulating Parliamentary Work” 809

Ramona Uhl

Frank Burgdörfer

“Youth Care Knowledge Exchange Through Online Simulation Gaming Designing and Appreciation Online Simulation Games to Enhance Youth Care Knowledge Exchange” 783

“Presentation of the SNUS Game” 810

Kees J. M. van Haaster

Rob Cary

“SEED YOUR SUCCESS — A haptic Business Game as Pre-Exercise for Complex Computer-Based Business Simulations” 811 Josef Duttle

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“SysTeamsProject — From Planning to Realizing Projects” 813

“Legend — The Communication–Puzzle” 836

Tanja Eiselen, Kristina Hermann

Peter Köstel

“Simplycycle — Transferring Still Evolving Know-How for a Circular Economy” 814

“Place the Pin! — A Positioning–Classic” 838 Peter Köstel

Sonja Eser

“VALUable — Discover Diversity” 839 “Go global with TOPSIM” 816

Peter Köstel

Florian Gaspar

“Entrepreneurship” 817

“The ‘Babel Fish’ Project — Building a Means of Communicating Across Simulation Communities” 840

Heiko Hammer, Helmut Wittenzellner

Elyssebeth Ellen Leigh

“Ecopolicy® — A Playful Understanding of Complexity Practical Application in Education and Management” 819

“Gamification Designs in Progressive Chinese Language Learning” 842 Erbin Lim, Gee Kin Yeo

Gabriele Harrer-Puchner

“Hexagon Distributed” 844 “SysTeamsChange — How To Use a Game on Change for Different Settings?” 821 Kristina Hermann

Heide Karen Lukosch, Rens Kortmann

“cultureQs®: The Change Accelerator” 846 Eric Lynn

“TOPSIM — Petrol” 823 Nils Högsdal

“‘Thonburi Study’ Guessing Game” 824

“Revisiting History: Lessons from Plunkett’s Pages, a Case Study of the 1916 Easter Rising Alternate Reality Game” 848 Ronan Lynch, Bride Mallon, Cornelia Connolly

Pathomporn Indrangkura Na Ayudthya, Urairat Yamchuti, Noppawan Yamchuti, Songsri Soranastaporn

“LUDOKI: Playfully Successful” 853 “Political Eduation 2.0: Testing and Evaluating an Online Platform for Political Simulation Games” 829 Konstantin Kaiser

“Tangible Board Game for Learning Basic Inventory Control” 830

Wolfgang Marschall

“Townlands: Measuring Success in a Low-Budget E-Learning Product Evaluation.” 855 Adrian C.J.F. Mallon

Tomomi Kaneko, Ryoju Hamada, Mashiro Hiji

“Games for English Language Teaching: Selected Cases” 857 “A Demo Session with the Gaming Simulation ‘Internationale Staatenwelt 2’ 2(ISw2)” 832 Steven Kawalle

Panicha Nitisakunwut, Songsri Soranastaporn

“Knut Bleichers UB – 10” 869 Rolf F. Nohr

“Gaming Simulation Design Through the Lens of Problem–Based Learning — A Design Workshop” 834

“Play the Hellwig Game” 870

Maximilian Knogler, Klaus Masch

Rolf F. Nohr

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“eBeerGame — BeerGame Reloaded” 871

“ChangesetterLive™ Transform Game Workshop” 904

Gunter Olsowski

Leif Sørensen

“Presantation of Business Simulation ViAL+” 872

“Changesetter Game Workshop” 906

Vitalii Yaroslavovoych Pazdrii

Leif Sørensen

“Simulation Games as a Tool for Civic Education” 874

“6styles Game Workshop” 908

Stefan Rappenglueck

Leif Sørensen

“Bakery Cake Game” 875

“A Matter of Time” 909

Stephan Rometsch

Joanna Średnicka

“Confidence and Trust Game” 880

“Interpersonal Skills LAB — Fixing the Communication Problem in Projects. (Challenges and Advantages of a Game Based Learning Approach.)” 910

Stephan Rometsch

Alexander Stork

“Playing a Traffic Jam Game (‘Baregg–Tunnel–Spiel’) with Smart Phones” 886 Stephan Rometsch

“Biomimicry Sensory Awareness Game” 892

“Designing and Evaluating Resilient Business Systems Through Risk Management Simulation Games” 913 Motonari Tanabu, Ryo Sato, Yasushi Narushima, Yoshiki Matsui, Hiroaki Shirai

Regina Rowland

“Biomimicry Life Principles Game” 894

“The Joint Human Factors Training Program of SWISS International Air Lines and skyguide Using the Serious Game Format InterLAB” 915

Regina Rowland

Margot Tanner, Heinz Weber, Simone Wunderlin, Alexander Stork

“Communicating Synthetic Biology via SYNMOD Game” 895

“Jolts: Activities That Wake Up and Engage Participants” 918

Markus Schmidt, Olga Radchuk, Camillo Meinhart

Sivasailam Thiagarajan, Samuel van den Bergh

“Celemi Business Game — Tango — Get the Right Talents” 899

“A Business Game with artificial Intelligence to Support Individualised debriefing” 928

Claudia M. Schmitz

Luiz Antonio Titton

“Classical Business Simulation Celemi Apples & Oranges” 900 Claudia M. Schmitz

“Crisis Simulation Game ‘Stellwerk’” 932 Eric Treske

“Discovering the First Business Board Game: ‘Business Management Game’ by G. Andlinger and J. Greene (1956)” 901

“HEX — A Game About Communication and the Use of Scarce Resources” 933

Sebastian Schwägele, Eric Treske

Eric Treske

“A NURSIM Game for Developing an International Nursing Curriculum” 902

“Simulation Game napuro — Corporate Sustainability (Demonstration Workshop)” 935

Songsri Soranastaporn, Urairat Yamchuti

Markus Ulrich

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“Gaming, the Language to Shape a Sustainable Future — A Journey from 1974 to 2054” 936

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Partners & Sponsors

Markus Ulrich

“Gaming: the Future’s Challenge” 940 Pieter van der Hijden

“Making and Gaming; Exploring the Relation Between Gaming, Maker Spaces and Fab Labs” 941 Pieter van der Hijden

“Addiction Prevention Serious Game” 942 Julian Vogel, Sibylle Schirrmacher

“Leadership Serious Game” 944 Julian Vogel, Sibylle Schirrmacher

“Working With HERAKLIT: Simulations and Gaming as Accessible Craft for Decision Makers” 946 Christoph David Weinmann

“Sail the Titanic” 948 Joseph Allen Wolfe

A Simulation Game for Hitting the Lottery Jackpot

949

Gerd Xeller, Frank Bosch, Karl Hofmann, Sibel Kasa

“An EdAdSim Game for Developing and Integrating Information & Communication Technology (ICT) into Schools” 951 Noppawan Yamchuti, Songsri Soranastaporn, Pathomporn Indrangkura Na Ayudthya

“Massawa Workshop” 960 Marcin Żmigrodzki

International

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Preface In the 21st century expectations and beliefs are changing as to what students, employees and decision-makers have to learn in order to function in our societies and global economy. We have to efficiently navigate through increasing amounts of information, we must analyze and make decisions, and we have to rapidly master new knowledge domains. We need to collaborate with others in accomplishing complex tasks, using different systems for representing and communyicating information and for generating innovation. Today a paradigm shift from teacher-centered instruction to learner-centered instruction is constantly being discussed. Lifelong learning must ensure the development of knowledge and competencies for sustainable societies. Shifting the emphasis from teaching to learning demands a more interactive and experiential learning environment for both teachers and learners. These forms of learning environments also involve a change in the roles of both teachers and learners. The role of the instructor is transformed from a knowledge transmitter to that of a learning facilitator and co-learner. When moving from a passive reproduction of inert knowledge to an active creation of applicable knowledge and to the development of useful competencies, gaming simulations have a lot to offer. Gaming simulations create an interactive, cooperative and safe learning environment that makes it possible to cope with complex authentic situations that are close to reality. Learning from multiple perspectives and contexts of use supports flexibility and allows learners to transfer acquired knowledge and skills to explore new domains. Game-based learning is a form of experiential learning, based on qualitative and quantitative models of socio-technical systems. Students, employees and decision makers are feeling and understanding the effects of decisions, thus exploring ideas for possible preferred futures and actions. As Klabbers has pointed out, design - broadly conceived - aims at implementing courses of action with the purpose to change existing (dysfunctional) situations into preferred ones. He distinguishes two levels of design: design-inthe-small and design-in-the-large. Design-in-the-large offers a basis for various forms of consulting, training and education in the attempt to foster new ways of thinking and acting as well as changing social systems. Design-in-the-small produces gaming simulations as interventions and interactive learning environments to enhance education and training. Put to use with this goal in mind, they contribute to the design-in the-large process of complex socio-technical systems and to organizational learning.

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The program committee of ISAGA (International Simulation and Gaming Association) had invited to submit contributions for the 45th ISAGA Conference (July, 2014, FHV - University of Applied Sciences Vorarlberg, Austria). Contributions from both scientists and practitioners were very welcome, as well as contributions that connect a scientific and a practitioner‘s perspective. The conference was organized founded on two pillars called the Science & Research and the Art & Craft of gaming simulation. Authors were in particular invited to contribute along the main theme of the conference, “The shift from teaching to learning: individual, collective and organizational learning through gaming & simulation”, and to present innovative ideas in education and training with simulation games. However, contributions might also focus on a wide range of themes related to theory, research and practice in the field of gaming simulation. A variety of keynotes, research papers, panel discussions, poster sessions and interactive workshops, altogether more than 170 contributions, ensured an interesting program. About one third of the submitted and reviewed full papers are presented in this book. The complete set of all papers and abstracts of posters and workshops is published with wbv as CD-Rom Proceedings. I thank the authors for their valuable contributions of interesting and innovative ideas, experiences and research which are detailed in this book. I thank Andreas Mierer and Sasha Demidoffa for their support in editing, Ingrid Mühlhauser for the original conference design and Yléne Dona for reproducing figures and for the design and layout of this book. I further thank my colleagues Tanja Eiselen and Werner Manahl for their work in the program committee and for being chair of best poster award, Birgit Zürn as chair of the best workshop award and Joseph Wolfe as chair of the best paper award (they also reviewed contributions). I also thank all reviewers, who made possible a double blind peer review with 2-3 reviewers per contribution: Maria Angeles Andreu-Andres, Eberhard Auchter, Heinz Bachmann, Geertje Bekebrede, Roland Böttcher, David Crookall, Thomas Eberle, Andrea Frank, Amparo García-Carbonell, Nils Högsdal, Christian K. Karl, Toshiko Kikkawa, Jan Klabbers, Elyssebeth Leigh, Sebastiaan Meijer, Vincent Peters, Johann Riedel, Stephan Rometsch, Sebastian Schwägele, Riitta Smeds, Richard Teach, Elizabeth Tipton, Friedrich Trautwein, Eric Treske, Shig Tsuchiya, Pieter van der Hijden, Marcin Wardaszko, Helmut Wittenzellner and Gee Kin Yeo. Finally I also thank the sponsors and team partners for their financial support for the whole ISAGA conference. I especially thank the publisher wbv and in particular Nicole Consbruch for the support in publishing the book and the CD-Proceedings. Book and Proceedings are dedicated to Paola Rizzi, who served many years in ISAGA steering committee and who organized an ISAGA conference in Bari in 2001. She also had the idea to create an ISAGA summerschool for game design with the metaphor of the renaissance “officina” in her mind. Officina was a place

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where masters and students could exchange experience, share knowledge and embark on their own voyage of discovery. It was a place where apprentices were the active element of the evolution of their knowledge; a place where it was possible to find co-teaching and co-learning at the same time. She brought together masters from different areas of game design, as well as students and professionals and guided them through the learning and game design experience. She put into practice the 2014 conference theme and inspired more than 250 students from more of 30 nations. Her 10 summerschools in Germany, Poland, Austria, Italy, India, Romania, Suriname, Estonia, USA and Japan also supported to nurture a new generation of gamers. We are grateful for this outstanding performance in the area of Gaming/Simulation. Dornbirn, May 2014 Willy Christian Kriz

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Simulations and Games for Crisis Management: A Journal-Based Literature Review Megan L. Anderson

Abstract Simulation and gaming have emerged as promising tools in the context of crisis management, providing dynamic environments for education and research. In 1997, the Journal of Contingencies and Crisis Management devoted a special issue to simulation and gaming; this article reviews developments in crisis management simulation and gaming published in the journal since. Following the framework used in Faria et. al’s (2009) review of simulation and gaming in the business context, this article is structured to provide a brief history of crisis management simulations and games, and the changing technology employed in their development and use. Further, the changes in why they are used and the current state of crisis management simulation and gaming are also discussed. Finally, research gaps and areas for future research are proposed. Keywords crisis, crisis management, simulation, gaming, exercise, learning, training

1 Introduction Crises are rife with uncertainty. As inherently rare events, each crisis is distinct from the other. Defining variables of a crisis include its type (e.g., flood, explosion, riot, crash), location, affected population, and relevant supporting organizations (Walker, 1994, p.1). These variables are very difficult to predict in advance. Further, the nature of crises and the resources available to deal with them are constantly evolving. These aforementioned challenges exemplify uncertainties that are beyond the practical ability of analysts to predict and which cannot be reduced to risk (Quade, 1989). The dramatic reconception of ideas and practices of risk and responsibility in the past century have given rise to today’s “Risk Societies” (Beck, 1992). A realm that was once thought to be only in the control of a higher power has now

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become a playground for mathematicians and statisticians. Despite the explosion of information seeking and processing capabilities, uncertainty still abounds, plaguing the decision makers of the modern world with age-old qualms. Simulation and gaming have emerged as promising tools to deal with such uncertainties (Walker 1994, p.1), functioning as dynamic environments for teaching and training, research and planning (Kleiboer, 1997). The applicability of simulations to crisis management motivated the Journal of Contingencies and Crisis Management to publish a special issue on this topic in 1997. Yet threat perceptions and technology have evolved significantly since, impacting the nature of simulation and gaming in the crisis management context. This article explores these changes and highlights areas for further research.

2 Methodology We have chosen, following the lead of Bragge et al. (2010), to conduct a journal-based study instead of a content based study. The search is limited to the Journal of Contingencies and Crisis Management, which remains the sole journal to have published a special issue on simulations and games in the crisis management context. We collected data of all published items from 1997 through 2014, choosing the commencement of this timeframe to align with the journal’s watershed, special issue that underlined the significance of simulations in crisis context for the first time. We queried specifically the terms “Game”, “Simulation” and “Exercise”, using the Boolean operator OR. As noted by Kleiboer (1997), these terms are often used interchangeably. There was no option to limit the search further. This yielded 286 results. Subsequently, after eliminating book reviews and opinion pieces, the following criteria were implemented and the search further filtered to align with the research objective. Thus, we included only papers that explicitly discuss the use of seminars, workshops, tabletops, games, drills, and exercises for educational or research purposes in the crisis management context. This filtering process involved manually scanning each article. This yielded 34 articles (from the original list of 286) which specifically fulfill the explicated criteria. After reviewing the set of articles, we aimed to extract major themes, trends and research gaps. Guided by Faria et al.’s (2009) review of business simulation games, the following sections are thus structured so as to provide a brief history of crisis management simulation and games, the changing technology employed in their development, changes in why they are used, and the current state of crisis management simulation and gaming.

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Figure 1 Articles referencing simulation or gaming published in the Journal of Contingencies and Crisis Management from 1997-2014.

3 A Brief History of Crisis Simulations and Games The origins of simulation and gaming in the context of crisis management can be traced back to the 18th century, when combat simulations were used for warfare instruction and tactical and strategic ideation (Starr, 1994 in Kleiboer, 1997, p.198). In order to instruct its officers more effectively, the Prussian army introduced Kriegsspiel (War Games). In addition, maps, tabletops, sandbanks and model armies provided simulation and gaming tools for military strategizing and tactical development. Most probably, the game of chess was originally developed to provide a simulated training experience for senior military commanders (Beckker, 1976 in Kleiboer, 1997, p.198). The purpose and methodology of simulation and gaming coevolved with the changing nature of warfare, and risks - both real and perceived- throughout the 20th century (McConnel & Drennan, 2006, p.86). Military innovations transformed the battlefield, and inter-state wars became less prevalent and less reliant on line and column tactics. Accordingly, after World War II and the rise of modern bureaucracy, the scope of simulations was widened to incorporate other types of crises. These included modern military conflicts, terrorism, disasters and many other political environments featured by high threats, short decision times and high uncertainty (Kleiboer, 1997, p.205). RAND Corporation, Harvard University and the Massachusetts Institute of Technology were among the leading innovators in this domain, addressing both the military and political dimensions of crisis management (Kleiboer, 1997, p.198). Most of the research in this area was conducted at the end of the 1950s and the 1960s, with renewed interest in the 1980s and beginning of 1990s. Neverthe-

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less, developments in the field have continuously outpaced the literature (Kleiboer, 1997, p.198). The scarce literature on the contemporary history of simulation and gaming in the crisis management context is overwhelmingly specific to that of American applications. Babus et al. (1997), for example, detail the origins of training for integrated inter-agency planning for the U.S. government. They credit the 1995 military intervention in Haiti, which illuminated the challenges involved in managing complex contingency operations. This exposed a need for improved lesson-learning mechanisms, resulting in the establishment of a training programme by key White House officials. They emphasized the use of reality-based simulations incorporating lessons learned from past contingency operations, real data and real situations. Although Western European scholarship contributes to much of the research on simulation and gaming in the crisis management context overall, scholars are less detailed in their documentation of the history of simulation and gaming in crisis management in Europe (at least in English). Carrel (2005, p.170), briefly discusses the origin of Swiss civil-military defense exercises in the 1970’s and their evolution since, while ‘t Hart (1997, p.208) summarizes the history of the development of simulations for increasing the crisis preparedness of individuals and organizations by the Crisis Research Center of Leiden University.

4 The changing technology employed in the development and use of crisis simulations and games Undoubtedly, technology plays a major role in crisis simulation and gaming. Networked screens and tablets have, in many cases, replaced sandbanks and tabletops. This section outlines the most influential technological innovations, and how they have transformed the field of crisis management simulation and gaming. Many of the technologies used in crisis simulation and gaming evolve with those already adopted for everyday use by professionals tasked with crisis management duties. Often, these same technologies are used or adapted in simulations and games to maximize fidelity. Since 1997 the major emerging technologies in this regard have been Web 2.0 platforms and mobile devices, which shift the primary means of coordination away from hierarchical forms of organization to a networked-based coordination structure (Chen et al., 2013, p.137). Up until 2005, for example, training exercises for the Swiss federal administration were held at central locations, usually in secure underground facilities (Carrel, 2005, p.172). Technology allowed exercises to finally be conducted from decentralized locations and facilities, as would be done in a real crisis situation. Project organizers used an existing secure communication platform, an Electronic Situation Display (ESD), to ensure that all participants had access to the same level of information from their given locations at the right time (Carrel, 2005, p.172).

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This ESD is a web-based, database-supported communication platform developed and operated by the Swiss National Emergency Operations Centre (NEOC) and is designed to support task forces and command and control bodies. Instead of utilizing existing tools, other simulations and games develop custom-made platforms specifically designed for specific end-user purposes. Babus et al. (1997, p.235), for instance, outline the tools developed for the 1997 U.S. government training programme to improve management of complex emergencies abroad. In 1996, The War Gaming and Simulation Centre (WGSC) developed a customizable software tool to focus and guide players throughout its simulations and games. The software, called the Planning Decision Support System (PDSS), featured text screens for discussion point display, digital maps and icons, text file output and game information upload/download capabilities (Babus et al., 1997, p.235). These tools illustrated the first major adoption signs of computer-based support tools in crisis simulation and gaming, and in crisis management in general. The PDSS was well received by users as a sophisticated and easily comprehensible system that added to the credibility and palatability of the experience (Babus et al. 1997, p.238). More recent developments illustrate the adoption of technologies originating in the video gaming industry, such as three-dimensional environments and virtual characters (avatars), for purposes other than pure entertainment. Vidal and Roberts (2014, p.20) describe France’s Civil Protection virtual reality-based training platform, which displays a three-dimensional environment that integrates a physics model for realistically simulating the spread of fire. Players can guide their avatars to look or go in any direction and engage their virtual crews by talking on the radio to their crew bosses. Similarly, McLennan et al. (2006) detail the use of the Networked Fire Chief (NFC) computer simulation program in their research on incident management team processes. NFC allows for the creation of detailed landscapes displayed on networked computer screens. Participants can control the spread of virtual fires by dispatching fire trucks, helicopters, and/or bulldozers, similar to the capabilities described in Vidal and Roberts (2014, p.20). Wolbers and Boersma (2013, p.189-190), in their study of collective sense making in Dutch emergency response teams, briefly discuss the use of scenario-driven, computer-simulated exercises by field command centres in various safety regions in The Netherlands. Virtually simulated scenarios include a sea collision, gas explosions, railroad and highway accidents, a hostage situation and a helicopter crash. Despite the growth of sophisticated technologies able to simulate catastrophic incidents, which would be difficult to replicate otherwise, scholars still highlight the importance of field drills and exercises that are not reliant on virtual,

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gaming technology. Chen et al. (2013, p.135) praise ‘Meteoro’ a 2-day full-scale simulation in preparation for the hurricane season in Cuba, while Helsloot (2005), describes the significance of large-scale crisis management simulation, Bonfire, in The Netherlands. Chrichton et al. (2000) write of the value of smaller scale low-fidelity tactical decision games designed to exercise non-technical skills, such as decision making, in emergency situations. One study cited the opportunity to make cross-departmental contacts as a defining value of the live simulation exercise experience, highlighting the importance of physical co-location (Perry 2004, p.74). Combined with advances in information and communication technology and gaming innovations, crisis management simulations are entering a new era. The growing ease and decreasing costs of creating simulated environments and gamified experiences for crisis management is noteworthy. Such dramatic shifts directly impact why simulations and games are used. These are discussed in the following section.

5 Changes in why crisis simulations and games are used Many of the uses for simulations and games have remained unchanged for centuries; however emerging technologies have allowed for the use of simulations and games in new and dynamic ways. Kleiboer (1997) notes that in order to adequately understand the function of simulations and games, scholars should first distinguish and define relevant concepts. Accordingly, she concretely defines simulations, scenarios and games. 5.1 Conceptual clarifications Simulations are operating models reflecting the core features of a real or proposed system, process or environment, the essential properties of which are best explained when contrasted with related concepts. These include modelling and forms of interactive learning, such as scenarios and games (Kleiboer, 1997, p.198). Scenarios serve two purposes. Firstly, they are forms of imagined reality used as independent heuristic tools (Kleiboer, 1997, p.198). As such, they provide participants in various domains of policy planning and strategy development, both in government and private sector, with an “opportunity to enact possible states and future developments of a particular social system” (Kleiboer, 1997, p.198). In the context of crisis management, scenarios typically incorporate features of previous crisis events, as well as recurrent crisis management and communication problems. This creates a second purpose - as building blocks for simulations. (Kleiboer, 1997).

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Figure 2 Conceptual boundaries of simulations, scenarios and games

Often used interchangeably or in combination with ‘simulation’ is the term ‘game’; however, not all simulations are games and not all games are simulations (Kleiboer, 1997, p.200). Simulations that contain central game components (goals, activities, payoffs) are considered games (Greenblatt, 1988 in Kleiboer, 1997, p.200). At the same time, games that are designed to epitomize or simulate a part of the real world can be considered simulations. 5.2 Different applications of crisis simulations Following these essential conceptual clarifications, Kleiboer (1997) identifies different forms of crisis simulations: educational simulations (teaching and training) and simulations for theoretical research (hypothesis development, theory testing) and applied research (crisis management strategy development, and crisis management strategy testing, personnel selection).

Figure 3 Different applications of crisis simulations (adapted from Kleiboer, 1997)

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An analysis of the 34 articles included in this review indicate that the research on crisis management simulations and games is overwhelmingly dedicated to their use as tools for educational purposes (see Table 1). There are few opportunities to learn from first-hand experiences due to the low incidence of major crises (t’Hart 1997, p.207); therefore, it proves difficult to rely on ‘real’ experience alone for crisis preparation (Lagadec, 1997, p.28). Consequently, crisis managers often seek to create their own, vicarious experiences by simulating crisis realities (t’Hart 1997, p.207), with the mentality that a trained group will be better equipped to take charge of an exceptional situation and innovate when faced with the unimaginable (Lagadec, 1997, p.28). As an educational tool, however, there has been a shift toward teaching and training both technical and non-technical skills with such methods (Chricton et al., 2009, p. 33). These non-technical skills include command decision making, situation awareness, communication, and leadership, especially under stress (Crichton & Flin, 2002). Devitt and Borodzicz (2008, p.214) refer to the incorporation of more forms of tacit knowledge into training simulations as an interwoven leadership approach, and highlight the importance of “interweaving task skills, interpersonal skills and personal qualities with awareness of the multidimensional requirements of stakeholders in any response”. Various studies note the multiple uses of crisis simulations. In addition to training tools, simulations are also used simultaneously to test the quality of existing plans, organizations, personnel and equipment- exemplifying Kleiboer’s applied research form (Boin & McConnell, 2007; Carrel, 2005; Chrichton et al., 2009). The more recent literature shows an increasing trend in the use of simulations and games for theoretical research (see Table 1). Crisis management simulations have been used to explore theories that attempt to understand and explain cognitive mapping (Alexander, 2004), incident management team processes (McLennan et al., 2006), organizational collaboration (Berlin & Carlstrom, 2008), team coordination (Bergstrom et al., 2010; Vidal & Roberts, 2014), collective framing (Bergeron & Cooren, 2012), and collective sense making (Wolbers & Boersma 2013). While simulations and games have become increasingly popular for theoretical research, scholars are quick to note the multiple limitations of their use for this purpose (Devitt & Borodzicz, 2008, p.210; Vidal & Roberts, 2014, p.27).

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Table 1

The multiple uses of crisis management simulations and games

Use of exercise, simulation, or game

Contextual application

Source

Education

National disaster and crisis management

t’Hart, 1997

Education

Strategic management of overseas complex emergencies

Babus et al., 1997

Education and research

Crisis management in general

Cottam & Preston, 1997

Education and research

Crisis management in general

Hermann, 1997

Education and research

Crisis management in general

Kleiboer, 1997

Education

Crisis management in general

Lagadec, 1997

Education

Foreign policy crisis management

Preston & Cottam, 1997

Education and applied research

Organizational crisis management

Yusko & Goldstein, 1997

Education

Emergency management for high reliability industry

Chrichton et al., 2000

Education

Crisis management in general

Borodzicz & van Haperen, 2002

Education

Crisis management in France

Lagadec, 2002

Education and applied research

Crisis management in general

Robert & Lajtha, 2002

Theoretical research

Exploring cognitive mapping through a strategic emergency management simulation

Alexander, 2004

Education

Crisis management in industry

Elsubbaugh et al., 2004

Education and applied research

Community disaster preparedness

Perry, 2004

Applied research

National, strategic crisis management

Carrel, 2005

Education

Complex incident management

Chricton et al., 2005

Applied research

National crisis coordination

Helsloot, 2005

Education

Crisis management in general

McConnel & Drennan, 2006

Theoretical research

Studying incident management team processes in simulated wildfire incident environments

McLennan et al., 2006

Applied research

Critical infrastructure breakdown preparedness

Boin & McConnel, 2007

Education

Inter-municipal emergency management

Palm, 2007

Theoretical research

Exploring theories of inter-organizational collaboration through accident management simulations

Berlin & Carlstrom, 2008

Theoretical research

Studying the role of leadership in multi-agency major incident response

Devitt & Borodzicz, 2008

Education and applied research

National disaster and crisis management

Scholtens, 2008

Education and applied research

Cross-boundary, multi-agency crisis management

Chrichton et al. 2009

Applied research

Organizational crisis planning

Somers, 2009

Theoretical research

Studying team coordination in unexpected and escalating situations

Bergstrom et al., 2010

Education

Crisis cooperation in government

Odlund, 2010

Theoretical research

Studying collective framing through a municipal crisis management simulation

Bergeron & Cooren, 2012

Education

Large-scale disaster management

Bratterberg, 2012

Education

Inter-sectoral collaborative disaster resilience

Chen et al., 2013

Theoretical research

Studying collective sense making in a simulated emergency response environment

Wolbers & Boersma, 2013

Theoretical research

Studying team coordination in a simulated incident management environment

Vidal & Roberts, 2014

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6 The current state of crisis management simulations and games In 1997, Lagadec wrote of the changing perception of simulations and games for crisis management: “Feedback exercises and simulations are no longer frightening monsters, but are becoming practices that are increasingly incorporated into an organization’s benchmarks” (p.30). Today, the value of conducting simulations is highlighted in most textbooks on disaster and crisis management and mandated by legislation and executive rules in connection with a variety of natural and technological threats in most industrialised nations (Perry, 2004, p.64). Despite widespread use of simulations, it remains that there is very little research precisely demonstrating their benefits and design (Perry, 2004, p.64). Indeed, Babus et al. (1997, p.238) and Borodzizc and Van Haperen (2002), reiterating this lack of research, have pointed out that crisis simulations themselves should be scrutinised and designed carefully, with precisely defined objectives, and accessible and user-friendly tools. Moreover, with regard to educational simulations, no training package is ever final and the balance of elements that ensure high-quality, effective professional training is delicate and must be maintained in all its aspects for sustained success (Robert & Lajtha, 2002). This perspective is reiterated by Devitt and Borodzicz (2008, 214) who recommend an adaptive, flexible and holistic approach that is “supported by the wider organizational culture in normality and incorporated into organizational training at many levels”. This fits with the overall shift to a more fluid, holistic and all-hazards approach to crisis management as a “continuous management process that can be revised or redesigned at any time and that should be updated/enriched with feedback from experience and simulation exercises” (Robert & Lajtha, 2002). Simulations can take many forms and are nowadays becoming increasingly cost-efficient and creative, avoiding long, heavy exercises (Lagadec, 2002, p.165). Nevertheless, users tend to be weary of the incorporation of advanced virtual environments, rich multimedia, and games technologies into these processes (MacKinnon & Bacon, 2012, p.1).

7 Conclusion This paper has reviewed the literature on simulation and gaming in the context of crisis management, with the aim of highlighting the history of crisis management simulations and games, the changing technology employed in their development and use, the changes in why they are used and the current state of crisis management simulation and gaming. As this review was limited to research published in the Journal of Contingencies and Crisis Management from the year 1997-2014, a more comprehensive review with a wider scope is encouraged.

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Reviews have shown that claims about the effectiveness of simulations and games more generally are not always justified (Wouters et al., 2010 p.1): “The use of simulation and games is increasing, but in schools and universities, doubt still lingers…maybe because we have not yet demonstrated with hard research that simulation/games can be a force for good…” (Crookall, 2010, p.913). Consequently, if these methods are going to be more widely adopted, it is vital to answer important questions about their nature, their use, and their effectiveness so that crisis management systems can benefit accordingly. Thus, areas for potential research include the perception and adoption of simulations and games by organizations and agencies operating in the crisis management domain. The technology acceptance model and the Model of Technology Appropriation could provide fruitful theoretical frameworks. In order to design more appropriate simulations and games, Lee et al. (2009, p.745) recommend that academics pay increased attention to how they can foster or incorporate theory and how the process of theory building can help academics work with practitioners to create more appropriate learning environments and solutions. It might therefore be useful to more systematically study the design of simulations and games in the context of crisis management with questions such as, what are the best practices of simulation and game design processes in the crisis management context? Further, how can concepts from the game based learning literature inform the design and implementation of crisis management simulations, exercises and games. While numerous studies have been conducted on the development and use of simulations and games in other contexts (see Faria et al., 2009 for a 40 year history of business simulations), their application in the field of crisis management has yet to be researched to such a comparable extent. Kleiboer’s (1997, p.198) conclusion that literature lags behind developments in the field- thus remains relevant today. In order to catch up, the field would benefit from filling the research gaps proposed in this review.

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Learning Processes for Crisis Management in Complex Organizations. Journal of Contingencies and Crisis Management, 5(1), 24—31. doi:10.1111/1468-5973.00034 McConnell, A., & Drennan, L. (2006). Mission Impossible? Planning and Preparing for Crisis. Journal of Contingencies and Crisis Management, 14(2), 59—70. doi:10.1111/j.1468-5973.2006.00482.x McLennan, J., Holgate, A. M., Omodei, M. M., & Wearing, A. J. (2006). Decision Making Effectiveness in Wildfire Incident Management Teams. Journal of Contingencies and Crisis Management, 14, 27—37. doi: 10.1111/j.1468 5973.2006.00478.x Ödlund, A. (2010), Pulling the Same Way? A Multi-Perspectivist Study of Crisis Cooperation in Government. Journal of Contingencies and Crisis Management, 18, 96—107. doi: 10.1111/j.1468-5973.2010.00605.x Palm, J. (2007). Developing Local Emergency Management by Co-Ordination Between Municipalities in Policy Networks: Experiences from Sweden. Journal of Contingencies and Crisis Management, 15(4), 173—182. doi:10.1111/j.1468 5973.2007.00525.x Perry, R. W. (2004). Disaster Exercise Outcomes for Professional Emergency Personnel and Citizen Volunteers. Journal of Contingencies and Crisis Management, 12(2), 64—75. doi:10.1111/j.0966-0879.2004.00436.x Preston, T., & Cottam, M. (1997). Simulating US Foreign Policy Crises: Uses and Limits in Education and Training. Journal of Contingencies and Crisis Management, 5(4), 224—230. doi:10.1111/1468-5973.00060 Quade, E.S. (1989). Analysis for Public Decisions. Third Edition. New York: North-Holland. Robert, B., & Lajtha, C. (2002). A new approach to crisis management. Journal of Contingencies and Crisis Management, 10(4), 181—191. doi:10.1111/1468-5973.00195

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Scholtens, A. (2008). Controlled Collaboration in Disaster and Crisis Management in the Netherlands, History and Practice of an Overestimated and Underestimated Concept. Journal of Contingencies and Crisis Management, 16(4), 195—207. doi:10.1111/j.1468-5973.2008.00550.x Somers, S. (2009). Measuring Resilience Potential: An Adaptive Strategy for Organizational Crisis Planning. Journal of Contingencies and Crisis Management, 17(1), 12—23. doi:10.1111/j.1468-5973.2009.00558.x Vidal, R., & Roberts, K. H. (2014). Observing Elite Firefighting Teams: The Triad Effect. Journal of Contingencies and Crisis Management, 22, 18—28. doi: 10.1111/1468-5973.12040 Walker, W. E. (1994). The use of scenarios and gaming in crisis management planning and training. Santa Monica, CA: RAND. Wolbers, J., & Boersma, K. (2013). The Common Operational Picture as Collective Sensemaking. Journal of Contingencies and Crisis Management, 21(4), 186—199. doi:10.1111/1468-5973.12027 Wouters, P., Van der Spek, E. D., & Van Oostendorp, H. (2009). Current practices in serious game research: a review from a learning outcomes perspective. In T. M. Connolly, M. Stansfield, & L. Boyle (Eds.), Games-based Learning Advancements for Multisensory Human Computer Interfaces: Techniques and Effective Practices. Hershey: IGU Global Yusko, K. P., & Goldstein, H. W. (1997). Selecting and developing crisis leaders using competency-based simulations. Journal of Contingencies and Crisis Management, 5(4), 216—223. doi:10.1111/1468-5973.00059

Author/Contact Megan L. Anderson University of Leiden Center for Terrorism and Counterterrorism The Hague, The Netherlands [email protected]

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Gaming in Higher Education: Students’ Assesment on Game-Based Learning M a Ángeles Andreu-Andrés, Miguel García-Casas

Abstract This study examines the use of gaming as a teaching-learning approach in a group of higher education students and analyzes how they assess and perceive the gaming that has been integrated as part of their course activities to reinforce previously covered material and introduce new one in a subject of their degree throughout a semester. The relation among the variables examined lets us know the students’ opinions concerning gaming as opposed to more prevalent strategies. All things considered, students participating in the research endorse experiential learning and corroborate they learn and have fun when gaming in class activities. Keywords game-based approach, higher education, students’ opinions

All the world’s a game, And all the men and women merely players: They have their exits and their entrances; And each person in their time plays many parts… (Adapted from Shakespeare by Dave Moursund, 2007)

1 Introduction Gaming is becoming a popular technique in many universities despite the fact that it seemed to belong to kindergartens and young children and, as Gredler (2004) mentions, their use decreases in higher education. Nonetheless, literature on gaming and simulation shows that they are used to teach disciplines such as Engineering (Mayo, 2007; Kuk, Jovanovic, Joranovic, Spalevic, Caric & Panic, 2012), Public Administration and Political Science (Silvia, 2012), International Re-

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lations (Shellman & Turan, 2006), Management and Leadership (Yaghi, 2008; Crosby & Bryson, 2007), Agricultural Engineering (Boehje, Dobbins, Erickson & Taylor, 1995), Civil Engineering (Ebner & Holzinger, 2007), Languages (Crookall & Oxford, 1990; Hubbard, 1991; Cabré & Gómez, 2006; García-Carbonell, Watts& Andreu-Andrés, 2012; Angelini, 2012; Montero-Fleta, 2013; Angelini & García-Carbonell, 2014), Nursing (Aebersold & Tschannen, 2013), Medicine (Lane, Slavin & Ziv, 2001; Mann, Eidelson, Fukuchi, Nissman, Robertson & Jardines, 2002; Premkumar & Bonnycastle, 2006; Okuda et al., 2009), Chemistry (Rastegarpour & Marashi, 2012), Mathematics (Piu & Fregola, 2011), Physics (Squire, Barnett, Grant & Higginbotham, 2004), Economics (Zapalska & Brozik, 2008), Business (Faria, 2001; Siewiorek, 2012), Social and Emotional Learning (Hromek & Roffey, 2009), and Sciences (Sahin, 2009), among other fields of study. Despite the fact that most of the literature on game-based learning for adult education mainly explores design and development of learning games (Greenblat, 1988; Prensky, 2001; Duke & Geurts, 2004; Moreno et al, 2008), their educational value (Gredler, 2004; Fortmüller, 2009; Yien et al., 2011), the impact on students’ learning (Deesri, 2002; Shu-yun, 2005; Macedonia, 2005; Tan et al., 2010), the learners’ profiles and expectations (Kuk et al., 2012), games’ effectiveness (Paras & Bizzocchi, 2005; Annetta et al., 2010; Guillen-Nieto & Aleson-Carbonell, 2012) and academics’ real views on the use of educational games in Higher Education (Cuenca and Martin, 2010; Ruggiero, 2012), seldom have the university students’ viewpoints on this teaching-learning approach been examined; a goal that it is pursued in this study as mentioned below and in the following section. In the foreword of Nygaard, Courtney and Leigh (2012, x-xiii), Geurts and Duke highlight that there is a clear connection between the students’ capacity to play in higher education and their future success as graduates. In their opinion, university students do not play enough as an approach to learn and develop themselves; meanwhile teaching is still following boring and inefficient strategies that turn their back on a learning-focused world of gaming and simulation. We consider that an important role of higher education is to facilitate the development of individual and social skills that are different from those that traditional methods can offer. Accordingly, students need gaming as part of their education and experiential learning to gain not only knowledge but skills and attitudes, at no expense, in order to become good professionals in a modern workplace of continuous change and innovation; a fact that our subject on language learning as a foreign language aims to do by using gaming and simulation as part of our course program. Learning, however, does not end with the game itself but with its debriefing (Lederman & Fumitoshi, 1995) since it is regarded as the bridge between gaming and making use of the knowledge and skills gained to other contexts. We, as instructors, can facilitate this connection through discussions before and after the

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game that allow students to link it with what they are learning in class sessions (Ash, 2011). Among the many interactive learning techniques used in game-based learning, Prensky (2001) points out “learning from mistakes” considering failure an opportunity for the gamer to get feedback and a motivation to keep on trying as opposed to the explanation provided by instructional material; a technique that has been largely used in the educational games employed in our subject throughout a semester. This paper, as part of a broader investigation, studies the results of their participation by focusing on the students’ assessment on gaming at the time it searches what other experiences with games these engineering students had in subjects attended before and during their university studies.

2 Aims and Methodology The use of gaming, in different supports, as a teaching-learning approach is surveyed in a sample of forty seven higher education students of a Spanish university, with ages that range from 20 to 25 years old; some examples of the games and simulations used as part of their syllabus are listed at the end of this section. After finishing the course, a statistical analysis of the answers to a questionnaire offers the opportunity to examine, on the one hand, the use of gaming as a teaching-learning technique in our subject with the purpose of reinforcing previously covered material, introducing new one and helping them develop teamwork, communication and problem solving skills; on the other hand, their answers let us know the students’ experience with the technique in different subjects attended before and during their university studies as well as their perspective on using games to learn or just having fun with them. This is a first step of a thorough study on the students’ perceptions on gaming and the relationship with their learning styles and the quality of their learning. Among the games in different supports (board, card, digital, computer-based and computer supported games) implemented, it can be mentioned the following: Two truths and a lie, a get-to-know-you Playing Dominoes, by Sue Kay and Vaughan Jones: To practice noun formation Hidden Word, by Ceri Jones, Tania Bastow, Sue Kay and Vaughan Jones: To improve fluency Bottle Tower, Construction Game by Michael Cardus: To explore various aspects of teamwork, planning, and delegation Grammar Casino, collaborative game to correct, recognize and explain grammatical structures, from http://www.macmillanenglish.com/straightforward ◆◆

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Board and Card Game 90 Days: To generate a list of potential situations faced

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by a new manager and to examine their positive or negative impact, from http:// thiagi.com/pfp/IE4H/march2009.html#BoardAndCardGame Online digital game to practice prefixes and suffixes, from http://www.english-online.org.uk/games/prefixgame2.htm Online digital game to review prepositions, from http://www.marks-english-school.com/games/b_prepmed.html Computer-assisted games: Culturball & Culturbasket and Tras la Pipa (among others) by Andreu and García: To review specific terminology and functions of the language, from http://www.upv.es/jugaryaprender/ingles/ingles3.htm Computer-based simulation Design your School, from The Open University http:// www.open.edu/openlearn/science-maths-technology/engineering-and-technology/design-and-innovation/design/design-school Situational simulation The School Board by EduSim: To test group decision-making skills and conflict management techniques Situational simulation The Parks Commission by EduSim: To enhance participants’ critical thinking, leadership and team-working skills

3 Results In the questionnaire participants assess anonymously 34 statements (see table 1) by rating them from 0 to 10. Table 2 shows the meaning of every mean value. These statements have been designed in order to study not only possible characteristics that may be related with the university students who like gaming as an active learning technique and those who do not, but their assessment after having used the technique in our subject and their experience with it in other courses.

u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u

14

I like videogames

15

I have a computer at home

16

I frequently use the computer at home

17

I maintain contact with my classmates

18

I like to be alone

19

I prefer traditional multiple choice questions on paper

20

I prefer questions that are included in games

21

Educational games help me review contents and learn new ones

22

Games are interesting

23

Games are necessary

24

Games are educational

25

Games are ingenious

26

Games are enjoyable

27

Games are amazing

28

Games are appealing

29

Games are useful

30

Games are motivating

31

I learn playing games

32

Games are not serious

33

Games waste my time in class

34

I am good at gaming

Table 1 Statements students assess anonymously regarding their opinions on using games as a teaching-learning approach

Mean value

Meaning

0.00 to 2.00

Strongly disagree

Number

Statements

2.01 to 4.00

Disagree

1

I like playing

4.01 to 6.00

Neutral

2

I like studying

6.01 to 8.00

Agree

3

I get good marks at University

8.01 to 10.0

Strongly agree

4

When I studied primary or secondary school I got good marks in Mathematics, Physics, etc.

5

When I studied primary or secondary school I got good marks in History, Languages, etc.

6

I have a lot of friends

7

Teachers have made me play to learn in primary and secondary school

8

Teachers have made me play to learn subjects on sciences in primary and secondary school

9

Teachers have made me play to learn subjects on humanities in primary and secondary school

10

Teachers have made me play in Physical Education (PE)

11

Professors at University have made me play in subjects dealing with sciences

12

Professors at University have made me play in subjects dealing with languages

13

I like computers

Table 2 Meaning of the mean values

Table 3 offers the mean value of every statement revealing that these students prefer playing to studying and their grades at University are less favourable than the ones obtained in secondary school, with higher marks in subjects such as Mathematics, Physics, etc. than in Literature or Language, for example; a reality that was expected due to the students’ profile. Students think they are sociable as they have friends, do not like solitude and maintain contact with their classmates. They also emphasize their lack of gaming in primary and secondary school except in PE although in the university

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they mainly play games in subjects dealing with languages. Despite the fact that they like computers and regularly use them, they do not enjoy videogames so much as it can be anticipated. When they are inquired to choose between traditional multiple choice questions on paper in order to check comprehension, test knowledge on a topic and learn from mistakes, and the possibility of including this type of questions in games, they prefer the latter. In their opinion, they learn playing games and consider them useful, enjoyable and educational. Students decline to consider games as non-serious activities that make them kill their time in class and declare that they are generally good at gaming. Number

Statements

Mean Value

u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u u

27

Games are amazing

5.77

28

Games are appealing

6.95

29

Games are useful

7.23

30

Games are motivating

6.70

31

I learn playing games

7.12

32

Games are not serious

3.39

33

Games waste my time in class

2.39

34

I am good at gaming

6.95

Table 3 Mean value of every statement or variable

Statements 1 1

1

I like playing

8.34

2

I like studying

5.72

3

I get good marks at University

5.04

13 19

4

When I studied primary or secondary school I got good marks in Mathematics, Physics, etc.

7.89

5

When I studied primary or secondary school I got good marks in History, Languages, etc.

6.45

6

I have a lot of friends

7.54

7

Teachers have made me play to learn in primary and secondary school

3.66

8

Teachers have made me play to learn subjects on sciences in primary and secondary school

3.25

9

Teachers have made me play to learn subjects on humanities in primary and secondary school

3.36

2

13 19 20

21

22

23

0.46 0.41 0.39

2

24

25

26

27

28

0.34

29

30

31

32

0.51 0.33

0.50

33

34

-0.31 0.36

0.38 0.44

0.31 -0.37

-0.34

-0.49

20

0.49 0.45 0.30 0.52

0.45

21

0.73 0.35 0.66

0.58

22

0.39 0.74

0.32 0.80

-0.56 -0.30 0.47 0.52

-0.31

0.49 0.73 0.51 0.49

0.45

0.62 0.82 0.47 0.39 -0.31 -0.44 0.45

23

0.37 0.47 0.36

0.31 0.36 0.59 0.69

24

0.43 0.67

0.42 0.78 0.36 0.41

-0.37 0.48

10

Teachers have made me play in Physical Education (PE)

7.93

11

Professors at University have made me play in subjects dealing with sciences

3.13

12

Professors at University have made me play in subjects dealing with languages

6.07

13

I like computers

7.02

14

I like videogames

5.12

28 29

0.55 0.42

-0.35 0.58

30

0.76

0.42

15

I have a computer at home

9.28

16

I frequently use the computer at home

7.35

17

I maintain contact with my classmates

7.51

18

I like to be alone

3.91

19

I prefer traditional multiple choice questions on paper

4.95

20

I prefer questions that are included in games

6.19

21

Educational games help me review contents and learn new ones

6.77

22

Games are interesting

7.19

23

Games are necessary

6.44

24

Games are educational

7.35

25

Games are ingenious

7.07

26

Games are enjoyable

7.49

25

0.37 0.66

0.34 0.72 0.77

26

0.64 0.71 0.42

27

0.37

-0.38 0.49

0.59 0.49 0.67 0.56

-0.38 -0.35 0.67

31 32

0.64

33 Table 4 R values with statistical significant relation

In order to analyse the relationship among the statements a correlation analysis between pairs of them is done to find possible significant relations and their intensity based on the correlation coefficient value. Table 4 shows R values of the

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statistically significant correlations. The closer R value is 1, the greater the reliability of the relationship is. To facilitate the understanding of the table, only the R values with statistically significant relationships equal to or higher than 95% are shown. The size of the sample (47) is included in the calculations of every correlation even though it is not mentioned in the table. Nevertheless, the results that are not significant are omitted as their levels of significance could reach 95%, if the sample were increased. These results make us infer that students who like playing prefer questions that are included in games instead of traditional questions on paper. They understand that games help them review and learn new contents of the subjects. Besides confessing they are good at playing, they find games interesting, educational, useful and motivating. The more they like playing, the less they feel games make them kill their time in class, since there is an inverse statistically significant relationship between those who like gaming and the reflection that games are a waste of time in class. However, those students who prefer studying consider that the games they play in the subject are necessary, motivating and make them learn. For learners who are in favour of traditional questions on paper there is an inverse statistically significant relationship between the fact of learning by gaming and their opinions regarding games: The more they prefer traditional multiple choice questions on paper, the less they seem to appreciate games and the more they consider them non-serious activities to do in class. Conversely, learners who prefer questions included in games think games help them review contents and learn; so, the more they like this type of questions, the less they feel games make them waste their time in class sessions. Consequently, the more interesting, educational, enjoyable, appealing and useful the games are, the less students think games make them kill their time in class. In addition, those who brand games as motivating show with an R value close to 1 that they learn when playing. Nonetheless, there is a significant statistically relationship between those learners who believe games are non-serious activities and their feeling that such activities make them waste class time. To sum up, from the statistically significant relationships found, it can be deduced that learners influenced by more traditional class activities undervalue gaming and feel they are non-serious activities that make them idle away class time. Nevertheless, learners who are in favour of less traditional activities and those who affirm they like studying together with the students who consider games interesting, necessary, educational, ingenious and amazing endorse the experiential learning approach as they ratify that they learn with games.

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4 Conclusions The forty-seven higher education students that have participated in this study underline their lack of gaming in primary and secondary school except in Physical Education; learners also admit that in their university studies they mainly play games in subjects dealing with languages, despite the widespread use of gaming in different subject areas around the world, as mentioned in the introduction of this study. Altogether, they back experiential learning and assert that they learn and have fun with gaming in class; they refuse to consider games as non-serious activities that make them waste their time in class; therefore, the more they like playing, the less they feel games make them dally in class sessions. However, there is a significant statistically relationship between learners who believe games are not serious activities and the feeling that such activities make lessons unproductive. Additionally, learners who are in favour of more traditional activities underrate games; it is possible that this minority of students belong to the group of learners for whom games may not be an effective teaching-learning approach as they do not like playing or have to struggle to process the information. Nevertheless, learners who back less traditional activities, together with those who affirm they like studying and those who consider games interesting and amazing, declare that they learn with games. Therefore, it can be said that, in spite of the mismatch among learners’ perspectives, a majority underpin the use of games; results that suggest an in-depth future study to assess the congruence between students’ preferences, instructor’s teaching style and quality of learning. As stated by Felder and Silverman (1988) and recalled by Felder (2002), how much students learn in class sessions is partially influenced by the harmony between students’ learning styles and the instructor’s teaching style. The initial results of our study make us wonder about the possible relationships among the students’ assessment on gaming and their learning styles as well as the quality of their learning since neither all games can be educational and effective learning environments, nor all of them can be good for all learners or all learning outcomes (Oblinger, 2006). A step forward on which we are currently working.

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Authors/Contact Mª Ángeles Andreu-Andrés Universitat Politècnica of València, Spain [email protected] Miguel García-Casas IES La Moreria, Mislata, Valencia, Spain [email protected]

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Student Perceptions of Gain in Telematic Simulation M. Laura Angelini, Amparo García-Carbonell, Frances Watts

Abstract The demand for quality training in the acquisition of communicative competence in English as a Foreign Language motivated the use of simulation and gaming methodology, specifically telematic simulation, with a cohort of engineering students. After the event, participants were polled by way of a Likert-type questionnaire and an open question. The objective of this paper is to report the findings of the qualitative analysis of the responses to the open question. The study of the students’ perceptions regarding telematic simulation shows that participants experienced satisfaction with the methodology, improved their oral and written production skills and consolidated their interpersonal skills. Keywords communication skills; interpersonal skills; language learning; simulation and gaming; telematic simulation

1 Introduction One of the challenges that university teachers of foreign languages face is to provide the tools and necessary practice that will lead students to reach not only an acceptable level of foreign language proficiency that will allow them to communicate effectively, but also the interpersonal skills that should form part of the process and product of teaching and learning. Language policy, curriculum design and assessment are explicitly discussed in the Common European Framework of Reference for Languages (CEFR) published in 2001. The CEFR has become indispensable in unifying criteria for all levels of users, especially teachers. Insofar as the interpersonal skills, the definition and demand have been made clear by organizations such as the Organization for Economic Co-operation and Development, in its Assessment of Higher Education Learning Outcomes (AHELO) initiative, as well as by the Centro Interamericano para el Desarrollo del Conocimiento en la Formación Profesional (CINTERFOR) and the American Board for Engineering and Technology.

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Simulation and gaming is an engrossing way to meet the challenge because it provides a rich framework of theory, practice and research into which teachers can plunge, find solutions and have a good time as well. As Klabbers (2001) points out, simulation and gaming produce interactive learning environments and aim at developing expertise. The learning environments combine the interacting key elements of knowledge, motivation and performance, together with metacognitve, learning and thinking skills. Students come out of a simulation or game with a heightened awareness of what they know and how to go about getting to know more. The stock of virtues that simulation and gaming has for language learning was discussed at length by García‐Carbonell, Rising, Watts and Montero (2001). Increased exposure to the language of study, better interaction, declassrooming the classroom, comprehensible input for learners, lowering of the affective filter and reduced anxiety in learning language are some of the advantages. The research by García-Carbonell (1998) and by Rising (1999) gave evidence of the effectiveness of simulation and gaming in the acquisition of communicative competence in English as a foreign language (EFL). Angelini (2012) has delved further into using simulation and gaming in the acquisition of production skills in EFL. This paper presents the portion of her findings that refers to the qualitative analysis of participants’ impressions after taking part in a telematic simulation. The number of qualitative studies on perceptions of students participating in virtual simulations is relatively small. Wasson and Morch (2000) carried out a qualitative study on the impressions of 32 university students that participated in collaborative telelearning scenarios, such as is the IDEELS telematic simulation (IDEELS: Intercultural Dynamics in European Education through online Simulation http://www. ideels.uni-bremen.de/). Their interest focused on the personal relationships, tools and tasks that can stimulate collaborative work. The study concluded that the adaptation of students to a virtual collaborative work strategy can be more effective after identifying a common objective that facilitates coordination of team activities and makes the individual part of a learning community. Ekker (2000) carried out a study with 46 students from four different European universities who participated in IDEELS. Analysis of responses to pre- and post-simulation online questionnaires showed that 90% of the students considered it a good learning experience. Around 73% felt that telematic simulation suited their needs. More than 80% did not experience difficulty with cultural differences. Interestingly, all the male participants, in contrast to 22% of the females, deemed that all the members of the group contributed to the tasks. In 2004, Ekker studied 230 subjects who had participated in various editions of IDEELS, examining level of satisfaction and attitudes. Personal characteristics did not significantly predict or affect user satisfaction with telematic simulation. These findings contrast with those of Prince (2004) and Orr (2003) who pointed out that sex, age, personality type, level of experience and computer knowledge were important predictors of attitudes

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towards computers and final user satisfaction. Ekker, although careful to point to the need for further research, detected a more positive attitude towards Internet-based simulation over time, as a result of the improvements in the software and the characteristics in the communications platform used. Ekker and Sutherland (2005), via polls of 237 students who had participated in different telematic simulations between 2000 and 2004, found that neither background characteristics nor the variables that intervene in the learning process had an effect on attitude change towards such issues as human rights, information technology and society or immigration. The duration of the simulation did, however, have a positive effect; the longer the simulation, the more probable that students show a more positive attitude towards and awareness of a person’s individual rights. Sutherland and Ekker (2011) analyzed learning styles and reticence towards team work in 240 third-year university students participating in a large-scale telematic simulation. The Paragon Learning Style Inventory together with questionnaires on satisfaction that measured attitudes before and after treatment were used to explore the degree in which learning styles affected attitudes towards team work before the simulation and perceptions later of the simulation as a learning experience. The study concluded that students experienced a very positive change in attitude towards team work and that the combination of physical and virtual environments, as well as the opportunity for collaborative work afforded by the telematic simulation, work well for a wide range of learning styles. Woodhouse (2011), by way of four different scenarios and of a personal interview, gathered the opinions of 33 Thai university students, who participated in a computer simulation to learn English. The study concluded that the students perceived that the simulation, although not face-to-face, did not keep them from getting to know socio-cultural aspects of communication of the language. Students noted having acquired greater power of decision, persuasion and assertiveness in communication. Watts, García-Carbonell and Rising (2011) examined perceptions (N=26) of collaborative work in telematic simulation in the evaluations collected from the individual portfolios presented at the end of the course. Findings showed that students highly valued the collaborative work required in the simulation, which was reflected in the active participation of all group members and the motivation and personal satisfaction with which they worked. From the analysis of their own work and that of their work groups, the students perceived that they learned different ways to solve problems, gained insight into group organization techniques that increase effectiveness and that collaborative work increased intellectual maturity and “knowledge of the world”. Correspondingly, they understood specific content faster, improved language skills and acquired experience in self-assessment. Andreu-Andrés and García-Casas (2011) focused on simulation and gaming as a teaching strategy. Qualitative analysis using grounded theory showed the

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perceptions of 47 engineering students who supported experiential learning and said that that they had fun while learning, rejecting that simulations or games were not serious. Increased familiarity with the strategy led to higher appreciation of its effectiveness. However, the authors found a statistically significant relationship between the students who believed that it was not a serious strategy and the sensation of it as a waste of time, in contrast to those who considered the strategy to be fun, motivating and effective. Other studies corroborate that simulation and gaming in language teaching foment the development and acquisition of competences such as team work, negotiation, decision making, leadership and intercultural communication, among others (Andreu-Andrés, García Casas & Mollar García, 2005; Angelini & García-Carbonell, 2014; Asal & Blake, 2006; Bytheway, 2013; Blum & Scherer, 2007; De Garmo, 2006; Garcia-Carbonell & Watts, 2012; García-Carbonell, Watts & AndreuAndrés, 2012; Guribye & Wasson,1999; Lay & Smarick, 2006; Rising, 2009; Vavrina, 2006; Wedig, 2010, to cite a few). However, the number of studies that examine student perceptions in learning a language through telematic simulation is still low, which accounts for the studies dating after the year 2000.

2 Materials and method In the broader field study by Angelini (2012), engineering students of EFL (N=65) from the Universitat Politècnica de València, Spain, participated in a large-scale telematic simulation of the International Communications and Negotiations Simulations Project (http://www.icons.umd.edu/). The scenario consisted of an international summit on current economic, social and security issues, attended by countries which were represented by student teams from around the world. Attendance was both synchronous and asynchronous. The central action phase of the simulation was preceded by an intensive briefing phase and followed by in-depth debriefing. This paper presents the results of the qualitative analysis of the 31 student responses to the open question that finalized a Likert-style survey, which was administered to the participants upon completion of the simulation. The data from the 47-item questionnaire were examined through discrete quantitative analysis. Students were given the opportunity to offer their perceptions with the prompt: Please express your opinion of your experience in the telematic simulation. The study of the subjects’ opinions followed the protocol for grounded theory set out in Charmaz (2006, p.11), in which responses are first coded, then sorted into preliminary categories until the data are saturated and subsequently analyzed to select central conceptual categories that give rise to the results. The responses were analyzed with ATLAS.TI, version 5.2.

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3 Results Analysis of the coded data first brought into focus four preliminary categories with student comments on English, telematic simulation, increased knowledge and better interpersonal relationships. Closer scrutiny yielded three categories related to (1) metalinguistic awareness, (2) methodological awareness and (3) cognitive awareness. The segments of the student comments reported here have been translated from the original Spanish and are identified by the letter S and number of the student author of the comment. 1 Metalinguistic Awareness Those surveyed valued their improvement in communication skills very highly. They highlighted production skills in oral and written expression as the most exercised and, in consequence, the most improved. In spite of the fact that some consider that no new grammar was taught in class, the general opinion was that existing knowledge was consolidated, which made them capable of expressing themselves with richer vocabulary in contexts similar to the real world. The course doesn’t teach new grammar but undoubtedly helps to improve the levels of speaking and comprehension that you already have (S1). I liked it a lot. I have improved in everything in general, but I think that I have gained more vocabulary and have expressed myself better writing in the teleconferences (S4). What I liked best about the subject was that, without teaching us material as is done in other courses, we have improved so much in speaking, vocabulary and grammar. With just creating the groups in which necessarily you are obligated to speak in English like in real life (S7). Many students noted an imbalance in knowledge of English in the groups and attributed to it the difficulty in carrying out tasks. It is worth mentioning that the total population of the study accredited having a B1 level of English; since many participants in other countries were native speakers of English, the language level of the subjects under study may be judged a problem. In line with this thinking, there were some who felt that it was not the difference in knowledge of the language but the mastery of certain skills over others. According to some, the variability in knowledge did not slow team work down and allowed the delegation of responsibilities in keeping with the strengths and weaknesses of each member of the group. The level of the participants is uneven; it is also necessary to learn to understand people with more or fewer language resources than one has. Some contribute more advanced knowledge of grammar and others, the facility to express themselves in speaking and writing (S11). I liked this experience enormously. I have learned new vocabulary. My difficulty has been to express myself in writing but my team mates have compensated my

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lack. I have collaborated with vocabulary and analysis of the topics that we had to debate (S24). The central themes of the category Metalinguistic Awareness present in the testimonies of those surveyed were speaking, writing and reading; and recurring themes were new vocabulary and grammar. Variation is discovered when considering knowledge variability, which some attribute to knowledge of English and others to general communication skills. For example, some students consider that this experience is a chance to measure their level of English against that of others and thus assess their own language competence. They observed the disparity in levels of knowledge and recognized their strengths and weaknesses in the mastery of the language. Thanks to the telematic simulation, some students stated that they had modified how they expressed themselves and improved their speaking with the practice that the methodology required. From my point of view, the average English level of the class was higher than mine. But I am convinced that having to speak, listen and exchange ideas with other students made me improve my English (S8). My level was lower than that of my group, but even so I think that this way of learning English helped me. I admit that I still have a ways to go to express myself fluently, that’s what is hardest. But I was able to do everything that my group needed and I spoke English (S28). One of the main aspects that students highly appreciated was the change in how to manage the language. Although students said the level was high, they also recognized change upon acquiring greater listening and reading comprehension, better mastery of speaking and writing and richer vocabulary and language structures. The level was much higher than in classes I have had before. That’s why I think I have improved more than in other years (S14). I think the subject has improved my English level. I have read many messages and each time looked up the vocabulary so that I would be able to use it again, as well as the structures of the sentences (S15). Becoming conscious of the usefulness of English is another central issue that students regarded that the simulation and gaming methodology favored. Some stated that, “Everything is going towards English, so you have to have a good level (S22)”. Consciousness of one’s own errors in using the foreign language is also noted. “The course has made me aware of the mistakes I make in using English” (S2). 2 Methodological awareness With respect to the results derived from the category Methodological awareness, perception of the overload of the information that students had to manage and assimilate due to the telematic simulation was clearly evident.

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There were lots of countries participating and the teleconferences were very fast. This created confusion. Sometimes there was too much information at once (S10). … at times too much information was handled, which due to a question of timing was impossible to manage in English because of the added effort it took (S20). Lots of information, without being able to understand the conflicts. This should be made clearer to students. Most of us are not natives (S14). Other testimonies refer to the deficiencies found in the computer platform and to the teleconferences. The fact that teleconferences occurred in real time led to the perception that the speed at which students had to act caused anxiety and stress. In some cases this may have affected the success of the negotiations. The simulation had good parts, like interacting with other countries, but performing in the teleconferences was too fast, you don’t have time to participate as much as possible. At some moments the teleconferences were exhausting and stressful (S3). In debating and negotiating I consider that the anxiety of having to cover all the topics and act right away got the best of us. We sometimes got tangled up and were not able to reach objectives (S21). In spite of the excessive amount of information in the opinion of the participants and the dynamics of the teleconferences, those surveyed recognized the experience as fun and interesting. Some thought that they had learned formal English and that the methodology led them to reach a higher level of knowledge of English in a unique way, as well as motivating them to do so. The simulation in general seemed very interesting to me, besides fun. Without a doubt a unique way to learn English and to force you to make the effort (S1). I found the telematic simulation to be a lot of fun! The level was high but not too high. I learned formal English (S5). The telematic simulation allowed me to reach a higher level of English in a fun way (S9). It is true that there were students who admitted that their team was “lost” when they did not understand what they had to do, but they also thought that the experience was “a unique way to learn English” and of being in contact with others through situations similar to the real world. Those whose level of satisfaction was high even dared to recommend implementation as an active and innovative method for teaching English. At first we were a little lost, since we didn’t know what we had to do. But once everything started, it was a good experience (S23). I am frankly happy with the experience and would recommend its use as an English language teaching method (S1). It’s an original way to practice skills in English and social life as well (S17). One of the most recurring themes revolved around knowledge acquired about issues of current interest in society. Nonetheless, students stated that they were not accustomed to debating topics of this nature.

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I learned new things; it made me think about topics I had not paid attention to before (S21). The topics of investigation are very up-to-date and I learned a whole lot. We were all committed to understanding more about each topic. I think we grew as a team in knowledge of the world, not only in English (S25). While for some students the topics dealt with were interesting, for others they were not. …the truth is that the theme in general, negotiations, topics and all the rest were not especially interesting. I frankly don’t like politics (S16). 3 Cognitive Awareness Not only did students become aware of the importance of the language, their errors and shortcomings and of the power of the methodology, the telematic simulation also increased awareness and understanding of current issues of global interest. I have acquired a whole lot of vocabulary and awareness of the world’s problems (S12). The topics to research were very up-to-date and I learned very much. We were all committed to investigating more about each issue. I believe we grew in knowledge of the world, not only of English (S25). Among other cognitive changes, the awareness of the difficulty of interpersonal relationships in team work was shown in the testimonies of some students who were discontent. Not knowing the other members of the group, their ways of thinking, the immediacy of decision making, the inexperience in team work, among others, caused some tension at certain moments. I found team work difficult, above all because of the pressure of making decisions and not knowing one another enough. There were some arguments, but we solved our differences (S30). Team work is something that at times can be complicated, but I really enjoyed having cooperated with people with different ways of thinking (S22). However, the students did value the relationships within their groups and between groups very positively. This is one of the most significant achievements. The highest degree of satisfaction is found in the work within the group. I loved the team work because it’s what I liked the most, it’s part of my personality. I don’t like to work alone. It is much more pleasant to have human relationships and work together on a topic (S18). Team work is vital in the course. Team work is promoted in the course and totally reaches the objective, improving our capacity to relate to others, debriefing of our ideas and decision making (S19). Working on a team enriched the relationships among members of the group as well as the contents. Students reached a higher capacity to connect, greater

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understanding of other points of view, greater flexibility and greater solidarity in their daily work. “The capacity for team work… was encouraged: putting yourself in others’ place to understand other positions even though you didn’t share them” (S11). They perceived that significant progress was made working together as a team and it was more pleasant as well. Similarly, work between the groups was found to be very satisfactory. Some considered that participating in a simulation on a world scale allowed them to break with certain prejudices and connect with people of different cultures. This fact was highly valued because they believed that they had enriched their own culture. Team work is a good experience. You learn to get along with people of different ideas, culture and language (S3). Some testimonies showed how the simulated scenario and different situations reproduced reality and should be regarded as a useful projection of a real-world scenario. It is very positive and will help us in real life. The main point of interest in this subject is to communicate with other students around the world. The fact that many of the students are from English-speaking universities gives the opportunity to improve our level significantly (S4). I have shared very good moments with my team and also with people from other cultures. I think this is what surprised me most, being able to strike up a discussion with people from other parts of the planet (S31).

4 Summary and conclusion In the qualitative analysis of student responses to the request to give their opinions of their experience in the telematic simulation, three conceptual categories emerged: Metalinguistic awareness, methodological awareness and cognitive awareness. Metalinguistic awareness: Through the application of simulation and gaming methodology, most of the population perceived progress in English, specifically in the production skills, oral expression and written expression, followed by significant improvement in reading comprehension. The majority also agreed on having acquired a great amount of new vocabulary even though they did not study grammar. Although the learning objectives for the telematic simulation do not revolve around the acquisition of new, more complex language structures and grammar was not studied in a conventional way, students perceived that they consolidated their knowledge in the management of more complex language structures and grammar. Methodological awareness: Despite the fact that, in general, the students found the topics dealt with to be relevant, there were also those who thought the dynamics of the teleconferences should be improved because the speed of the teleconference system was found to be detrimental to decision making on the spot and

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caused stress and anxiety. Even though there is the perception of the need for information to be rationed out because of the lack of time to process it during the teleconferences, students highlighted that they found the telematic simulation fun and interesting. Cognitive awareness: In addition to finding the telematic simulation to be an original and interesting way to learn English, students also considered it a good way to learn about issues and events of current world interest with which they were unfamiliar. The students showed satisfaction in team work and mentioned the development of cross skills such as negotiating, decision making, flexibility, solidarity and conflict solving, among others The findings presented in this paper complement and support the results obtained in the discrete quantitative analysis of the data obtained from the 47-item survey on six different aspects, i.e., the subjects’ pre-treatment level of English, progress in English with the simulation experience, the factors influencing progress, contribution to learning, attitude and motivation, and satisfaction with the telematic simulation. To cite an example, a strong correlation was observed between telematic simulation and progress in language and generic skills. Other interesting findings were related to lower anxiety levels, increased creativity, increased autonomous learning and greater empathy with and openness to other cultures and opinions, among other findings. The combination of qualitative and discrete quantitative analyses may serve as a point of reference for other studies in similar contexts. Notwithstanding the limitations of this study, the students’ perceptions of increased metalinguistic, methodological and cognitive awareness after participating in a telematic simulation show that the sense of gain with which students finish do seem to serve the purpose of proving that the virtual learning environment is appropriate for acquiring foreign language competence.

References Andreu-Andrés, M. A., García Casas, M., & Mollar García, M. (2005). La simulación y juego en la enseñanza-aprendizaje de lengua extranjera, Cuadernos Cervantes. XI/55, 34—38. Andreu-Andrés, M. A., & García-Casas, M. (2011). Perceptions of Gaming as Experiential Learning by Engineering Students. International Journal of Engineering Education. 27(4), 795—804. Angelini, M. L. (2012). La simulación y juego en el desarrollo de las destrezas de producción en lengua inglesa. Doctoral thesis. Departamento de Lingüística Aplicada. Universitat Politècnica de València. Angelini, M.L., & García-Carbonell, A. (2014). Análisis cualitativo sobre la simulación telemática como estrategia para el aprendizaje de lenguas. Revista Iberoamericana de educación, 64(2), 1—15. Retrieved from http://www.rieoei.org/deloslectores/5994Luna.pdf Asal, V., & Blake, E. (2006). Creating Simulations for Political Science Education. Journal of Political Science Education 2.1: 1—18. ATLAS.TI THE KNOWLEDGE WORKBENCH v.5.2. (2007). Atlas.ti Scientific Software Development GmbH, Berlin. Blum, A. & Scherer, A. (2007). What Creates Engagement? An Analysis of Student Participation in ICONS Simulations. APSA Teaching and Learning Conference. Charlotte, NC. 9—11 Feb. 2007. Bytheway, J. (2013). Affecting language learners’ use of vocabulary learning strategies in massively multiplayer online role-playing games. INTED Proceedings 2013. 5032—5040. Charmaz, K. (2006). Constructing Grounded Theory. A Practical Guide through Qualitative Analysis. London: SAGE.

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De Garmo, D. (2006). ICONS and ‘Resistant Populations’: Assessing the Impact of the International Communication and Negotiation Simulations Project on Student Learning at SIUE. APSA Conference Teaching and Learning in Political Science. Ekker, K. (2000). Changes in Attitude towards Simulation-based Distributed Learning. In Wasson, Barbara et al. Project DoCTA: Design and use of Collaborative Telelearning Artefacts. Research network for ITU - Information Technology in Education. 5. Ekker, K. (2004). User Satisfaction and Attitudes Towards An Internet-based Simulation. In Sampson, D. et al (Eds.), Proceedings of the IADIS International Conference: Cognition and Exploratory Learning in Digital Age (CELDA 2004): 224—232. Ekker, K., & Sutherland, J. (2005). Telematic Simulations and Changes in Attitudes towards Simulation Topics. In Richards, G. (Ed.). Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 2034—2041). García-Carbonell, A. (1998). Efectividad de la simulación telemática en el aprendizaje del inglés técnico. (Unpublished doctoral thesis). Universitat de València, Spain. García-Carbonell, A., Rising, B., Watts, F., & Montero, B. (2001). Simulation/gaming and the acquisition of communicative competence in another language. Simulation and Gaming, 32 (4), 481—491. García-Carbonell, A. & Watts, F. (2012). Investigación empírica del aprendizaje con simulación telemática. Revista Iberoamericana de Educación, 59(3), 1—11. García-Carbonell, A., Watts, F., & Andreu-Andrés, M. A. (2012). Simulación telemática como experiencia de aprendizaje de la lengua inglesa. Revista de Docencia Universitaria, 10(3), 301—323. Gosen, J., & Washbush, J. (2004). A Review of Scholarship on Assessing Experiential Learning Effectiveness. Simulation & Gaming, 35, 270—293. Guribye, F., & Wasson, B. (1999). Evaluating Collaborative Telelearning Scenarios: A Sociocultural Perspective. In B. Collis & R. Oliver (Eds.) Proceedings of Educational Multimedia & Telecommunications. Chesapeake, VA: AACE, 1264—1265. Klabbers, J.H.G. (2001). The emerging field of simulation & gaming: Meanings of a retrospect. Simulation & Gaming, 32 (4), 471—480. Lay, C., & Smarick, K. (2006). Simulating a Senate Office: The Impact on Student Knowledge and Attitudes. Journal of Political Science Education 2.2: 131—146. Orr, C. (2003). The Effect of Individual Differences on Computer Attitudes. In Mahmood, M. A (ed.), Advanced Topics in End User Computing. Hershey, PA, US: Idea Group Publishing, 210—232. Prince, B. (2004). Measures and Relationships of Computer Usage, Computer Locus of Control, Computer Literacy, and End-User Satisfaction among College of Business Seniors. Proceedings of the 7th Annual Conference of the Southern Association for Information Systems. Savannah, GA, USA, 272—277. Rising, B. (1999). La eficacia didáctica de los juegos de simulación por ordenador en el aprendizaje del inglés como lengua extranjera. En alumnos de Derecho, Económicas e Ingeniería. (Unpublished doctoral thesis). Madrid: Universidad Pontificia Comillas. Rising, B. (2009). Business simulations as a vehicle for language acquisition.In Guillén-Nieto, V; Marimón-Llorca, C; Vargas-Sierra, C (Eds.), Intercultural Business Communication and Simulation and Gaming Methodology. Bern: Peter Lang, 317—354. Sutherland, J.L., & Ekker, K. (2011) Simulation-Games as a Learning Experience: An Analysis of Learning Style and Attitude. In Ifenthaler et al. (Eds.), Multiple Perspectives on Problem Solving and Learning in the Digital Age, Springer, 291—312. Vavrina, V. (2006). An Old-Timer’s Reflections on IP Simulations. APSA Teaching and Learning Conference. Wasson, B., & Morch, A. (2000). Identifying collaboration patterns in collaborative telelearning scenarios. Educational Technology & Society 3(3). Watts, F., García-Carbonell, A. & Rising, B. (2011). Student perceptions of collaborative work in telematic simulation, Journal of Simulation/Gaming for Learning and Development, (1)1—12. Wedig, T. (2010). Getting the Most from Classroom Simulations: Strategies for Maximizing Learning Outcomes. PS: Political Science & Politics 43(3) 547—555. Woodhouse, T. (2011). Thai University Students’ Perceptions of Simulation for Language Education. Paper presented at ThaiSim 2011, Ayutthaya, Thailand.

Authors/Contact M. Laura Angelini Universidad Católica de Valencia San Vicente Mártir, Spain [email protected] Amparo García-Carbonell, Frances Watts Universitat Politècnica de València, Spain [email protected]

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The Impact of Business Simulations as a Teaching Method on Entrepreneurial Competencies and Motivation — A Review of 10 Years of Evaluation Research in Entrepreneurship Education Eberhard Auchter; Willy Christian Kriz

Abstract Since nearly ten years we have been carrying out 6 comprehensive studies in the area of entrepreneurship education with business games that simulate start- up business processes. One part of the studies is to research the learning effects of university students in Germany, enrolled in regular courses involving start–up simulations. In these simulation courses the entire process of starting a new venture is simulated. Another important part of our studies is the evaluation of entrepreneurship education in the nationwide German competition “EXIST–priME– Cup”. Both activities (regular courses and voluntary competition cup) share the common goals of fostering entrepreneurial competencies and influencing the intention of participants to start up their own company. Comparable business simulations are used and research methodologies are applied in both programs. A logic model — the theory based evaluation approach- provides a framework for the interpretation of what takes place during the entrepreneurship business simulations. All studies show an overall increase of knowledge in business administration skills required in start–up context .But apart from other results, significant differences due to gender aspects have been identified. The differences refer to entrepreneurial attitudes and motivation. This aspect is the focus of 4 further studies to examine these gender differences and to identify responsible factors and measures to diminish this imbalance by an appropriate simulation seminar setting. Keywords start–up simulation; entrepreneurship education; evaluation; entrepreneurial competencies and motivation; gender

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1 Introduction There is still a great demand in the German speaking area for teaching and training entrepreneurship in universities and also in the field of start–up consultancy. To get a new company started is a complex task and requires from its founders a wide range of competencies and knowledge (Kriz & Auchter, 2006). The computer supported business simulation game “TOPSIM-Startup” represents the complexity and the relevant variables in different start–up situations, and covers all stages of a start–up business from collecting information, checking the business idea to transforming the business idea to a successful company in a competitive situation (Auchter, 2003; Auchter & Keding, 2004). In 2004 we have begun to carry out a range studies in the area of entrepreneurship education with business simulations that simulate start–up business processes, further called “start–up business simulations” (e.g. Kriz, Auchter & Wittenzellner, 2008). One part of the studies is to research the learning effects of university students enrolled in regular courses involving start–up business simulations. Currently we have done research on more than 50 courses and on more than 1000 students. Another important part of our studies is the evaluation of entrepreneurship education in the nationwide German competition “exist-priMEcup”. More than 8000 students have been attending about 300 of these cup-seminars. Both activities (regular courses and voluntary competition cup) share the common goals of fostering entrepreneurial competencies and influencing the intention of participants to start up their own company. Apart from other results, in all studies significant differences due to gender aspects have been identified. Two new studies examine the reasons for these gender differences and on the basis of these insights new approaches of gender related seminar designs try to diminish these gender differences. Our latest study is dedicated to examine the long-term effects of the “EXIST-priME-Cup”. Therefore 2012-2013 we started study in the form of a follow-up survey to assess long-term effects of the program in terms of entrepreneurial competencies and behavior. In our studies a startup simulation came into use. “TOPSIM-Startup!” is a strategic entrepreneurship simulation which offers a wide variety of different businesses (TATA interactive systems, 2007). A strong emphasis is put on a realistic simulation of the start–up phases within the first 2 years of a new venture: (1) Initial Phase: The entire process of starting a new venture is simulated: starting from the business idea, covering the writing of the business plan and leading to the actual incorporation of the company. (2) Competition Phase: After the incorporation, the business concept has to be put to work in a very competitive environment. Up to five teams will be competing against each other for up to eight quarters (2 years). Some simulations used in nationwide German competition EXIST–priME–Cup, are not identical with the scenarios described above, but the same business simulation methodology is used with a very similar structure and decision settings and is therefore absolute comparable with “TOPSIM–Startup”.

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2 The Evaluation Approach Our approach in evaluating the effectiveness of the simulation games used in the university courses was based on the logic model outlined by Kriz and Hense (2006). This model, as described in Figure 1, provides a framework for the interpretation of what takes place during a start–up simulation (game or competition). The logic model consists of a number of variables that can be classified under three headings: prerequisites (inputs); processes (actions); and effects (outputs or outcomes). The logic model helps to identify those elements responsible for the learning processes that emanate from start–up business simulations. All the variables in the logic model were derived from previous research, including: contemporary research on simulations (Hindle, 2002; Kriz and Brandstätter, 2003); approaches to situated learning or ‘problem oriented learning’ (Brown et al., 1989; Gruber et al., 1995); and more general models concerning the quality of teaching and the learning environment. Further, all dimensions (factors) in the logic model were measured using questionnaires, tests, and interviews involving both participants (students) and facilitators. INPUT

Socio-demographical data: age, gender, course and stage of studies; Startup disposition: intention for own start up, entrepreneurs in the family; Previous experience/attitude Skills: knowledge of business and administration, preparation of business plans, social competence Entrepreneurial competence: innovatory tendency, attitude to risk, proactive orientation Personality disposition: achievement motivation, willingness to prevail, desire to be independent, emotional stability, propensity to lead etc.

Figure 1

PROCESSES

Individual Learning: over- and under-challenged, motivation level, role-taking and causal attribution Interaction in the simulation: learning time, number of periods in simulation, type of simulation (version, complexity); type of seminar (obligatory course or voluntary cup event) Social Learning: student-student-Interaction (quality & intensity of teamwork, leadership), student-trainer-interaction (intensity & quality of support / facilitation / debriefing)

Logic Model of Entrepreneurship Education with Startup Simulations

OUTCOMES

Learning: professional skills: knowledge of business and economics, preparation of business plans, preparation of start up; Social & Personal competence: team skills, recognition of one’s own strengths & weaknesses Motivational: intention to try to become a start up entrepreneur Simulation success: acceptance of “Startup” simulation, satisfaction

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3 Methodology and Data To date we have completed three studies into the use of a start–up simulation game as a mandatory component of a university course and three studies of the voluntary German national competition called the ‘EXIST-priME-Cup’. We developed three questionnaires to collect data concerning the variables described in Figure 1 with respect to the three studies into the use of the start–up business simulation game ‘TOPSIM-Startup’ in various university courses. Questionnaire 1 was administered before the business game (simulation) commenced and served to measure the input variables. Questionnaire 2 was administered during the business game and served to measure the process variables. Questionnaire 3 was administered after the business game and served to measure the output variables, and to collect more data about the process variables. Where appropriate, the participants were asked to rate the questionnaire items on the basis of a 5-point Likert-type scale. The data for Study 1 was collected in 2005 and 2006. A total of 606 participants from five technical universities took part in the investigation of 31 start–up simulations. Study 2 essentially replicated Study 1 with a total of 202 students who participated in 11 further training courses in 2006 at the same universities as in Study 1. In Study 2, however, the improvement in the students’ business knowledge was assessed using a multiple-choice test administered both pre and post the simulation, rather than relying on a rating by the student’s course instructor (as was the case in Study1). Apart from studying the use of start–up simulations in university courses we also investigated outcomes from the German entrepreneurship competition called the ‘EXIST-priME-Cup’. These cup competitions are carried out within a nationwide entrepreneurship competition whereby the best teams in the competition progress through four levels. In this study 3 the same business game simulation methodology is used in each cup level, but with increasing complexity in terms of the scenarios and simulated variables. Due to time constraints, only one questionnaire (with 35 assessment items) was used after each cup competition seminar to assess participant outcomes. This single questionnaire incorporated a representative set of items from each of the three separate questionnaires that were used to assess the start–up simulations in the various university courses (Auchter & Kriz, 2011, 2013; Kriz & Auchter, 2012). Note that, unlike the business game simulations used in the university courses, participation in the cup competition is voluntary. The average rate of return of the questionnaires was 97%. In 2007 N=815 students participated in 43 cups in the evaluation, 2008 N=1706 in 76 cups and in 2009 N=1624 in 80 cups (total N=4145 students in 199 cups). Study 4 took place in 2009. Seven term long simulation seminars based on the same start–up simulation and the same methodology as study 1 and 2 have been carried out. The participants have been business students (N=99). In order to

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trace gender effects (that we found in studies 1 to 3, see results), we designed this additional study by constituting teams with either male or female only participants. The motivation for this research design came from prior research suggesting significantly better learning outcomes for female pupils in technical subjects where the classes only included female participants (Joffe & Foxman 1988; IEA, 1998; Kessels, 2002). Study 5 was carried out 2010/11 as a further evaluation of the national competition in which we initiated two specific changes in an attempt to enhance the impact of the national competition on the development of entrepreneurial competencies and motivation in female participants. First, we used both computer and board based simulations (each with the same level of complexity). Second, we introduced an extended debriefing session into the board based simulations; with the debriefing sessions being extended even further for the women only seminars (where all the participants and instructors were female). The results we present below are based on 152 cup competition seminars comprising the following four groups: 1. Computer based simulation, mixed gender: (143 Cup competition seminars, N=919; female (f)=344; male (m)=575 2. Computer based simulation, women only:2 Cup competition seminars, N=32 women 3. Board based simulation, mixed gender:4 Cup competition seminars, N=51, f= 18; m=33 4. Board based simulation, women only:3 Cup competition seminars; N=64 women As noted earlier, due to time constraints, we could only distribute one questionnaire (35 assessment items) per cup competition seminar. It should also be noted that, in this later study, the scales used for the questionnaire items were extended from 5- to 6-points to provide greater variation in participant responses. Study 6: Previous studies neglected however an important part of our evaluation model: to examine the long-term effects of the “EXIST-priME-Cup”. Therefore 2012-2013 we started a new study in the form of a follow-up survey to assess long-term effects of the program. The aim was to invite all former participants from the 2007 to 2011 year groups to participate in an online survey. Alongside the evaluation of the effects of the “EXIST-priME-Cup” in the form of a longitudinal analysis, the other question looked at was to find out what had become of the former participants. Although N=8190 persons had participated in the program in the years 2007-2011 only N=5988 addresses of the former participants were still valid. Overall N=1217 persons took part in the online survey. This represents a response rate of 20.3% based on the former participants still potentially being reached.

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4 Results Study 1, 2 All results presented are significant on alpha probability value p r1 holds for some players. On the contrary, Lose-side knowledge can be achieved when someone buys Lose security or sells Win security, that is, when p1 < r1 holds for some players. Since the price r1 will fluctuate according to the transactions during the game process, it is expected that either side of knowledge can be aggregated in the comment system. Another important aspect is whether the knowledge is on an uncontrollable condition or a controllable parameter for the owner. For example, the latter includes knowledge on how the proposal should be modified to make it more attractive to the customer. It should be noticed that any knowledge on a controllable parameter can be framed as either Win-side or Lose-side. For instance, “if the owner does this, the probability will increase” also means “if the owner does not do this, the probability will remain low”. However, framing this type of knowledge as Lose-side does not make sense for the player having it. Suppose that the player provides this knowledge by framing it as Lose-side and buys some Lose security when p1 < r1 holds for the player. Then, the owner will utilize this knowledge and thus the probability p1 will increase. This will decrease the expected value of Lose security (= (1 – p1 ) x 100 per unit) and thus the expected wealth of the player. Hence, any rational player will not take this action. However, this knowledge can be attained as a comment framed in the opposite side when p1 > r1 holds. Therefore, it is desirable for the game to have some fluctuations of the prices. 3.4 Game Outline The outline of the game is depicted in Fig.1. At the beginning of the game, the owner of the negotiation item of interest provides basic information on the item and the information is made visible to the other players. Then, the first turn is given to the owner, where she/he can buy Win or Lose security as many units as she/he likes from the automated market maker. This action sets the initial prices for the securities, which represent the owner’s initial subjective estimates. Then, the following turns are made open to all the players including the owner. Turns are taken by first-come-first-served basis.

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were provided different information such as the profiles of the customer and competing companies. Three game sessions in the red-and-white-ball setting and a game session in the imaginary sales negotiation scenario setting were conducted on the prototype web application both with and without the comment system. It was first confirmed that the players enjoyed the game, that is, playing the prediction market game is fun for the players. Furthermore, in these preliminary experiments, no significant differences were observed in the prediction accuracy between with and without the comment system. However, as shown in Table 1, it was noticed that introducing the comment system activates transactions. Table 1

Number of transactions in each game session

Session Fig.1

Outline of the game

After the market is closed and the actual outcome is realized, the posterior wealth and the comment contribution of each player are calculated. The performances of the players can be visualized and compared by plotting them on the two dimensional plane spanned by the dual game scores. Pareto-optimal players can be identified. The winner of the game, if necessary, can be determined from them with some weighting factors between the scores. In a real-life situation, several markets will be run in parallel, and also one after another, the members of the sales division should be rewarded based on the whole performance across the multiple markets.

4 Game Experiments A prototype prediction market game was developed as a simple PHP-based web application with MySQL database. Then, preliminary laboratory experiments were conducted to see how it works. Six undergraduate students in Aoyama Gakuin University participated in the experiments. A fixed payment was given to each participant and none of this payment amount was dependent upon the participants’ game scores. They played the prediction market game on the prototype system using the following settings. Two problem settings were arranged as follows: 1) A red-and-white-ball setting, which asks whether there are more red balls than white balls in a container with 100 balls of the two colors. Win security corresponds to Yes, and Lose security to No. Before a game started, the players were secretly provided different information such as a sample of certain size drawn from the container. 2) An imaginary sales negotiation scenario in a system integration company. The players

Without comment system

With comment system

Red-and-white-ball #1

14

42

Red-and-white-ball #2

13

43

Red-and-white-ball #3

14

35

Imaginary negotiation item

14

46

13.75

41.50

Average

5 Conclusions This paper proposed a prediction market game with a comment system for enhancing knowledge sharing among the salespeople of a company. Further, a prototype of the game is developed and preliminary laboratory experiments were conducted. As the result, it was observed that the proposed comment system activates transactions in the prediction market game and hence increases the frequencies of information sharing. Currently, all the comments are treated equally and no formal countermeasure is taken to prevent the same contents from being input repeatedly. Providing comments of same meaning, possibly by altering expressions, many times to the comment system may hinder properly evaluating comments by their evaluation scores. On the other hand, knowledge pieces are inherently connected to one another, and the relationships among them can be quite valuable. However, it is difficult for the current comment system to capture these relationships. Thus, refining the comment system, for example, by introducing gIBIS structure (Noble & Rittel, 1988), may also be an important challenge.

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References Chen, K.Y., & Plott, C.R. (2002). Information Aggregation Mechanisms: Concept, Design and Implementation for a Sales Forecasting Problem, California Institute of Technology. Social Science Working Paper #1131. Chen, Y., & Pennock, D.M. (2010). Designing Markets for Prediction. AI Magazine, 31, 42—52. Hanson, R. (2003). Combinatorial Information Market Design. Information Systems Frontiers, 5, 107—119. Hanson, R. (2007). Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation. Journal of Prediction Markets, 1, 3—15. Mizuyama, H., Torigai S., & Anse M. (2014). A Prediction Market Game to Route Selection under Uncertainty, In S. A. Meijer & R. Smeds (Ed.), Frontiers in Gaming Simulation (pp. 222-229). Springer. Noble, D., & Rittel, H.W.J. (1988). Issue-Based Information Systems for Design. Proc. of the ACADIA Conference, 275—286. Plott, C.R. (2000). Markets as Information Gathering Tools. Southern Economic Journal, 67, 1—15. Wolfers, J., & Zitzewitz, E. (2004). Prediction Markets. Journal of Economic Perspectives, 18, 107—126.

Authors / Contact Hajime Mizuyama; Kazuto Yamamiya Dept. of Industrial and Systems Engineering Aoyama Gakuin University Japan [email protected]

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Predictive Analytics in Business Games and Simulations Mihail R. Motzev

Abstract Decision making in business games involves predictions at many stages of the process. Predictive analytics support and assist decision makers and help them prepare better and more cost-effective alternatives for each decision. This paper presents predictive models for business games and simulations, focusing on multilayered active neuron neural networks. It presents some of the results from research done in Europe and at Walla Walla University in College Place, Washington, USA. Keywords predictions, models, simulations, business games, predictive analytics, GMDH, self-organizing data mining, multilayered active neuron neural networks.

1 Introduction Every organization, large or small, private or public, business or nonprofit, uses predictions either explicitly or implicitly, because it must plan to meet the conditions of the future for which it has imperfect knowledge. Bernstein (1996) effectively summarizes the role of forecasting in organizations today: “You do not plan to ship goods across the ocean, or to assemble merchandise for sale, or to borrow money without first trying to determine what the future may hold in store. Ensuring that the materials you order are delivered on time, seeing to it that the items you plan to sell are produced on schedule, and getting your sales facilities in place all must be planned before that moment when the customers show up and lay their money on the counter. The successful business executive is a forecaster first; purchasing, producing, marketing, pricing, and organizing all follow”. Similarly, decision making in business games involves predictions at many stages of the process about different, unknown variables. Players receive a description of an imaginary business and an imaginary environment and make decisions – on price, advertising, production targets, etc. – about how their company should be run. These decisions are compared with a model, which determines how well they have fared and so forth.

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Models form the basis for any decision. They support and assist decision makers and help them prepare better, more cost-effective alternatives for each decision. On one hand, models make it possible to identify the structure and the functions of the system of interest. This leads to a deeper and better understanding of the problem, usually, models can be analyzed more easily, faster and economically than the original problem. On the other hand, they help to predict what the system can expect in the future and make it possible to run simulation experiments with the system, as well as to apply “what-if” analysis. A ‘model’ in this sense is a set of rules which state that if a certain decision is taken then a certain result will follow. Elgood (2005) pointed out its importance, especially for the model-based games: “Models are also core features of other types of game, but in this type – named for them – they have special prominence. Players submit their decisions to the same model time after time: its presence is ubiquitous.” This paper concentrates on predictive models for business games and simulations. It presents some of the results from international research done in Europe and most recently at Walla Walla University in College Place, Washington, USA.

2 Predictive analytics Predictive analytics encompasses a variety of techniques from statistics, machine learning and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events (Nyce, 2007). In business, predictive analytics exploits patterns found in historical and transactional data to capture relationships among many variables, allowing assessment of risk or potential gain associated with a particular set of conditions and guiding decision making among candidate alternatives. Technically, predictive analytics is an area of data mining that deals with extracting information from data and using it to predict trends and behavior patterns. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown, whether it is in the past, present or future. The core of predictive analytics relies on capturing relationships between explanatory variables and predicted variables from past occurrences, and exploiting them to predict the unknown outcome. In the past, before the advent of modern forecasting techniques and the power of the electronic computers, the manager’s judgment, based on experience and very often just intuition, was the only tool available in decision making. This situation totally changed in the second part of the last century. Today it includes a number of advanced statistical methods for regression and classification. In certain applications it is sufficient to directly predict the dependent variable without

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focusing on the underlying relationships. In other cases, the underlying relationships can be very complex and the mathematical form of the dependencies unknown. For such cases, machine learning techniques emulate human cognition and learn from training examples to predict future events. The real-life experience shows that a simple forecast method, which is well understood, will be better implemented than one with all inclusive features but that is unclear in certain facets. Historically, using predictive analytics tools—as well as understanding the results they delivered—required advanced skills. However, modern predictive analytics tools are no longer restricted to specialists. As more organizations adopt predictive analytics into decision-making processes and integrate it into their operations, they are creating a shift in the market toward business users as the primary consumers of the information. Business users want tools they can use on their own. Vendors are responding by creating software that removes the mathematical complexity, provides user-friendly graphic interfaces, and/or builds in short cuts that can, for example, recognize the kind of data available and suggest an appropriate predictive model. Predictive analytics tools have become sophisticated enough to adequately present and dissect data problems, so that any data-savvy information worker can utilize them to analyze data and retrieve meaningful, useful results. For example, modern tools like KnowledgeMiner software (Mueller et al., 2003) present findings using simple charts, graphs, and scores that indicate the likelihood and/or the level of possible outcomes (Fig. 1).

3 Predictive Techniques and Models Generally, the term predictive analytics is used to mean predictive modeling, scoring data with predictive models, and forecasting. Armstrong (2009) makes one attempt to summarize all techniques and prepare a methodology tree for forecasting. Though it contains the most important methods, there are at least a few missing links representing some of the most recent developments of intelligent techniques concerning Artificial Neural Networks and Genetic Algorithms in particular.

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Figure 1 Example of KnowledgeMiner software user-friendly output

Nearly any regression model can be used for prediction purposes. Broadly speaking, there are two classes of predictive models: parametric and non-parametric. In parametric, the modeler makes “specific assumptions with regard to one or more of the population parameters that characterize the underlying distribution(s)” (Sheskin, 2011), while non-parametric regressions require fewer assumptions than their parametric counterparts. A third class of semi-parametric models also exists, which includes features of both. The approaches and techniques to conduct predictive analytics can be generally grouped into regression techniques and machine learning techniques. It is important to note that the accuracy and usability of results will depend greatly on the level of data analysis and the quality of assumptions. Unfortunately in economy, ecology, sociology, etc., many objects are ill-defined systems that can be characterized by inadequate a priori information about the system, big number of immeasurable variables, fuzzy objects with attributive variables, noisy and/or small data samples. Regression analysis focus lies on establishing a mathematical equation as a model to represent the interactions between the different variables in consideration. Depending on the situation, there is a wide variety of models that can be applied while performing predictive analytics – multiple regression (linear or non-li-

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near), logistic and probit regression, time series models, robust regression, multivariate adaptive regression splines, and others with much narrower application. The performance of regression analysis methods in practice depends on the form of the data generating process and how it relates to the regression approach being used. Since the true form of the data-generating process is generally not known, regression analysis often depends to some extent on making assumptions about this process. Most significant problems here are related to complex objects systems identification, pattern recognition, approximation, and extrapolation. Technically, that means massive arrays of potential explanatory variables and at the same time short time-series data (i.e. overfitting), strong relationships between explanatory variables (multicollinearity), autocorrelation of the errors, unknown time lags and other problems. It should be noted that regression techniques continue to be an area of active research. In recent decades, new methods have been developed for robust regression, regression involving correlated responses such as time series and growth curves, regression in which the predictor or response variables are curves, images, graphs, or other complex data objects, regression methods accommodating various types of missing data, nonparametric regression, Bayesian methods for regression, regression in which the predictor variables are measured with error, regression with more predictor variables than observations, and causal inference with regression. Machine learning, a branch of artificial intelligence, was originally employed to develop techniques to enable computers to learn. Today, since it includes a number of advanced statistical methods for regression and classification, it finds application in a wide variety of fields including medical diagnostics, credit card fraud detection, face and speech recognition, analysis of the stock market and more. Some of the methods used commonly for predictive analytics are geospatial predictive modeling, k-nearest neighbors, support vector machines, radial basis functions, and artificial neural networks. One of the main problems is that the mathematical relationship that assigns an input to an output and imitates the behavior of a real-world system using these relationships usually has nothing to do with the real processes running in the system. Machine learning models are implicit models with no explanation component by default, and the systems details and relationships are not at all described. The analyzed system is treated as a black box, and this approach cannot be used to analyze cause-and-effect relationships. Another important problem is that the knowledge of observed input values does not uniquely specify the output. In most cases designing topology is a trial-and-error process; there are no rules concerning how to use the theoretical (a priori) knowledge in design process and other less significant issues.

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Apparently, problems do exist in both groups, and a possible solution is in the unification of these techniques. Today there are more and more intelligent techniques combining the best from regression and machine learning. One of them is presented in the next section of the paper.

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the data sample (testing set) that has not been used for estimation of coefficients (Fig. 3). GMDH is also known as polynomial neural networks and statistical learning networks, thanks to implementation of the corresponding algorithms in several commercial software products (Madala et al., 1994).

4 Group Method of Data Handling The Group Method of Data Handling (GMDH) is a heuristic, self-organizing modeling method (Ivakhnenko, 1966). In GMDH-type self-organizing algorithms, models are generated adaptively from data in the form of networks of active neurons in a repetitive generation of populations of competing models of growing complexity, corresponding cross-validation, and model selection until an optimal complex model is finalized (Fig. 2).

Figure 3 Neural network after selection of best models at the second layer

Figure 2 GMDH iterative algorithm – a multilayered active neuron neural network

Figure 4 An optimal model y* selected by a neural network with three layers

The most popular base function used in GMDH is the gradually complicated Kolmogorov-Gabor polynomial (1):

This modeling approach grows a tree-like network out of data of input and output variables (seed information) in a pair-wise combination and competitive selection (like the genetic algorithms) from a simple single individual (a neuron) to a desired final solution (the model – Fig. 4), which does not have a predefined behavior. Neither the number of neurons, the number of layers in the network, nor the actual behavior of each created neuron is predefined. In this way, the modeling process is self-organizing because the number of neurons, the number of layers, and the actual behavior of each created neuron are adjusting during the model-building process. The algorithm presented in this paper was initially developed in the 1980s, during the first steps of GMDH (Marchev et al., 1985) and machine learning techniques (For this research in 1980 the author was nominated the First Prize Award in Individual Competition at the National Scientific Session for Students in

(1)

In order to find the best solution, GMDH algorithms consider various component subsets of the base function (1) called partial models. Coefficients of these models are estimated by the least squares method. GMDH algorithms gradually increase the number of partial model components and find a model structure with optimal complexity indicated by the minimum value of an external criterion. External criterion (also known as cross-validation technique – Stone, 1977) is one of the key features of GMDH. It is always calculated from a separate part of

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Economics, Sponsored by Bulgarian Ministry of Education). It was designed as a multilayer net of active neurons (MLNAN), which works both for multi-input to single-output models’ identification (for example different type of regression models) and for building econometric models of simultaneous equations (i.e. multi-input to multi-output). The basic idea (Motzev, 1985) in this MLNAN is that first the elements on a lower level are estimated and the corresponding intermediate outputs are computed and then the parameters of the elements of the next level are estimated. At the first layer, all possible pairs of the inputs are considered as potential factors, and only some of the best (in the sense of the selection criteria – here coefficient of correlation) intermediate models are used as inputs for the next layer(s). In the succeeding layers all possible pairs of the intermediate models from the preceding layer(s) are connected as inputs to the components of the next layer(s). This means that the output of a component at a processed level is or may become an input, depending on a local threshold value (the selection criterion here is the coefficient of determination of the partial model), to several other components at the next level. Finally, when additional layers provide no further improvement, the network synthesis stops. It should be noted that self-organization does not replace a good domain theory. Inclusion of some well-known, a priori information widens the basic scheme (Fig. 5) of self-organizing modeling by knowledge extraction from data and scientific theory. However, very often self-organization provides the only way to get any knowledge from a complex system or to add some new aspects to existing theoretical fragments (Mueller et al., 2003).

Figure 5 Basic scheme of self-organizing modeling with a priori information

The procedure described above is a multilayer GMDH algorithm for multi-input to single-output models identification. In case of synthesizing complex models in the form of Simultaneous Equations (SE, i.e. multi-input to multi-output

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models) an additional part was developed as an iterative procedure (Motzev et al., 1988). Here, the equations from the previous part are used to synthesize the SE: The intermediate models are generated combining already chosen, good equations according to the combinatorial algorithm. Each of the competing hypotheses is a hypothesis about the significance of entering a given version of a single equation into the system of SE. Each generated SE is considered as a potential model for the system of interest, which competes with others “fighting for survival”. The evaluation of these competing models is done, using a complex set of criteria – MSE, coefficient of determination, MAPE, and others. If the results are unsatisfactory after solving the structural form of the system (biased values of the coefficients, low accuracy of the equations, or other), the procedure returns to the first part. The decision maker can then apply some new, a priori knowledge and/or add fresh data, or change the selection criteria etc. Then a new synthesis of the structural equations is completed and with the so-obtained new set of equations the second part begins again. It ends when satisfactory results have been achieved in the sense of the selection criteria. The final choice of the “best” model is made by the decision maker, who has one final option to apply additional, qualitative information/knowledge, but after having the guarantee that a large number of possible models have been evaluated and the final choice is based on a small number of good ones. ◆◆

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These characteristics make the proposed MLNAN very useful for addressing most of the model-building problems discussed above. For example, overfitting is eliminated by the use of external criterion (cross-validation) for validating the model. The small number of independent measurements (or short time-series) is also not an issue, because the inverted matrix size is always 2x2 (pair-wise combinations). This helps in dealing with the problem of multicollinearity as well. The autocorrelation is eliminated by adding lagged time series values as predictors. Despite the totally automated procedure the decision maker has options at the crucial points to apply additional insights, knowledge or hypotheses.

5 Applications, Comparisons, Benefits and Future Improvements The first working prototype of the MLNAN described above was used to improve an existing business game. The game “National Economy” had been used for many years at the Economic University in Sofia, Bulgaria (Motzev, et al. 1984). The original version contains a model developed with the general multiple regression analysis. The same data and set of variables were used to build a new model, using the MLNAN algorithm.

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Table 1 Model characteristics and comparisons Characteristics

Old Version

Improved Version

Model description

A one-product macro-economic model developed as a system of five SE. Contains five endogenous, one exogenous, and five lag variables.

A one-product macroeconomic model with the same structure. Contains same set of variables.

Model-building technique

Indirect OLS used to estimate unknown coefficients in equations.

Model synthesized using the GMDH procedure.

Model accuracy

Mean squared error relative to the mean (MSE%) = 14%

MSE% = 2.7%

The brief comparison shows (Table 1) that the new version has much better accuracy (more than five times smaller MSE) and thus provides a more reliable base for simulations and what-if analysis. Increasing model accuracy provides many other benefits. For example, it makes it possible to analyze more precisely the problem in consideration, which leads to a deeper and clearer understanding of the problem itself. Also, a model with higher accuracy will generate better predictions and help players making better and more cost effective decisions. Another area of application of the MLNAN was the macroeconomic modeling. A series of increasingly complex simulation models of the Bulgarian economy was developed (Motzev & Marchev, 1985, 1991) as follows: SIMUR I (1980) – One-product macroeconomic model in the form of 5 SE. Contains 5 endogenous, 5 lag and 1 exogenous variable. Average MSE% = 2.7% SIMUR II (1985) – Aggregated macroeconomic model in the form of 12 SE. Contains 12 endogenous, 5 exogenous and 26 lag variables with lag of up to 3 years. Average MSE% = 2.0% SIMUR III (1987) – Complex macro-economic model of 39 SE, with 39 endogenous, 7 exogenous and 82 lag variables (time lag up to 5 years). Average MSE% 0.9 for most of them (average R2 = 0.9339). Recently, another detailed study (Onwubolu, 2009) of the predictive performance of two time series forecasting techniques (Elman neural network and GMDH algorithms) against the autoregressive integrated moving average (ARIMA) also confirmed

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that GMDH based techniques are able to develop even complex models reliably and achieve lower overall error rates than state-of-the-art methods. Predictive analytics and in particular GMDH based techniques require both powerful hardware and fast software, designed and elaborated for this specific aim. One element in the first working prototype that needed improvement was the software, which had been designed for mainframes and mini computers (Marchev & Motzev, 1989). The original version was too large and too complex - its total volume was about 30 thousand program lines in PL/1. It was designed for an IBM 4331 computer under the VM-370 operating system. At present, this system has a multitude of abilities and parameters that are assigned in interactive mode, which in fact often hampers more than aids the unprepared user. Moreover, it ties him to an outdated operating system and an expensive computer. Developing your own computer program in this area is a big project, which takes extensive resources, time and highly qualified professionals. The numerous tools, available on the market, that help with the execution of predictive analytics range from those that need very little user sophistication to those that are designed for the expert practitioner. One possible solution was the “KnowledgeMiner” data mining software (Mueller et al., 2003). It is a self-organizing tool for modeling and predictions that implements GMDH, Analog Complexion, and Fuzzy Rule Induction techniques. “KnowledgeMiner” can be used to create linear & nonlinear, static and dynamic time series models, multi-input/single-output and multi-input/multi-output models as systems of equations even from small and noisy data samples. The model outputs are presented both analytically (as equations with estimated coefficients) and graphically, by a system graph reflecting the interdependent structure of the system. To evaluate the proposed tool, a comparison was done using a model like SIMUR II, created with similar data for the German national economy in the form of 13 SE by the developers of “KnowledgeMiner” software (Mueller et al., 2003). It wasn’t possible to use the same set of data, and the results could be used only for general comparisons; however, both models show similar levels of high reliability and accuracy. It is important to note that one software module in the original prototype (program SIMUL, designed and developed exclusively by the author of this paper) provides some functions not covered by “KnowledgeMiner”. “KnowledgeMiner” has an excellent module for complex evaluation of the synthesized model, its adequacy and reliability, but SIMUL provides more options for conducting different simulation experiments and what-if analysis. Updating this program and making it compatible with “KnowledgeMiner (yX) for Excel” software would be a useful new project in the future.

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With the new software, the proposed MLNAN was used in the model-based management game “New Product” (Motzev, 2012), designed for students taking “Production and Operations Management” at Walla Walla University. After accumulating knowledge and experience during the initial steps of this game, students work on a case scenario, which is an example of stochastic business process. As in the real-life business, there is similarity between values observed, which means that the time series data are autocorrelated and could be presented with an ARM. The ARM specifies that the output variable depends on its own previous values and is one of the prediction functions used to forecast an output of a system Y(t) based on the previous outputs Y(t-i). However, in most cases the order of the general ARM is unknown, which makes both structural and parametrical identification very difficult. Leading researchers suggest applying an iterative approach to model building for forecasting and decision making (Box and Jenkins, 2008). This makes the MLNAN an appropriate tool to develop the unknown ARM, which students can use to make better and more cost/effective decisions at the next stages of the game. The game was accepted with great interest and students reported in feedback that the game was a valuable learning tool that helped to increase their knowledge and competencies. Beginning in the Spring Quarter of 2014, the MLNAN will also be used as a tool for predictive analysis and model building in another class, “Forecasting Methods”, and as an illustration of artificial neural networks and GMDH-type self-organizing algorithms in a “Management Information Systems” class. The benefits of utilizing MLNAN in business simulations are clear. This approach provides opportunities to shorten time and reduce cost and effort in model building and at the same time to develop reliable complex models with low overall error rates. Increasing model accuracy helps researchers to more precisely analyze problems, which leads to deeper and better understanding. Also, models with increased accuracy generate better predictions and support managers in making better decisions that more closely relate to real-life business problems. If a business game (especially a model-based game) does not accurately represent a real system, then the knowledge that the students receive about real-life business is questionable. For example, knowing precisely how much increasing the cost of advertising, or reducing the total cost of production increases the marginal profit does matter. However, if the game model is not accurate and the predictions made by the players are not close enough to a real-life business case, then learning will be minimal. Tools like the MLNAN make it possible not only to develop faster model-based business games, but also to improve the decisions that students make during the game.

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6 Conclusion The proposed MLNAN provides opportunities to shorten time and reduce cost and effort in business simulations and model-based business games. The results so far show that it is possible to develop even complex models reliably and to achieve lower overall error rates than by using state-of-the-art methods. Of course, there are some limitations of predictive models based on data fitting. For example, history cannot always predict the future; using relations derived from historical data to predict the future implicitly assumes certain steady-state conditions or constants in the complex system. This is almost always inaccurate when the system involves people. Another issue is the “unknown unknowns”. In all data collection, the researcher first defines the set of variables for which data is collected. However, no matter how extensive the researcher considers his selection of the variables, there is always the possibility of new variables that have not been considered or even defined, yet that are critical to the outcome. It is imperative to conclude, however, that the model outputs must always be evaluated by the researcher to figure out whether new and useful knowledge of the domain has been discovered. Predictive analytics create and provide data, but the real-life business needs information, i.e. data in the business context. The extracted information is valuable to a business only when it leads to actions that create value or market behavior that gives a competitive advantage. The researcher has to determine the ultimate importance of the information generated by algorithms like the MLNAN described in this paper.

References Armstrong, S. (2009). Methodology Tree for Forecasting, http://www.forecastingprinciples.com/index.php?option=com_ content&task=view&id=16&Itemid=16. Bernstein, P. L. (1996). Against the Gods: The Remarkable Story of Risk. New York: John Wiley & Sons. Box, G., & Jenkins, G. (2008). Time Series Analysis (4th ed.). New York: John Wiley & Sons. Elgood, C. (2005). Using Management Games. Burlington: Ashgate Publishing. Ivakhnenko, A. G. (1966). Group Method of Data Handling - A Rival of the Method of Stochastic Approximation, Soviet Automatic Control, No.13, 1966, 43—71. Madala, H., & A.G. Ivakhnenko (1994). Inductive Learning Algorithms for Complex Systems Modeling. Boca Raton: CRC Press. Marchev A., & Motzev, M. (1985). Computer Macroeconomic Models for Simulation Experiments. Systems Analysis and Simulation, 28, 145—150. Marchev A., Motzev M., & Muller, J.-A. (1985). Applications of The Self-Organization Procedures for Business System Models Building. Automatics, 1, 37—44. Marchev, A., & Motzev, M. (1989). Principles of Multi-Stage Selection in Software Development in Decision Support Systems. Methodology and Software for Interactive Decision Support (Lecture Notes in Economics and Mathematical Systems, 337 IIASA, 181—189. Motzev M., & Marchev, A. (1984). Applications of Management Simulation Games for Student Training in Business Education, X Internationales Seminar Uber Rechnergestutzte Planspiele, Berlin. Motzev M. A. (1985). New Approach for Simulation Models Building, XVI IFAC/ISSAGA Workshop, Alma-Ata. Motzev, M., & Marchev, A. (1988). Multi-Stage Selection Algorithms in Simulation, Proceedings of XII IMACS World Congress, Paris, France, 4, 533—535. Motzev, M. & Marchev, A. (1991). Macroeconomic Models for Simulation of the Bulgarian Economy. Systems Analysis, Models and Simulation, 8, 145—150.

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Motzev, M. (2012). New Product -An Integrated Simulation Game in Business Education, Bonds & Bridges, Proceedings of the World Conference of the ISAGA, 63—75. Mueller J.-A., & Lemke, F. (2003). Self-Organizing Data Mining: An Intelligent Approach To Extract Knowledge From Data. Trafford Publishing. Nyce, C. (2007). Predictive Analytics White Paper, American Institute for Chartered Property Casualty Underwriters/ Insurance Institute of America p.1. Onwubolu, G. (ed.). Hybrid Self-Organizing Modeling Systems. Berlin: Springer. Sheskin, David J. Handbook of Parametric and Nonparametric Statistical Procedures, Boca Raton: CRC Press. Stone, M. (1977). Asymptotics for and against cross-validation, Biometrika 64 (1), 29—35.

Author/Contact Mihail R. Motzev Walla Walla University School of Business, USA [email protected]

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Process Model for the Development of Simulation Games for Training Purposes Jan-Jasper Mühle, Johannes Schweizer, Markus Klevers

Abstract The authors examine the development of simulation games for training purposes. In the context of an increasing global competition and due to the need of technical innovations, the enormous importance of excellent trained employees has become evident. Taking different perception types into account, the authors show that simulation games are the best answer to train employees and to stimulate enthusiasm for these innovations. In contrast to classic training methods (e.g. teacher-centered lectures), the design of educational simulation games may be very complex and time consuming. Thus, the authors design a process model for the development of simulation games for training purposes, which is presented in this paper. It consists of a network-like structure with four phases (Initialization, Design, Realization, Implementation) and 17 modules that divide this complex task into manageable sub-tasks. Doing this, it supports directing experienced and unexperienced simulation game designers comprehensively and purposefully through the development process. Keywords simulation game development, simulation game for training purposes, game design

1 Introduction As the progressive liberalization of world trade continues, an increasing competitive pressure to introduce cutting-edge concepts and technical innovations is gaining importance. A particularly crucial role in the successful introduction of these innovations plays the need for excellent training of staff. Above all, it is essential to motivate the staff and to win acceptance when implementing new ideas. Thus, it is necessary that the training content is not only taught but furthermore internalized and lived by the employees.

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Indeed, the sense organs in humans may vary individually (Vester, 1998, p.51) and can be differentiated according to three types of perception: The auditory perception type is a good listener and uses his hearing to absorb information (Quilling & Niccolini, 2009, p.142). The visual perception type observes processes, graphics and written documents in order to record information and to learn. Last but not least, the haptic-motoric perception type is practically gifted and learns through touching and feeling. To educate himself he becomes active and prefers to try out something instead of reading (Fleuchaus, 2012, p.9-10). In order to address all types of perception simultaneously, simulation games are an excellent training method (Muehle, 2013, p.17). They can be used in many areas and contain simulations of real systems, so that participants take on roles and make decisions for which they are responsible (Kriz  &  Nöbauer,  2008,  p.105). In addition, simulation games offer the participants the opportunity to acquire “tacit knowledge” (Nonaka, Takeuchi, Ingham & Koenig, 1997, p.4), which is based on their own subjective insights and experiences (North, 2010, p.47). Compared to traditional methods, such as teacher-centered lectures, stand-alone courses and interactive selfteaching, serious simulation games give the participants a good understanding of complex relationships. A further advantage of simulation games is that participants can contribute their own ideas to experience success stories, so as to inspire and to emotionalize (Boppert & Klenk,  2012, p.209-269). In general, the development of a comprehensive simulation game for the training of employees that lasts several hours or even multiple days may be very complex and time-consuming – especially compared to PowerPoint presentations that often can relatively quickly and easily be designed. Especially with regard to medium-sized businesses that lack the experience to produce simulation games for training purposes under their own autonomy in-house, their development may be seen with an aversion due to huge costs and a massive preparation effort whereas their increased success in training may not even be assessed. In order to increase the popularity of simulation games and to reduce their development costs, the need for engineering directives and guidelines that address a wide circle of users becomes evident. As a result, a so-called process model that provides an efficient approach to develop tailor-made training simulation games is presented in this paper. It aims at supporting beginners and experienced developers by offering a comprehensive, target-oriented working method in the development itself, as well as in its project management.

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2 State-of-the Art and impetus to present a process model for the development of simulation games for training purposes On the internet and in literature a large number of different process models for a variety of applications can be found. In the discipline of product development, these include the Munich process Model, the PDCA cycle (Lindemann, 2007) and the VDI Guideline 2221 (VDI2221). Similarly, in the area of developing business and simulation games, some process models already exist: The development tool of Jones (1995, p.65) provides a questionnaire and is in particular suited for the engineering of small simulation games (Capaul & Ulrich, 2010, p.119). Another method for the development of simulation games is the iterative process model according to Grabka (2006, p.28), which is very open and limited. The authors Ellington, Addinall and Percival (1982, p.21 34) outline a general approach which can also be used for designing training simulations. At the level of macro logic this model is made up of the four phases (I.) establishing the design criteria, (II.) developing the basic idea, (III.) developing a viable package to meet the design criteria and the (IV.) release of the game. Within the phases an approach similar to a flow chart is given by confronting the user with a catalogue of questions. Detailed recommendations for action and comprehensive methodological components to develop simulation games for the purpose of employee training, however, are not provided. The sequence to design policy games for strategic management by Duke and Geurts (2004, p.269-305) can be seen as a standard work when designing simulation games. It is made up of 21 steps and consists of five phases (I.) to set the stage, (II.) to clarify the problem, (III.) to design the exercise, (IV.) and to develop and (V.) implement the exercise. It spotlights on the design of simulation games for strategic management. In this work, however, the focus will be specifically directed to the development of simulation games for staff training. In contrast to strategic management where simulation games may be used to draw a clear link of a problem, at staff training the content that needs to be instructed is known in the context of training cases. Therefore, an extension and specialization of existing process models is presented in this paper that meets the specific requirements that are relevant in the development of a training simulation game. Thus, it accounts that in the development of training materials different departments and several designers are involved by being comparatively more oriented to secluded work packages that allow simultaneous engineering. In terms of incremental improvement and changing requirements that may arise when a training simulation game is developed parallel with the development of innovative ideas to be trained (e.g. such as the introduction of a new inventory strategy for a car manufacturer), the presented model not only allows iterations like the 21 steps by Duke and Geurts indirectly, but explicitly requires them. Compared to existing models, it furthermore places

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special emphasis on a modular structure so that individual modules can be optimized or replaced by new or tailored modules and therefore is itself subject to a continuous improvement cycle. Additionally, in the context of strict project management the presented model uses a Gantt chart to meet deadlines. According to lean management a pull-principle is introduced so that the designer only uses the modules needed, which means that the process model can also be used partially. Subsequently, the process model for the development of simulation games for training purposes is presented in more detail. As part of a comprehensive employee training, it has been successfully applied in the context of designing an all-day simulation game for the training of a specialized process concept for a car manufacturer. The use of its individual modules is documented by Muehle (2013). Since the model is subject to a process of continuous improvement, however, feedback from further experienced users is very important.

3 The Process model and its modules In this chapter the process model to develop simulation games for training purposes is presented. It consists of a network-like structure with the four phases Initialization, Design, Realization and Implementation. Thereby, the complex task to develop a simulation game is divided into manageable subtasks. The process model itself is presented in the following figure. When using the model, the usual processing sequence starts with the Implementation phase. The Design and Realization phases then follow clockwise. The completion of the development is marked by the Introduction phase. However, the results of each phase are gradually improved by an iterative procedure, so that a deviation from the standard procedure may often be useful. As shown in the figure, the phases jointly focus on the required Product specifications in the center of the module. Furthermore, each phase additionally targets important milestones in the header. In addition to the illustration, a fundamental part of the process model is its 17 specific modules that individually offer a questionnaire to guide the user through the development task. Moreover, various methods are recommended to support the processing.

Figure 1 Process Model

4 Initialization phase The Initalization phase is composed of a total of five modules. The first step is represented by the modules to resolve the Training goals, the Target group and Requirements, premises & conditions. These modules are in mutual interdependence, but can be processed independently and simultaneously as long as an intensive communication between the users is guaranteed. On this basis, the second step is the intensive clarification of all conditions for the Verification of the simulation game, i.e. ensuring that a simulation game is appropriate for the training content. The decision to develop a game leads to establishing necessary Product Specifications. 4.1 Training goal module Training goal Target

Suggested analytical methods

This module aims at determining the training goal in terms of relevant content, issues and topics u u u

Recommended Presentation of results

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Invite experts and own staff to a workshop to develop training objectives Survey (interview or questionnaire) to determine training content Analysis of the topics to be trained An overview of the course content and objectives should be mapped in a training content matrix as a function of training session depth Questions to be answered

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Which divisions are affected by the training and which training goals can be identified?

What areas and persons need to be entrusted with the organization and implementation of the simulation game?

Which specific training objectives need to be taught?

What technological tools (hardware and software) are available to develop the simulation game?

Which content results from the training goals and which training depths needs to be achieved?

What materials are already available to realize the simulation game?

Does the individual training content and depths depend on different training groups? (cf. Target group)

Where is the game developed?

Does the training content depend on Requirements, premises & conditions?

Where is the simulation game implemented? Does this result in requirements for transport, logistics and material? Which local laws and regulations need to be taken into account?

4.2 Target group module Target group Target

This module aims at identifying the participants to be trained

Suggested analytical methods

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Since communication among the developers plays a major role, this module focuses on the contact persons and their knowledge. 4.4 Verification of the simulation game

Recommended Presentation of results

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Invite customers and experts within the company to a workshop to develop training objectives The classification of target groups into training groups should be done in a chart Questions to be answered

Verification of the simulation game Target

Suggested analytical methods

This module examines if the use of a simulation game is an appropriate training method to teach the identified content u

Which specific target groups will participate? u

The target groups consist of which levels of hierarchy? In which activities the target groups need to be trained? How many employees must be trained for each target group?

Recommended Presentation of results

An analysis of the training content as a basis for deciding whether the simulation game is suitable or not A review of existing simulation games as basis for the decision if a new simulation game needs to be developed

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Resolution for the development

Questions to be answered

Is it possible to combine training groups in terms of training content? Is it possible to combine training groups in respect to training depth?

What training methods are suitable for teaching the course content?

Which employees can be assigned to which training groups?

What training methods are suitable for the training of the identified target groups?

What is the time availability of the participants?

What are the appropriate training methods? Is the use of a simulation game the most effective training methodology to achieve the objectives?

4.3 Requirements, premises & conditions Requirements, premises & conditions Target

Suggested analytical methods

This module aims at engineering the framework for the simulation game development u

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Recommended Presentation of results

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Invite customers and experts within the company to a workshop to gather requirements, premises and conditions Survey of stakeholders In an overview

Which simulation games exist in related areas? Is it possible to use an existing simulation game? Is it possible to adapt and customize an existing simulation game? Is it necessary to develop a new game?

This module examines if existing simulation games can be adapted or are already is available, which would be easier than developing a completely new simulation game.

Questions to be answered Which people from which areas take part in the game development? Who are the contact persons? To what extent can employees bring knowledge into the development of the simulation game? Which time frame is intended for the game development? What deadlines must be met? Which time frame is intended for the simulation execution? What budget is at disposal? What is the budget for the implementation of the simulation game?

5 Design Phase The second phase of the process model is the Design phase with its six modules. A key role is played by the module Roadmap and organizational framework to ensure that work packages are completed in time for a successful development task. In regard to the remaining five modules, the Selection of content, the Selection of setting and the Selection of structure should then be executed. As

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before, these modules are in mutual interdependence and can only be processed simultaneously if an intensive communication is ensured among the processors. The modules are loosely derived from Ellington, Addinall and Percival (Ellington et al., 1982, p.21p.34) and form the basis for generating Solution alternatives and ideas. The completion of this phase is the Evaluation of solution alternatives in which the most suitable ideas are identified for the Realization Phase.

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5.3 Selection of setting module Selection of setting Target

Suggested analytical methods

In this module the setting of the simulation game is defined in the context of the training content and the requirements. The conclusion of this module is marked by the selection of the simulation games setting u

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5.1 Roadmap and organizational framework module

Recommended Presentation of results

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Analysis of the training content taking the results from the initialization phase into account Consideration of the module selection of content Morphological box Decision on the establishment of the simulation

Roadmap and organizational framework Target

Suggested analytical methods

In this module a roadmap is planned in order to determine the chronological and logical order of executing the modules, as well as determining deadlines, delivery dates and giving a cost estimate (Litke & Kunow, 2006, p.47) u

Analysis of the results from the initialization phase

Questions to be answered What is the desired main action of the simulation game? What storylines should it pursue? What relation to reality should it have? What is the position of the participants?

Recommended Presentation of results

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Gantt chart

What is the desired level of abstraction? What are the requirements regarding the number of participants?

Questions to be answered Which modules are prerequisites of other modules? What modules depend on each other?

What is the participants starting position? In which extent should the participants influence the gameplay? What is the desired duration of the game?

Which modules follow each other?

In which languages should it be offered?

Which employees are responsible for which tasks? Which deadlines need to be met?

What is the participants’ previous knowledge? What kind of processes should be mapped?

What processing time is intended for each module and when is the start of processing?

5.2 Selection of content

5.4 Selection of structure Selection of content

Target

Suggested analytical methods

The specific training content of the simulation game is determined in this module u

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Recommended Presentation of results

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An analysis of the training content as a basis for deciding whether the simulation game is suitable or not A review of existing simulation games as basis for the decision if a new simulation game needs to be developed A training content matrix Clear display in a separate list Questions to be answered

Selection of structure Target

Suggested analytical methods

Recommended Presentation of results

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Analysis of the results from the initialization phase and the modules content and setting Decision on the game media to be used

What is the games desired framework? What roles should the participants take?

Which training content is characterized by decision-making or problem-oriented processes that can be displayed in a simulation game?

What are the ground rules?

Which training content aims at developing strategies and are to be trained by exemplary learning or in the simulation game?

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Questions to be answered

What specific training content is suitable for a simulation game?

Which training content consists of actions such as Analysis or evaluations that can be transferred to a simulation game?

This module aims at selecting the content of the simulation game to set the game media

What degree of complexity is desired? Should an adaption of complexity be considered? Which degree of interactivity is desired?

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An overview of various simulation game media is given below, whereas a combination of different media may be useful: Board game Card game PC aided simulation Outdoor game Game on a playing field Table game Haptic game Group game Behaviour game Role-play game PC-based competitive simulation Internet- or intranet game (Blötz, 2001, p.11; Ellington et al., 1982, p.24-27)

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5.6 Evaluation of solution alternatives module Evaluation of solution alternatives

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Target

This module aims at reducing the number of solution ideas

Suggested analytical methods

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Preselection Cost-benefit analysis in order to obtain a ranking of suitable solutions (Lindemann, 2007, p.283)

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Ranking for a transparent documentation

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Recommended Presentation of results

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Questions to be answered What criteria can be used for a preselection? Which solution ideas can be excluded a priori since they do not meet KO criteria? Which criteria should be considered in a cost-benefit analysis?

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5.5 Solution alternatives and ideas module Solution alternatives and ideas Target

Suggested analytical methods

Recommended Presentation of results Target

In this module, a variety of solutions and ideas for the implementation of the simulation game is derived. By means of creativity techniques the creativity of the developer is stimulated.

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Analysis of the results of previous modules Research in a simulation database (e.g. www.bibb.de/de/29264.htm or www. bpb.de)

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Creativity techniques for generating solutions and ideas

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Morphological box

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Questions to be answered Which partial solutions can be derived from existing simulation games?

6 Realization phase The third phase of the process model is called Realization phase and is comprised of the modules Making prototypes, Field trials and Overall configuration. Like before, the modules recommend simultaneous engineering to gradually reach optimal results. Once the functionality of the developed simulation game is proven by a final field trial, the Implementation phase follows. 6.1 Making prototypes module Making prototypes Target

This module aims at designing prototypes to verify solution alternatives

Suggested analytical methods

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Recommended Presentation of results

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Workshop and creativity techniques to implement the prototype Construction of prototypes Documentation of the procedure Questions to be answered

Which solution ideas can be generated with respect to the simulation structure and its setting? Which solution ideas can be developed to teach the content?

What is the prototypes purpose? Should it examine the playability or is constructive feasibility analyzed?

Which solution ideas can be derived with regard to the specifications?

What level of detail should it have? How can it be implemented? Can existing games, toys or objects be used?

Creativity techniques such as brainstorming, the Osborn checklist, 6-3-5 brainwriting or CPS (Lindemann, 2007, p.143) should be used to effectively obtain innovative ideas, and are particularly suitable for collective problem solving workshops. However, it has to be noted that the composition of participants has an impact on which method to use (Backerra, Malorny & Schwarz, 2007, p.97).

Which requirements regarding visual appearance and design are applicable? Who is in charge of designing and making the prototype?

This module supports the design of prototypes and considers that it is important for the prototype to meet its specific function and to fit in the context of the simulation game and other materials.

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6.2 Field trials module Field trials Target Suggested analytical methods

This module aims at gradually perfecting the prototypes in order to compile the overall configuration of the simulation game u u

Recommended Presentation of results

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Iterative procedure Final field trial to validate the simulation Verified and completed simulation game Description of the game Guidance book draft Work instruction draft

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7 Implementation phase The introduction phase is comprised of the four modules Rehearsal, Implementation, Acceptance and Lessons learned. This phase marks the developments closure and the game’s acceptance, as well as to ensure that the experiences gained during the project are retained. 7.1 Rehearsal module Rehearsal Target

Questions to be answered How does the protoytpe perform the inspected matters?

Suggested analytical methods

Recommended Presentation of results

Where and how can improvements be made?

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What are the strengths and weaknesses of the prototype? What has to be improved?

This module aims at putting the simulation game to a final test under real conditions with a trial group before introducing it to the “public”

u u u

Can the considered prototype be released?

Rehearsal under realistic conditions The developers take on the role of the observer to follow the trial group Documentation of observations Feedback questionnaire Checklist of modification to be made Questions to be answered

It has to be noted that the simulation game should be playable without the developers’ participation. Therefore, a parallel development of the game and work instructions is recommended.

When and where should the rehearsal be carried out? Who should be invited? Who are the people involved? (Trainers? Observers?) What should be the content of the feedback questionnaire?

6.3 Overall configuration module

What insights and which fine-tuning have resulted from the rehearsal? Where can the rehearsal be arranged?

Overall configuration Target

Suggested analytical methods

Recommended Presentation of results

This module aims at defining the games overall configuration based on the content and setting to complete the development by composing the partial solutions and the favorable prototypes. u

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Workshop and use of creativity techniques

Completed simulation game Detailed guidance book Detailed work instructions Questions to be answered

How can the chosen design and structure be implemented? Which items need to be used for implementing and carrying out the game? Which items are already available? Which items can be purchased? Which items need to be developed? How many trainers are needed? What are the game’s requirements

7.2 Implementation module The introduction of the simulation game marks the completion of the development and should only be done once a high reliability can be ensured, thus if the product has been tested and all known fatal errors have been eliminated. For a successful introduction of the game a high-quality presentation of the simulation itself as well as optimal conditions with respect to scheduling, an experienced coach and an open-minded group should be ensured. 7.3 Acceptance module The acceptance of the simulation game is an important step as identified deficiencies are documented, renewed and as the product is passed to the client and approved (Wieczorrek & Mertens, 2009, p.98). At this point, no procedure is described but rather referred to the legal framework and technical literature.

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What requirements are placed on the use of the simulation?

7.4 Lessons learned module

Which target state should be reached? Lessons learned Target

Suggested analytical methods

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Recommended Presentation of results

What rough time planning should the game meet?

This module can be seen as a complement to the process model to gain experience and to carve out positive and negative insights for future developments (Jenny, 2001, p.497; Wieczorrek & Mertens, 2009, p.86)

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Evaluation of the documentation Feedback discussion with all stakeholders Documentation, if necessary by use of special software

Questions to be answered What points worked really well during the game development? In which areas did problems occur? At what points improvements could have been made? What could have been done better? What was the time required for the development of the game? What was the schedule? What was the budget provided? What costs incurred in which areas? Which employees from which areas with qhich qualifications where involved in the development?

8 Conclusion In this paper a process model to develop simulation games specifically for training purposes has been presented. Its phases and modules aim at offering the efficient possibility to develop tailor-made simulation game. Furthermore, its graphical illustration supports the designer by showing the current development status. The approach divided in phases in combination with the use of milestones and a Gantt chart has proven itself as goal-oriented. By adding additional modules, the process model can furthermore be customized. Another major step in the development of the process model was its practical application. As part of the training concept for a newly build automotive plant, it has been used to design a simulation game for the employee training of synchronized automotive logistics. The developed simulation game was successful. Furthermore, an extensive list of requirements defined at the beginning of research could be used to validate the process model as well.

What are the games benefits? What other lessons can be learned?

References 7.5 Product specification module The Product specifications are a compilation of all the clients´ requirements in terms of scope of deliveries and services. The specifications have to be described from the user’s perspective including all marginal conditions (VDI/ VDE 3964, p.3). Product specification Target Recommended Presentation of results

This module shows how to precise the Product specifications for the customer u u

Task organization after (VDI/VDE 3694) Approach after (VDI 2519) Questions to be answered

What are the aims of the defined product of the simulation game? What range of functions should the game have? In which areas should the game be used? What are its requirements in regard to operation, development, support and maintenance? What functional and non-functional requirements should the game fulfill? What are the requirements for the documentation of the game development? What are the requirements to the quality of the simulation?

Backerra, H., Malorny, C., & Schwarz, W. (2007). Kreativitätstechniken. München: Hanser Fachbuchverlag Blötz, U. (2001). Planspieltraining in der Aufstiegsfortbildung. In: Berufsbildung in Wissenschaft und Praxis, Jg. 29, 1/2000 Boppert, J., & Klenk, E. (2012). Wissensvermittlung und Kompetenzwettbewerb in Lean-Logistics-Projekten. In Göpfert, I., Brown, D. & Schulz, M. (Hrsg), Automobillogistik. Heidelberg: Gabler Capaul, R., & Ulrich, M. (2010). Planspiele - Simulationsspiele für Unterricht und Training; mit Kurztheorie: Simulations- und Planungsspielmethodik. Altstätten: Tobler Duke, R. & Geurts, J. (2004). Policy games for strategic management – pathways into the unknown. Amsterdam: Dutch Univ. Press Ellington, H., Addinall, E., & Percival, F. (1982). A handbook of game design. London: Nichols Pub Co. Fleuchaus, A. (2012). Der Umgang mit unterschiedlichen Lerntypen an einer Wirtschaftsschule: Empfehlungen für den Mathematikunterricht. Hamburg: Bachelor Master Publishing Grabka, T. (2006). Referenzmodelle für Planspielplattformen – Ein fachkonzeptioneller Ansatz zur Senkung der Konstruk tions- und Nutzungskosten computergestützter Planspiele. Berlin: Logos-Verlag Jenny, B. (2001). Projektmanagement in der Wirtschaftsinformatik. Zürich: vdf, Hochschulverlag an der ETH Zürich Jones, K. (1995): Simulations: A Handbook for Teachers And Trainers. London: Kogan Page Kriz, W., & Nöbauer, B. (2008). Teamkompetenz: Konzepte, Trainingsmethoden, Praxis. Mit Einer Materialsammlung zu Teamübungen, Planspielen und Reflexionstechniken. Göttingen: Vandenhoeck & Ruprecht. Lindemann, U. (2007). Methodische Entwicklung technischer Produkte – Methoden flexibel und situationsgerecht anwenden. Berlin: Springer Litke, H., & Kunow, I. (2006). Projektmanagement. Freiburg: Haufe Lexware Muehle, J. (2013). Konzeption eines Vorgehensmodells zur Erstellung von Planspielen zu Schulungszwecken für die automobile Variantenfließfertigung. Garching: Lehrstuhl fml Nonaka, I., Takeuchi, H., Ingham, M. & Koenig, G. (1997). La connaissance créatrice: La dynamique de l’entreprise apprenante. Paris: De Boeck Supérieur North, K. (2010). Wissensorientierte Unternehmensführung: Wertschöpfung durch Wissen. Wiesbaden: Gabler Verlag Quilling, E. & Nicolini, H. (2009). Erfolgreiche Seminargestaltung: Strategien und Methoden in der Erwachsenenbildung. Wiesbaden: VS Verlag für Sozialwissenschaften VDI/VDE 3694:2008-01. Lastenheft/Pflichtenheft für den Einsatz von Automatisierungssystemen. VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik. Berlin: Beuth Verlag GmbH

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VDI 2221:1993-05. Methodik zum Entwickeln und Konstruieren technischer Systeme und Produkte. VDI-Gesellschaft Produkt- und Prozessgestaltung. Berlin: Beuth Verlag GmbH VDI 2519:2001-12: Vorgehensweise bei der Erstellung von Lasten-/Pflichtenheften. VDI-Gesellschaft Produktion und Logistik. Berlin: Beuth Verlag GmbH Vester, F. (1998). Denken, Lernen, Vergessen: Was geht in unserem Kopf vor, wie lernt das Gehirn, und wann läßt es uns im Stich? München: Dt. Taschenbuch-Verlag Wieczorrek, H., & Mertens, P. (2008). Management von IT-Projekten: Von der Planung zur Realisierung. Heidelberg: Springer-Verlag GmbH.

Authors/Contact Jan-Jasper Mühle, Markus Klevers Technische Universität München Munich, Germany [email protected] Johannes Schweizer BLSG AG, Ingolstadt, Germany

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Designing a Serious Game for Military Ethics Tijmen Muller, Gillian Visschedijk

Abstract Military personnel of all ranks and on all levels will encounter ethical dilemmas during their career. Ethical dilemmas may occur in day-to-day business and, more importantly, during military operations, in which certain decisions may mean a difference between life and death. In order to prepare military personnel for ethical decision making and to prevent decrease of moral standards, the Dutch Forces continuously provides training in military ethics. The type of experiential learning and immersion that serious gaming provides has the potential to play an important role in the development of moral professionalism: it can present the trainee with authentic scenarios containing ethical dilemmas, force him to make a decision and confront him with the possible consequences of these decisions. The experience gathered by playing the game is input for further discussion with peers and experts. This paper presents the design and evaluation of a serious game for military ethics based on previous experiences with a dilemma game. Keywords serious game, military ethics, design, training

1 Introduction In current operations, military personnel is frequently confronted with a variety of moral dilemmas. In a dilemma, a person needs to decide upon a way to act, while each decision is undesirable somehow or the outcome of each alternative is unclear. Military in particular are held accountable for their decisions, since they are granted the power to use force and in specific situations may have to choose between life and death. It is expected from them that they act morally correct, even in complex and dangerous situations. Constant attention to military ethics is needed with the current increase of the scale, complexity, and the technological possibilities of military operations in order to prevent unethical behavior as much as possible (Verweij, 2007).

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In order to train military in their moral professionalism it is necessary to confront them with compelling dilemmas and force them to make a decision. Current classes on military ethics often present ethical dilemmas in a classroom setting via text or short movies, or cases are verbally presented by students themselves when students are more experienced. An important emphasis is on discussion using a Socratic approach in which a dilemma is viewed from different perspectives. The discussions between students are key to the success of this method and depend largely on the group process. The disadvantage is that trainees are not forced individually to choose a way to act and this method allows them to have little or no part in the discussion. Additionally, discussing a single dilemma often takes a lot of time and may trigger a form of ‘group think’: the group is unable to keep with the Socratic rule of postponing judgment and agrees on a solution too quickly. Serious gaming provides the type of experiential learning and immersion that makes it potentially a valuable training tool for this subject (Oprins &‘t Hart, 2011), providing ways to tackle the aforementioned drawbacks. In a game, all trainees can be forced to make their own decisions, and a number of dilemmas can be presented in a short time. Discussion afterwards is still essential for the learning process, and will be livelier as all trainees were forced to think about the same dilemmas. Game statistics can be used by the instructor to (anonymously) show the differences in trainees’ opinions. Previous experience in the application of a serious game for dilemma training for mayors, the Mayor Game, has shown the feasibility for this type of gameplay (Stubbé, van de Ven & Hrehovcsik, 2014). Current games in use by the Dutch Forces do not primarily target these types of skills, but focus primarily on ‘military craftsmanship’ (Muller, Boonekamp, Smelik & Visschedijk, 2014). These considerations led us to focus our research on investigating the potential of a military ethics game for the Dutch Forces. To do so, we designed a new game based on the concept of the Mayor Game. This paper presents the process and results of the (re)design of the dilemma game for military ethics.

2 The Domain of Military Ethics Development of moral professionalism through training is important on all ranks and levels, but especially within the group of junior leaders. The lower military ranks have a great responsibility in current military operations, especially in peace-keeping operations, as they have to deal with both unclear threats and the harmless local population. They may have to make decisions with great impact, but are usually young and relatively inexperienced. It is essential to provide these commanding (non-commissioned) officers with training experience so they can develop their moral competence before they become part of a military operation.

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Three levels of moral competence can be distinguished: the cognitive, the affective and the voluntative level (van Baarda & Verweij, 2010). The cognitive level describes the competency to recognize the moral dimension of a problem or dilemma. If the cognitive level is underdeveloped, a person will fail to see that a problem is in fact an ethical problem, but will rather regard it as a practical or technical problem. The affective level describes the competency to show empathy and to view the ethical problem from a number of different perspectives. The problem is viewed without immediately preferring a biased and one-sided perspective. Finally, the voluntative level describes to competency to consistently act according to moral values. It describes the will to make decisions that agree with the own moral beliefs – in other words, integrity. This also implies that someone actually consciously knows the values one lives by, which is certainly not always the case. In order to gain experience with ethical decision making on each levels, training in military ethics should confront trainees with realistic military situations and require them to make a choice.

3 The Mayor Game The Mayor Game is a serious game that was developed within the “Safety” pilot of the GATE research programme (http://gate.gameresearch.nl/).The goal of the project was to design a serious game that supported crisis management training for policy makers, or more specific: mayors. During crises, mayors cooperate with a policy team, consisting of a number of advisors. Depending on the crisis, parties involved could be the policy advisors of the police, the fire brigade, paramedics, a communication advisor, et cetera. The primary learning goal is decision making on a strategic level and under time pressure. Training time of mayors is limited, so one of the preconditions was that the game should deliver a brief but valuable experience. Additionally, the game needed to focus solely on the learning goals of the mayors; the more traditional and commonly used table-top exercises require a large number of actors with each their own training goals, reducing the training effectiveness for the mayor. Finally, a safe training environment was of major importance for this training audience, since they cannot lose face as leader. Summarized, the game needed to provide a brief, single-player and anonymous training experience. The final design of the Mayor Game consisted of a web-based game, integrated in a broader training session. The game provides a number of scenarios, each containing around six to nine dilemmas that need to be solved within a limited amount of time (typically 15 minutes). Each dilemma is introduced with a few lines of text and ends with a question that needs to be answered by a simple ‘yes’ or ‘no’. The members of their policy team are available digitally and can provide additional information and advice. After resolving all dilemmas, statistics are pre-

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sented to the trainee summarizing the answers and which advisors were consulted. Additionally, an interpretation of the preferred leadership style of the trainee is presented through a web chart – the values in this graph are based on the answers that were given in the game. The main goal of playing the game is to confront the trainee with a variety of dilemmas and force him to go through the decision making process. The choices of the trainee do not have an in-game effect, but are only used in the final statistics; by definition it is not possible to assess the trainee’s answers to a dilemma as right or wrong. Most of the actual learning is done in the discussion and reflection phase following the experience of playing of the game. This process follows the idea of experiential learning. Currently, most mayors in the Netherlands have played the game more than once and think of it as a valuable training tool that really makes them think (Bronzwaer, 2011). Mayors are challenged by the variety of realistic and authentic dilemmas, but also because the game makes the players reflect on the nature of their own leadership and on their values. These aspects are key for the training of ethical dilemmas as well.

4 Military Ethics Game The design approach of the military ethics game was characterized by design iterations and prototyping from start to end. The available system architecture of the Mayor Game was a great advantage here. We were able to quickly design and implement a first dilemma and let experts on military ethics play it immediately, starting a discussion about the potential of a serious game for military ethics. Next, we focused on three basic design challenges: What are the learning goals and the context in which the game is applied? In other words, which elements of military ethics need to be incorporated in the game (learning goals), who will play the game, in what courses, etc. What changes in game concept are necessary? Elements from the Mayor Game, such as the advisors for a mayor and feedback on a mayor’s leadership styles, are not applicable for military ethics. Instead, key elements for ethics, such as the levels of moral competence and personal values, needed to be incorporated. What are good scenarios and dilemmas? The success of this type of game depends for a large part on the quality of the scenario and its dilemmas. Therefore a big effort was made designing these in such a way they are realistic, interesting, and provoking. The design challenges were faced during various activities. First brainstorm sessions and research into existing games and training methods for military ethics was performed. Existing reports on military ethics (Oprins &‘t Hart, 2011) were used for the design of the first scenario and dilemmas. ◆◆

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Second, several meetings with subject matter experts on military ethics were held, both from a theoretical background (military ethics professor) as well as from a more applied background (ethics instructors). They helped us keeping the design in line with theoretical foundations, deciding the focus of the learning goals, the proper fit in the current ethics curriculum for various target groups, and we discussed a suitable didactical setting. Next, prototype test sessions were held; first with fellow colleagues, followed by a focus group session with three instructors on military ethics and three military officers who experienced various ethical dilemmas themselves. In these test sessions we were able to discuss ideas for design changes, verify the quality of dilemmas and, most importantly, discuss new scenarios and dilemmas. Finally, a pilot was executed to test the game in an actual training with 25 trainees, military officers in the rank of Captain and Major. In this session the didactical setting, such as the introduction of the game and the discussion afterwards, was tested as well. The experience of the trainees, their opinion on the game and ideas for further improvement were collected by a questionnaire. 4.1 Learning goals and didactical setting There are several learning goals that the Military Ethics Game should target. First, the trainee needs to become familiar with the three levels of moral competence. For each of the dilemmas in the scenario a trainee should question himself to what extent there actually is a dilemma (cognitive level), realize there are several different ways to look at the dilemma (affective level) and think whether or not he acts in accordance to his own values (voluntative level). To be able to act in such a way, the trainee first needs to understand his personal values, which is something not many people consciously do – the Military Ethics Game should also target this goal of self-reflection. Finally, a wide variety of dilemmas are presented in the game, allowing the trainee to gain experience by putting this theory into practice and be confronted by many realistic military cases. Differences in answers to the dilemmas within the group of trainees provide an excellent starting point to explore and discuss the different perspectives on a given problem. Summarizing, like the Mayor Game, the Military Ethics Game should ‘make you think’. Given these learning goals, we believe the game will be especially useful at the beginning of a military ethics training program. The game can open up discussion and create sense of urgency, both important preconditions for a target audience who often think ethics is not an interesting subject. As with all experiential learning based on gaming, discussion and reflection after playing the game is crucial (Lederman, 1992). In addition, a link was made with an exercise that was already part of the training, requiring the trainees to make an inventory of the values they believed they held. Summarizing, a lesson with the Military Ethics Game looks as follows:

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1. Short introduction to the training; trainees make an inventory of the values they believe are important to them; a short discussion – 20 minutes. 2. Introduction to the game; playing the game individually or in couples (both having their advantages and disadvantages) – 20 minutes. 3. Discussion and reflection on the dilemmas; reflection on the game’s feedback (e.g. comparing the values to the inventory made in the previous exercise) – 30+ minutes. During the final discussion, an instructor can choose on what to focus and how detailed the dilemmas are explored. Additionally, the instructor can refer to theory to clarify specific aspects, e.g. to explain juridical consequences of certain actions. The choices for the didactical setting are in line with social constructivism theories like Job Oriented Training (van der Hulst, Muller, Besselink, Coetsier, & Roos, 2008). This is reflected by putting practice before theory in the curriculum, making learning active using the game, with realistic and challenging dilemmas to make it relevant, to rely on cooperation and reflection, and to have the instructor act as facilitator instead of teacher. 4.2 Core design choices One of the main learning goals is to consider a dilemma from various perspectives, i.e. the affective level. In our final design, the player may ‘ask advice’ from five advisors, each representing a specific interest: a chaplain (representing personal beliefs and gut feeling), a colleague (representing comradeship and social pressure), a commander (representing the mission goals and commanders intent), the minister of Defense (representing long-term goals and organizational interests), and a local authority (representing cultural relativism). Other perspectives were considered but discarded, such as the press and a legal advisor, for example because their opinion would be rather one-sided. These personifications of interests are presented to the player and can be asked for advice as in Figure 2. Additionally, the player may tick each perspective as ‘important’ for that specific dilemma. These choices are saved and summarized after playing the game, showing the player which of the perspectives had his preference. After answering a dilemma, the player is presented with a quick reflective questionnaire, asking him 1) how hard it was to make a decision; 2) what he believes the Dutch society will think of his decision; and 3) what he believes the local society will think of his decision. Note that the first question relates to the cognitive level, i.e. to what extent did the trainee feel this case actually was a dilemma. This information is saved and may provide input for a class-wide discussion on the notion what a dilemma actually is. The final aspect we focused on was the feedback system. In the Mayor Game, the decisions of the player are linked with different leadership styles. Follo-

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Fig. 2

The five personifications of different interests that are available for advice.

Fig. 3

Statistics on the underlying values of the choices the player made.

wing the choice to focus on the trainees’ own held values, we decided to link the answers to a dilemma with one or more of the following 8 virtues: wisdom, fairness, restraint, courage, responsibility, loyalty, honesty, and love. This collection of virtues contains the four cardinal virtues, the four personal qualities military should have according to the Dutch Forces’ vision on leadership (having courage as duplicate), and the theological virtue of love (in the sense of devotion to the wellbeing of others). Figure 3 gives an example of how this feedback is presented. This information relates to the voluntative level and should give the trainee insight into whether or not he acts according to his own moral standards. 4.3 Scenario design The design of a realistic scenario with challenging dilemmas was realized in close cooperation with military ethical experts. They provided realistic dilemmas and discussed some more high level implications. For example, it was concluded that the flow of the story with some images of movies adding to the text is important to create an immersive environment in which it is easier to consider oneself in the situation. Also, it was decided that it is necessary to focus on a specific role of the player and to emphasize its task, as ‘the military’ is of course a broader target audience than mayors. Consequently, we focused our first scenario on an infantry platoon commander, as this would initially be our target audience of the pilot. Eventually, we stringed together seven dilemmas within one scenario, following a platoon commander going on a UN mission abroad in the fictive country of Xona. Some examples of scenarios are whether or not you would provide first aid to a grandchild of a highly respected village elder who had just heavily beaten this child and whether or not you would use force on a farmer who may be able to help recover a wounded colleague but refuses to help.

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5 Pilot The Military Ethics Game was evaluated by means of a pilot. The game was played by a group of trainees (n = 25) of the intermediary course for officers, a required training for officers within the Dutch Forces to become the rank of Major or equivalent. The didactical setting was as described before, where each trainee played the game individually and discussion and reflection was led by a teacher in military ethics. Afterwards, a 31-item questionnaire was used to assess the game on six scales: value and usefulness, engagement, challenge & control, rules & goals, action language (i.e. ease of use) and game world (e.g. attractiveness and realism). The scales were used previously in several (game-related) studies (Deci, Eghrari, Patrick & Leone, 1994; Oprins, Bakhuys-Roozeboom, & Visschedijk, 2013). The items were randomized and scored on a 5-point Likert scale, ranging from 1 = completely disagree to 5 = completely agree. The results (see Table 1) indicate that this group of trainees is fairly positive about the value and usefulness of the game to train military ethics (M = 3.417, SD = .686). We believe that the training value will increase if the teacher gains more experience with the didactical setting, as this was the first time he used a game as a training tool. Interesting in the results is also that challenge and control is experienced by this group of trainees as more or less neutral (M = 2.936, SD = .660). This can be explained in part by the fact that the scenario was designed for the level of platoon commanders, while these trainees have already past that stage in their career. The fact that the game was still in a pilot phase using a preliminary version of the game can explain the rather neutral scores of game world. Consequently, the visuals (both on the conceptual level as well as aesthetics) need to improve in a following version of the game. These explanations and additional suggestions for improvement were also mentioned in the short group interview that was held with the trainees at the end of the pilot. The overall notion was that trainees thought the game has even more training value for a more inexperienced target group. Scale (# of items)

Mean (SD)

Cronbach’s Alpha

Value and usefulness (7)

3.42 (.69)

.930

Engagement (6)

3.25 (.81)

.911

Challenge & control (5)

2.94 (.66)

.659

Rules & goals (5)

3.37 (.55)

.632

Action language (4)

3.70 (.60)

.693

Game world (4)

2.91 (.70)

.613

Table 1 Results of the pilot (n=25) with a maximum score of 5 for every item

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6 Conclusion and discussion The expert sessions and the results of the pilot show that the Military Ethics Game, based on the game concept of the Mayor Game, can have training value in initial military ethics training. We believe the game makes experience-based learning possible that was as of yet not available within this domain. Additionally, the process of (re)designing the game has shown that the game concept can be reused for a new domain with relatively little effort. Additionally, we have collected several recommendations during the design and the evaluation phases that could improve further use of this game concept: Visualization: The personifications of the interests were somewhat confusing for the military, as these persons are of course not available in real-life situations. The visualization of the game did not allow them to view these advisors as a metaphor for ‘voices in your head’ or angels (or devils, if you will) on your shoulder as they were meant. More thought has to be put into the presentation of this aspect of the game. Advisor-assigned feedback: When linking the values to the ‘yes’- and ‘no’-answers for each scenario, we realized that values could be even better assigned to the different advisors, allowing feedback on a more detailed level. At the moment this is technically not possible, but would be desirable for a following implementation. Class statistics: Statistics based on the answers of all the trainees, such as preferred answers for a specific scenario or most-selected virtue, may be very helpful for the instructor. For example, it allows him to show the diversified opinion of the trainees on a dilemma to start a discussion. These statistics should be made available in a next version of the game concept. Domain-, experience- and mission-specific scenario design: In order to optimally challenge trainees, they need to be able to relate to the scenario in terms of perception and experience. For example, during the pilot the game was played by military from the army, navy, air force and military police in the rank of Major (or equivalent), but the scenario was designed from the perspective of an infantry platoon commander. Different scenarios need to be designed to better serve different audiences. Another interesting way to use the game is as part of mission-specific training, in which country- or culture-specific elements should be part of the scenario design. ◆◆

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References Bronzwaer, S. (2011). Extreem-rechts wil BBQ, wat nu? NRC. Deci, E. L., Eghrari, H., Patrick, B. C., & Leone, D. (1994). Facilitating internalization: The self-determination theory perspective. Journal of Personality, 62, 119—142. Lederman, L. C. (1992). Debriefing: Toward a systematic assessment of theory and practice. Simulation & Gaming, 23(2), 145—160. (1992) Muller, T.J., Boonekamp, R.C., Smelik, R.M., & Visschedijk, G.C. (to be published). Serious gaming voor opleiding en training van kaderleden. TNO report. Soesterberg. Oprins, E., Bakhuys-Roozeboom, M., & Visschedijk, G. (2013). Effectiviteit van serious gaming in het onderwijs. Onderwij sinnovatie, 32—34. Oprins, E., & ‘t Hart, M. (2011). Normvervaging in de militaire praktijk. TNO report TNO. Stubbé, H., van de Ven, J.G.M., Hrehovcsik, M. (2014). Games for Top Civil Servants: an integrated approach. In: Ruggiero, D. (ed.), Cases of Societal Effects of Persuasive Games. Igi-global.com. van Baarda, Th.A., & Verweij, D.E.M.: (2010). Militaire ethiek – een algemene inleiding. In van Baarda, Th. A., & Verweij, D.E.M. (eds.), Praktijkboek Militaire Ethiek: Ethiek en integriteit bij de krijgsmacht, morele vorming, dilemma training (pp. 17—48). DAMON, Budel. van der Hulst, A.H., Muller, T.J., Besselink, S., Coetsier, D., & Roos, C.L. (2008). Bloody Serious Gaming: Experiences with Job Oriented Training. In The Interservice/Industry Training, Simulation & Education Conference. National Training Systems Association. Verweij, D.E.M. (2007). Morele professionaliteit in de militaire praktijk. In Kole, J. & De Ruyter, D. (eds.), Werkzame idealen – ethische reflecties op professionaliteit (pp. 126-138). Koninklijke van Gorcum, Assen.

Authors/Contact Tijmen Muller, Gillian Visschedijk TNO Soesterberg, The Netherlands [email protected]

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Glitches, Players, and Metagames: Another Family Conversation James Darrel Murff, Elizabeth Jane Tipton

Abstract This paper is a continuation of a series reporting on a long conversation between an educational game design mother and her entertainment game tester/reporter son. It began many years ago with things educational game designers could learn from the entertainment game industry. Recently, the conversation wandered into programming glitches and emergent behavior. The discussion has now moved onto the topics of player agency, emergent gameplay, player archetypes and metagaming. Keywords emergent gameplay; player agency; player archetypes; metagaming

1 Introduction In 2009, our decade-long conversation on the differences and commonalities between games for entertainment and games for education was made public during panel discussions at ISAGA and ABSEL. At that time, the focus was on improving educational game design through an understanding of the problems commonly seen in during the testing and consumption of entertainment games. These conversations have continued to this day, more recently focusing on games going wrong. More recently, the conversation has turned to player agency, emergent gameplay, player archetypes and metagaming.

2 Glitches There are many tales of games not turning out as expected. Sometimes games have so many glitches that they are unplayable, as in BIG RIGS: OVER THE ROAD RACING (2003) where the physics are abnormal, the AI is non-existent, and the win conditions cannot be attained. Other games suffer from poor design choices, as in RIDE TO HELL: RETRIBUTION (2013) where the game lost its open-world elements during revision to result in an exceedingly offensive linear

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game so bad that the only positive remark in Electronic Gaming Monthly was about the pause menu (Harmon, 2013). However, glitches do not necessarily lead to unplayability. The Elder Scrolls V: SkyriM (2011) has hundreds of bugs where non-player characters behave unexpectedly, getting stuck repeating the same routine over and over again or having their animations glitch out strangely. Players have turned these glitches into a form of egg hunting, posting videos of these odd behaviors on YouTube. Bethesda, the game’s developer, has kept certain glitches in the game just for their entertainment value. Red Dead Redemption (2010) had some of its glitches immortalized online as memes: the gunslinger-dog, the bird-people, and the cougar-man, and the donkey-lady. The programmed non-player character behaviors became associated with the wrong animations. MINECRAFT (2011) took advantage of one glitch by repurposing it, creating the character known as the creeper from a failed model for a pig. The creeper has been merchandised as in stuffed toys, action figures, LEGO and apparel. It has even appeared in TV shows, music concerts, and games produced by other companies. Glitches are not restricted to the entertainment gaming industry as they also happen in educational games. Two papers (Wolfe & Jackson, 1989; Wolfe, 1993) discuss situations where the advertising demand function within business games violated the economic concept of advertising elasticity of demand. Players were apparently unaware that the games’ external validity was broken. In terms of learning outcomes, this is of serious concern as business games are used for training/evaluating players’ business skills (Greco et al, 2013). Sometimes, glitches can occur in educational games without derailing the learning outcomes. During one play of the supply chain simulator, THE MIT BEER GAME (Sterman, 1992), small coins were used to represent product being delivered. A player stumbled and dropped about 400 of them on the floor. As coins flew everywhere, the players demanded that the game stop as those downstream in the supply chain did not receive their product. A local businessman participating in the game exclaimed “Have you never heard of a beer truck wreck?” The class played on. Glitches can also be caused by deliberate errant player behavior. In another international business simulation contest, a team performed well yet the members were quite unhappy. When asked, one member reported that the decisions were not what the team had submitted to the contest site, but rather matched those proposed by one and turned down by the rest. When confronted, the suspicious team member admitted to changing the decisions after they had originally been turned in. The team “fired” that member and went on to win the contest.

3 Emergent behavior Emergent behavior is when specific components of a game behave as they are supposed to, but they either go too far with their behaviors or interact in ways the

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developer didn’t originally intend. The Radiant A.I. system developed by Bethesda for THE ELDER SCROLLS IV: OBLIVION (2006) and then expanded for use in SKYRIM allowed non-player characters to interact with the game world by establishing goals without specific scripts for achieving them. While this gave the games a more organic feel for the players, it also caused non-player characters to satisfy their programmed needs in strange ways. In perhaps the funniest example, players committing crimes were being caught even though they appeared have been unseen by other characters. Bethesda finally tracked it down to the non-player chickens reporting the crimes to the non-player guards. Emergent behavior is not restricted non-player interactions. In CRACKDOWN (2007), one car type gains traction and suspension with as the driver’s ability increases. When the maximum level is reached, the car’s traction is strong enough to grip the side of a vertical surface, allowing the player to drive up the sides of buildings. Emergent behavior in game engines created now common game mechanics. A glitch in the programming of STREET FIGHTER II (1991) allowed for players to skip the recovery time of a move by performing another within a specific time window. Though entirely unintentional, this mechanism allowed players to string together moves to deal more damage to opponents and thus created a hallmark feature of fighting games. Straferunning occurred in DOOM (1993); bunny-hopping arose from QUAKE (1996). These result in dramatic increases in player’s speed. The QUAKE engine is also responsible for the creation of rocket jumping due to the way it pushes back characters when rockets explode, resulting in players jumping significantly higher by shooting at their feet. Software embraced these by designing maps with secrets accessible only through these emergent behaviors. Other developers have also incorporated these; the designers of TEAM FORTRESS 2 (2007) incorporated rocket jumping to give heavier characters greater mobility. Emergent behavior is not restricted to the entertainment gaming industry as it also happens in educational games. During the play of a marketing simulation many years ago, students provided their decisions by punched cards. The program, at that point in time, did not validate the inputs. One team input actual number of units to be manufactured, forgetting that the number was to be coded in as a thousand unit block. When the computer run was completed, they ended up with an overwhelming amount of inventory. Due to the feature that automatic loans were provided if a firm underestimated its cash needs, the team also had an insurmountable debt. During play of the business simulation CAPSTONE (1986), one poorly performing team suddenly changed their price from $24 to $24,000 near the end of the game. This resulted in the firm having zero sales, as expected. However, industry demand was a function of all prices in the industry and thus total sales also went to zero, completely collapsing the marketplace. When asked why, the team stated that they assumed the lagged effect of price on demand would let them sell a few first, and thus make a lot of money. Hofstede & Murff (2011) re-

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port on an experience where an old well-tested game, SO LONG SUCKER (Shapely et al., 1964), demonstrated emergent behavior when used in a multicultural classroom. This game was designed by a group of American mathematicians to demonstrate unstable coalitions. When played by American students, cooperation existed only in the short term as expected. When played by Taiwanese students, a new behavior emerged as cooperation existed well past the point where it was obvious that the game rules would not allow a team solution. When both groups were mixed, a new behavior emerged among the American students as they adopted some, but not all, of the behaviors of the Taiwanese students. Many developers have attempted to stimulate the process of emergent behavior with varying success. However, the only true way to harness emergent design is to watch how students approach a particular game. GRAND THEFT AUTO (1997) is based on the concept of making the player feel as though they have discovered something clever or outside the bounds of the game, even though the designer purposefully allowed for the “rampage” behavior. In DISHONORED (2012) and DEUS EX (2000), player choice determines the path through the game. Although the game scenarios are more violent in nature, it is actually possible to complete these games without harming anyone. Players are not forced into specific actions to complete objectives, but are allowed choice. Intentional emergent behavior is not restricted to these genres. Completion of the puzzle determines success in games such as THE INCREDIBLE MACHINE (1992). The very first modern table-top role playing game, DUNGEONS & DRAGONS (1974), encouraged players to develop their own house rules, styles of gameplay, and narratives. This is not even a new idea; H.G. Well’s encouraged intentional emergent behavior in Little Wars (1913) in the chapter entitled “Ending with a sort of challenge.” This intentional emergent behavior can also be seen in educational game settings. In “The Bunny Festival” developed at ISAGA Summerschool 2012, the specifications for a product to be manufactured were given via an instruction sheet. These appeared to be rigid steps; yet when read carefully, it is apparent that no steps were actually given. When the designers realized that their project encouraged emergent gameplay, the game was altered to run for two production rounds with a mid-game debriefing to encourage those that had not done so already to “think outside the box.” During testing and in classroom use so far, players have found unique unanticipated ways to satisfy each of the specifications by “thinking outside the box.” In 2005, Peter Molyneux, the designer of POPULOUS (1989) and THEME PARK (1994), commented that players of the next-generation of games would “want to customize the experience, setting their own goals in a world that they can play around in” (Kosak, 2005). Students that we are designing for now have grown up in this environment of games encouraging emergent behavior. This is particularly evident in a recent study of undergraduate students and information technology (Dahlstrom, 2012), where 55% of the students “wished

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instructors used more simulations and educational games.” Emergent behavior, no matter the source, gives the player the feeling of having discovered something. Even if a game is designed specifically to encourage players to try a particular behavior, allowing the choice reinforces the belief that the game allows for true interaction and thus enhances player agency.

4 Player Agency Designer intent is how the designer intends for the game to be played and for the game systems to interact; player agency is how the player approaches the choices given to them by the designer. Player agency is what separates a game from a non-interactive medium like a book or movie as it affects the course of the game, even in miniscule ways. CALL OF DUTY (2003) has very little player agency; the player’s only interactive role is to kill enemies to advance in the game. Conversely, DWARF FORTRESS (2006) is often lauded as a prime example of player agency, as every small decision has a natural and evolving impact on the game world. This matters because games are not merely lectures from a designer to a player. They are more akin to a dialogue; the designer dictates, and the player refutes or agrees. This is obviously abstracted, of course. For example, the “dictation” of the designer may be where enemies are placed, and the “refutation” of the player is how the enemies are eliminated. It’s a conversation where one party — the designer — can’t hear the other party’s side of the conversation until the conversation itself is finished. This is especially important to remember because games are not static. The way players approach games and interact with them changes over time. This is not just a social or cultural trend, but an exploration of the old-made-new. Players are still finding quirks in old games such as DOOM or LEGEND OF ZELDA (1986) and discussing them and posting about them online. The goal is to build a game that offers the player enough agency to ensure their exploration of the game and the concepts within. Problems have been long noted with the completely predictable environment of the typical classroom (Dewey, 1916); this setting is particularly dissonant for students who have been raised with games that encourage player agency and emergent behavior. This means that educational games must be designed with a greater focus on interlocking and observable systems rather than direct teaching. Learning should at least be partially auto-didactic; players should interact with the game and at least recognize new concepts, even if they don’t understand them. Students may even break the game in an unexpected manner, as in the SO LONG SUCKER experience. In a predictable environment, the teacher would force the students back on track to the planned learning outcome. Through skilled debriefing, a teacher using a game designed for greater player agency can expand the lesson and address the concepts discovered by the students. The teacher can even

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use emergent behaviors to teach a different lesson than the one initially planned. Thus, players learn in a more natural way through the use of their internal agency, rather than being told what they have to know. However, the potential for deviation from the planned learning outcome due to player agency appears to be problematic for some in the current educational environment of common standards and rigorous assessment. Player agency can often be tied to the principle of “players will do anything they can figure out how to win.” PORTAL (2007) has a situation that requires solving several smaller puzzles in order to complete a bigger puzzle. Valve found that experienced players were skipping the main puzzle entirely by flinging themselves in an unanticipated manner. Rather than taking a few minutes, these particular players were solving the bigger puzzle in seconds. Yet not all players chose this option, as players can differ greatly in their personal goals when playing games.

5 Player Archetypes Players behave according to a principle that is best paraphrased from physics: “Players seek their lowest natural state.” In other words, players seek the easiest, most straightforward avenue for their goals as possible. The goals, however, are not necessarily those defined by the game designer. Whatever the goals are, and whatever the players take out of them, comes down to which archetype they belong to: Power, Challenge, or Exploration. Power gamers focus on victory above all else. They will bend — or even break — the rules in order to gain an advantage. This often manifests itself as using weapons that are stronger than others (“unbalanced”), utilizing strategies that have a high chance of winning against weaker players (“cheesing”), and memorizing program bugs that grant some advantage (“glitching”). These players will run roughshod over other players and even the game itself in their bid for victory. This roughly correlates to external motivation. Power gamers are not motivated to play games which have no designer-defined goals. They need some sort of structure in their gaming life in order to function. Make a power gamer play a sandbox game with no goals whatsoever — such as MINECRAFT or DWARF FORTRESS — and they will likely quit out of boredom. This is not a bad thing. Power gamers are the easiest players to predict, as they always follow the win condition. To put yourself in the mind of a power gamer, you work backward from victory to figure out how the win condition can be circumvented, exploited, or otherwise cheated. Consider a power gamer playing “capture the flag” in a game that allows for the use of vehicles as well as running around on foot. The victory condition (game goal) is to capture a specified object, usually a flag, at the other team’s home base and return it to the gamer’s home base. Working backward from the victory condition, it’s clear that the power gamer will obtain the flag in the

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quickest possible manner. They will then most likely seek out a vehicle soon after grabbing the flag; this will, after all, confer a distinct survival advantage and thus make the victory that much easier. If there is no vehicle available, they will use weaving, unexpected paths, and difficult-to-reach areas to throw off pursuers and make it back to home base. The best designers, rather than punishing these players for outside-the-box thinking, make their unusual behaviors a part of the game. For example, when the shortcut in PORTAL was discovered during play-testing, the developers left it in and formulated a challenge around it. The developers of DISHONORED noticed that players were using their given supernatural powers in unusual ways and combinations. Rather than smacking their hands and telling them no, these alternative uses were embraced, leading to a wide variety of paths to the single win condition. Player agency was enhanced through the designers learning of alternatives from the power players. In an educational setting, these players are the ones that are most likely to rip your game apart within the first session or two. They will always seek out the victory — whatever that may be — and will attempt to achieve it as quickly as possible. If they can’t, they will continually try new tacks until one works. These are the students that ask the wellworn question: “Will this be on the next exam?” Challenge gamers are those who play games not because they want to win but because they want to be challenged. This means that they often devise unusual tests in order to heighten the difficulty. Refusing to use certain gear, approaching the game from a far more difficult angle, and playing against players who are obviously and significantly better are all a part of the challenge gamers’ repertoire of tricks. This player has a balance between internal and external motivations. Challenge gamers seek to win (external) similar to a power gamer but do so according to their own modified rules (internal). Much like the power gamer, they thrive best in environments with goals of some kind. However, they also do well in a sandbox environment, as this allows them more freedom to express their need to challenge themselves. Player agency is an important component of this expression. Where the power gamer is exceedingly easy to predict, the challenge gamer is far tougher. Where you can simply look at the optimal path to a goal for the power gamer, you must also consider modifying that path for the challenge gamers. For example, a challenge gamer might refuse to move past a game obstacle until it is defeated, where a power gamer will often simply circumvent the obstacle if possible without interacting with it. In an educational setting, challenge gamers are those players who often force themselves into more difficult situations. This is rarely conducive for their learning, but is very helpful to the educator, as the knowledge gleaned from challenge gaming can be used to further refine the game in question. Think of these as pruners; you can use them to locate and remove extraneous lessons from your game until the one left is the one you intend to teach. These are the students that will latch onto a particular topic, such as dinosaurs,

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and then proceed to learn everything that they possibly can about only that one topic before moving on to something new. Finally, there are exploration players. These players indulge in games not because they want to win or to challenge themselves, but rather because they want to explore the systems that make the game function. They are the most difficult player archetype to predict, as they often indulge in behavior that is directly contradictory to the explicit goal of completing the game. For example, exploration players may just spend time looking at and admiring the textures in a room rather than progressing to the next area of the game. Exploration players are almost entirely internally motivated. Rather than deriving pleasure from completing the designed challenges, they derive pleasure from whatever personal qualities they prefer. Where one exploration player might enjoy listening to every sound in the game and judging how they interact with each other, another might focus on seeing how the non-player characters react when something is done outside normal parameters. They may set off on a quest of their own devising to locate unreported glitches or they may invent completely new ways to play old games. You can’t design a linear game around an exploration gamer as they will rapidly lose interest in a game that forces them into a particular win condition outside their own goal. Exploration gamers thrive when placed into environments with plenty of experimentation; MINECRAFT and DWARF FORTRESS are fantastic and obvious examples, but any game with unusual systems will generally hold their attention. For example, an exploration gamer may play WORMS ARMAGEDDON (1999) in order to better understand the way the wind physics work. In an educational setting, exploration gamers are incredibly valuable. Not only do they expand the parameters of the game simply by approaching it in their own unique way, they open dialogues with the designer that the designer can’t predict. This means that a designer can learn more about their own game through an exploration gamer than they originally thought possible. In the classroom, these are the students are difficult to motivate in a traditional lecture and exam structure. Getting them to turn in their homework can be exasperating. Yet, these are also the students that will create new ideas and find unexpected connections between old ones. All of these gamer archetypes, however, have one thing in common: they want to be invested in the game. Whether it be through victory, challenge, or exploration, each type of player has their own ideals and goals. The easiest way players accomplish these is through the use of metagaming.

6 Metagaming Metagaming is the act of creating a “game outside the game” by altering the game parameters through non-game actions. If a game is made up of gaming structures — mechanics dictated to the player by the designer — then metagaming is made

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up of metastructures — mechanics dictated by the player to the game. Metastructures can act as a recontextualization of existing mechanics or motivations, but they can also be wholly unpredictable. The most common form of metagaming is metacompetition. When players can’t directly compete with one another, they compete in other, more creative ways. Leaderboards, which show off the best players around, are a common metagaming structure supported by developers. Speedrunning, which is completing a game as quickly as possible either alone and through the use of tools to make the impossible easier , was a natural offshoot of the common arcade goal of completing levels as quickly as possible and has been noted at least since the release of the LEGEND OF ZELDA (1986). Another relatively common form of metagaming is theorycrafting, the art of taking game mechanics and examining them to understand what is the best possible outcome. This is common across all genres and acts as a socialized version of powergaming, where a group of players methodically discovers the most optimal solution to a game. Collaborative data collection, in which players band together to gather data, share information, and theorycraft outside the game’s confines through online forums has been seen in relation to both WORLD OF WARCRAFT (2004) and DARK SOULS (2011) as well as many other games. Then, there are less common metastructures. Using violent games creatively rather than destructively has spawned spectacular creations. Within MINECRAFT, giant cola cans floating in the sky, immense yet intricately-detailed castles, and even the Taj Mahal have been built. Players may create real world objects like the Turing-complete calculator powered by dwarves built within DWARF FORTRESS. Successor games, in which a player plays a single-player game for a while and then hands it off to another player, have resulted in tales such as the one that occurred in DWARF FORTRESS where belligerent dwarf-eating elephants died in a biblical-level flood of lava. A few games, with EVE ONLINE (2003) as the most notable, incorporate political maneuvering as a metastructure. More wars in EVE ONLINE are won and lost in the smoke-filled back rooms than on the battlefield. The comp-stomp, that is playing a competitive game against the game’s AI, rather than other players — is commonly seen amongst strategy game players, but it is rare outside of this genre. Emotional metagaming — taunting, fakeouts, and mindgames — is common within the fighting game community, but is almost entirely neglected in other genres due to the impersonal nature of playing against other players over a network. Finally, there are some metastructures that seem obvious in hindsight, yet are so rare that it’s surprising they were ever discovered. The clearest and most recent example of this is occurred earlier this year with TWITCHPLAYSPOKEMON (2014). This particular metastructure uses a videogame video streaming service and internet chat to create a place where thousands upon thousands of

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players can attempt to play the same instance of a game at the same time. Imagine a hundred thousand players all mashing buttons on the same hand-held Gameboy. This social experiment of using internet viewers as a collective mind to input game commands to a turn-based low-penalty-for-failure game is something wholly original and entertaining, if somewhat frustrating for the players at times. During the first run of the game, it took over 16 days of continuous play to complete a game that averages around 50 hours. Metastructures can also occur in the classroom. When SO LONG SUCKER was used in a Swiss-system tournament, four students were actually playing to lose but only some of the time. During the debriefing, these students explained that were curious to see if what they had learned about negotiations and strategy in another course could be implemented to attain a goal they had self-determined. They were attempting to manipulate the tournament to ensure that only they would be in the finale together. These students changed the game system in an unplanned manner to convert theory into experience and experience into learning. In a nationwide simulation contest, a team did some very sophisticated data analysis of the other teams’ results and made very good estimates of the other teams’ decision making processes. One of the judges had noticed and asked the team how they were able to accomplish this task. A student explained a few analytical tools that he was using, and then turned to the judge and said, “Are you able to comprehend what I am explaining to you?” The student was not playing to outperform the other teams, but rather to outperform those administering the game.

7 A final thought Gamers do not all approach games with the same goals and motivations, just as students do not all learn in the same manner. Students playing games for educational purposes may create new metastructures that the instructor is unaware of during the game play. This then is yet another reason why debriefing is absolutely necessary for establishing what students actually learned from a game. The learning goals established by the game designer may not be the learning goals achieved by the students. After all, “most learning is not the result of instruction. It is rather the result of unhampered participation in a meaningful setting.”  (Illich, 1972)

References BIG RIGS: OVER THE ROAD RACING. Stellar Stone, LLC. (2003). Santa Monica, CA: Stellar Stone. (http://en.wikipedia.org/ wiki/Stellar_Stone) CALL OF DUTY. Infinity Ward. (2003). Los Angeles, CA: Infinity Ward. (http://www.infinityward.com/games/) CAPSTONE. Capsim. (1986). Chicago, IL: Capsim. (http://www.capsim.com/capstone/) CRACKDOWN. Realtime Worlds. (2007). Redmond, WA: Microsoft Game Studios. (http://www.microsoft.com/games/)

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Dahlstrom, E. (2012). ECAR Study of Undergraduate Students and Information Technology, 2012. Louisville, CO: Educause Center for Applied Research. DARK SOULS. From Software. (2011). Tokyo: Namco Bandai Games. (http://www.bandainamcogames.co.jp/english/) DEUS EX. Ion Storm. (2000). London: Eidos Interactive. (http://en.wikipedia.org/wiki/Eidos_Interactive) Dewey, J. (1916). Democracy and Education. New York, NY: Macmillan Company. DISHONORED. Arkane Studios. (2012). Rockville, MD: Bethesda Softworks LLC. (http://bethsoft.com/) DOOM. id Software. (1993). New York, NY: GT Interactive. (http://en.wikipedia.org/wiki/GT_Interactive) DUNGEONS & DRAGONS. Gary Gygax & Dave Arneson. (1974). Lake Geneva, WI: Tactical Studies Rules. (http://en. wikipedia.org/wiki/TSR,_Inc.) EVE ONLINE. CCP Games. (2003). Reykjavik: CCP hf. (http://www.ccpgames.com/en/home) GRAND THEFT AUTO. Rockstar North. (1997). New York, NY: Rockstar Games. (http://www.rockstargames.com/) Harmon, J. (2013). EGM Review: Ride to Hell: Retribution. Electronic Gaming Monthly. Lombard, IL: EGM Digital Media, LLC. Retrieved from http://www.egmnow.com/articles/reviews/egm-review-ride-to-hell-retribution/ Hofstede, G.J., & Murff, E.J.T. (2011). Repurposing an Old Game for an International World. Simulation & Gaming 43, 1, 34—50. Greco, M., Baldissin, N., & Nonino, F. (2013). An Exploratory Taxonomy of Business Games. Simulation & Gaming 44, 5, 645—682. Illich, I. (1972). Deschooling Society. New York: Harper & Row. Kosak, D. (2005). Peter Molyneux on Next-Generation Game Design. Gamespy. San Francisco, CA: IGN Entertainment. Retrieved from http://www.gamespy.com/articles/594/594887p1.html LEGEND OF ZELDA. Nintendo EAD. (1986). Kyoto: Nintendo Co., Ltd. (http://www.nintendo.com/) MINECRAFT. Mojang AB. (2011). Stockholm: Mojang AB. (https://mojang.com/) POPULOUS. Bullfrog. (1989). Redwood City, CA: Electronic Arts. (http://www.ea.com/) PORTAL. Valve Corporation. (2007). Kirkland, WA: Valve Corporation. (http://www.valvesoftware.com/) QUAKE. id Software. (1996). New York, NY: GT Interactive. (http://en.wikipedia.org/wiki/GT_Interactive) RED DEAD REDEMPTION. Rockstar San Diego. (2010). New York, NY: Rockstar Games. (http://www.rockstargames.com/) RIDE TO HELL: RETRIBUTION. Eutechnyx. (2013). Bavaria: Deep Silver. (http://www.deepsilver.com/home/) Shapley, L. S., Nash, J. F., Hausner, M., & Shubik, M. (1964). ‘So Long Sucker,’ A four-person game. Game Theory and Related Approaches to Social Behavior (M. Shubik, ed.). New York: John Wiley & Sons, Inc. SLAVES TO ARMOK: GOD OF BLOOD CHAPTER II: DWARF FORTRESS. Tarn Adams. (2006). Unknown: Bay 12 Games. (http://www.bay12games.com/dwarves/) Sterman, J. D. (1992). Teaching takes off: Flight simulators for management educations: THE BEER GAME. Retrieved from http://web.mit.edu/jsterman/www/SDG/beergame.html. STREET FIGHTER II. Capcom. (1991). Osaka: Capcom. (http://www.capcom.com/) TEAM FORTRESS 2. Valve Corporation. (2007). Kirkland, WA: Valve Corporation. (http://www.valvesoftware.com/) THE ELDER SCROLLS IV: OBLIVION. Bethesda Game Studios. (2006). Rockville, MD: Bethesda Softworks LLC. (http://bethsoft.com/) The Elder Scrolls V: Skyrim. Bethesda Game Studios. (2011). Rockville, MD: Bethesda Softworks LLC. (http://bethsoft.com/) THE INCREDIBLE MACHINE. Kevin Ryan. (1992). Eugene, OR: Dynamix, Inc. (http://en.wikipedia.org/wiki/Dynamix) THEME PARK. Bullfrog. (1994). Redwood City, CA: Electronic Arts. (http://www.ea.com/) TWITCHPLAYSPOKEMON. Twitch Interactive. (2014). San Francisco, CA: Twitch Interactive. (http://www.twitch.tv/ twitchplayspokemon) Wells, H.G. (1913). Little Wars; a game for boys from twelve years of age to one hundred and fifty and for that more intelligent sort of girl who likes boys’ games and books. London: F. Palmer. Wolfe, J. (1993). On the Propriety of Forecasting Accuracy as a Measure of Team Management Ability: A Preliminary Investigation. Simulation & Gaming 24, 1, 47-62. Wolfe, J., & Jackson, R. (1989). An Investigation of the Need for Algorithmic Validity. Simulation & Gaming 20, 4, 272-291. WORLD OF WARCRAFT. Blizzard Entertainment. (2004). Irvine, CA: Blizzard Entertainment. (http://us.blizzard.com/en-us/) WORMS ARMAGEDDON. Team 17. (1999). Wakefield, UK: Team 17 Digital Limited. (http://www.team17.com/)

Authors/Contact James Darrel Murff TheMittani.com, Seattle, USA [email protected] Elizabeth Jane Tipton Eastern Washington University, Spokane, USA [email protected]

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Adaptation of Business Game for Learning of Geographic Information Systems in Debriefing Stage Irena Patasienė, Martynas Patasius, Grazvidas Zaukas

Abstract The paper deals with the cases of interdisciplinary learning that help the business administration students to learn to work with specific software packages. The experience shows that the students of business administration studying the business geographic systems module find it relatively easy to carry out laboratory works with the presented sequence of work steps. They, however, face difficulties in understanding the benefit of application, i.e., where and to what degree geographic information system can be applied in practice. The quality of business information systems study was improved by modeling the company’s performance by means of the computer business game. Since the business game ‘HARD NUT’ allows the students to gain access to the data base (DB) structure, they were offered the possibility to change the structure of the game DB thus enabling them to make use of the geographic information system ArcGis on-line accessible via the internet. The model described in the paper allows the students to get better awareness of the benefit of information system reorganization aimed at the improvement of the enterprise’s competitiveness. Organized debriefing helps a student to understand GIS more deeply. Keywords Business Game, Debriefing, Geographical information systems

1 Introduction The study quality is improved by modernizing the study programs; however, the students’ or employers’ interviews show that the task of combining the knowledge of several subjects remains difficult, specifically, if their learning was far back in time. The problem becomes even more relevant if different IT software packages have to be selected and applied. Different study program subjects used a specific software; however, usually little attention is paid to the problem of ICT equipment

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compatibility. The idea of the business enterprise’s computerization becomes even more complicated in the case of e-learning. The highlighted problem is corroborated by the analysis of literature sources. According to Skrudupaite and Jucevicius (2009), as many as 90% attempts made in implementing the synchronized system of production management fail. The greatest difficulties occur in coordinating reorganization in different segments of the system. The conclusion is that the businesses do not have a sufficient number of systemically thinking specialists; therefore, the universities should improve the quality of training. The curricula should be supplemented by the instruments aimed to stimulate systemic thinking of the students, thus ensuring their knowledge where and when reasonably selected ICT measures can be readily and precisely applied. Stankevice and Jucevicius (2012) emphasize the importance of application of the simulation models, i.e., the scientists maintain that the strategy of simulation innovations help survival of the businesses which are able to timely and in place simulate the products and processes which are innovative only for the businesses themselves. It is difficult to carry out the insight into business in time without preparation and without sufficient experience. The realization of the multidisciplinary principle in the study process should contribute to the solution of the problem (Smaižienė & Jucevičius, 2009) and the usage of real business data (Bagdonas et al., 2012). Motzev (2010) suggests using a simulation game in the study process encompassing all the production processes: team formation, development and launching a new product, pricing, etc. The measures mentioned undoubtedly improve the study quality; in addition, the benefit of interdisciplinary learning is ensured to a higher degree, the nucleus of which is integrated into several subjects of the curriculum, the variable additional parts being used only in a specific stage of the study process. The aim of the paper was to work out a model of interdisciplinary measures designed for business administration learning in compliance with the requirements of the curriculum and train the student to be able to make managerial decisions in a modern enterprise exhibiting the features of knowledge organization. The authors have the experience in using a computer business game in the study process (Bagdonas et al., 2010), specifically, for teaching business basics, business computerization, information systems and finance study. This experience suggested complex usage of the on-line business game ‘HARD NUT’ combining it with other sophisticated information communication measures used in the model of business geographic information systems. The business game itself does not have significant geographical information. It is true that the Kotler’s model can be modified to add such information. For example, it is possible to divide the territory into parts (like counties) and to consider each part as having a separate market. Then it would be possible to estimate the effective distribution expenses for each market (affecting the market share)

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given the positions of the distributors. But such changes would make the business game much more complex for the students, as they would have to manage many more variables. For example, if the territories would correspond to each of ten counties, there would have to be 20 numbers representing the market share, instead of just 2 (one for each product). Therefore, the changes of the model itself were ruled out and the natural place for such extension was judged to be the debriefing.

2 Representation of the network of enterprises in the on-line business game With regard to time requirements and references (Bekebrede et al., 2010; Bielecki, 2012; Mockus, 2010; Motzev, 2010; 2012; Targamadze et al., 2010) it was decided to integrate the on-line business game ‘HARD NUT’ (the use of which started in business administration study program at the Faculty of Social Sciences in studying introduction into business) into the module of business geographic systems. It is desired that the prepared teaching aid would be applicable for both traditional and e-learning. Figure 1 represents the conceptual model of the organization of the simulated enterprises incorporating the cluster of production enterprises and traders. At the beginning of the game the students are supposed to play following the conditions of the monopoly, which introduces the conceptual model of simulated organization and the possible connections with other enterprises.

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saved and stored in the server for knowledge acquisition. For that, the students are supposed to know how to connect to the MySQL database through ODBC, to be aware of the DB structure and able to construct informative queries. The gained experience in the data analysis is supposed to help make reasonable decisions in playing under the conditions of competition.

Figure 2 Possible development trends of the basic on-line business game

The students were offered five business game development cases by additionally solving the following problems: selection of advertising by evaluating really offered advertising; the task of the production planning optimization; the task of loan management; business plan development; bankruptcy prediction. ◆◆

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Figure 1 Conceptual model for the organization of the simulated enterprises incorporating the cluster of production enterprises

In analyzing the basic model of the activity of the simulated production enterprise (Fig.2) the students carry out the prepared laboratory work which introduces business basics. Assignments 1-3 are designed for learning economic dependences, and the aim of the fourth test is to learn how to analyze the DB data

MS Excel or any other simple ICT tools are sufficient for the solution of the most of the tasks. The presented model (Fig.1) clearly shows that nearly all participants of the enterprises’ activity process (businesses, traders, customers, suppliers, banks, suppliers of the advertising) can posses the geographical elements. Even though they are not provided in the basic version of the game, the architecture of the business game ‘HARD NUT’ allows the players to use the extensions, especially during the stage of debriefing. Therefore, in Fig.2 the general system is supplemented by the sub-system ‘The analysis by using GIS’. Figure 3 represents the model which exhibits addition of the simulated system by the geographical elements. That is recommended to be performed by the fourth year students attending the subject of business geographical information systems.

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Figure 4 Expansion of the database by the geographic data

Figure 3 The model of organization of activity of the simulated enterprises in analyzing the cluster of production enterprises and traders

Figure 3 shows that the use of GIS can be closely related to debriefings. As the students have to prepare a report, they are asked to use GIS tools for visualization. This transforms the willingness of the students to achieve good results in a game into willingness to learn complex software. In a basic version a short debriefing follows each game period. During this debriefing the instructor explains the students the main factors that have affected the results. Then, after the game is over, there is a longer debriefing. The students have to prepare reports and presentations describing and explaining their decisions and results. Special emphasis is given to visualisation (it is strengthened by deliberatively keeping the game itself text only). In the extended version those visualisations have to take into account presumed geographic positions of the distributors. They are supposed to use specialised GIS software for this visualisation, specifically, ArcGIS desktop and online versions (since the producer of this software has an agreement with the university). The knowledge obtained from the module ‘Information systems and social data analysis’ is fully sufficient for the connection to the business game data base (DB) through ODBC and for its addition by the required geographic elements. Figure 4 presents addition of the relational table (new or corrected tables are in a bold frame).

The students are encouraged to perform a more detailed data analysis by means of the effectively operating visualization aids. Since time has an important significance on making reasonable decisions, it is essential for the business administration study program student to learn how to present the data in such a form which can ensure understanding of the essence of the data presented, estimation of the situation of the enterprise and making rational decisions. The starting form is of great significance. Figure 5 shows the starting form constructed by the students and suggested to be used in the expansion of the game, where, apart from the representation of the calculation of economic figures, visualization of the data by means of geographical information systems (GIS) is presented.

Figure 5 The picture of the starting form created by the students with the possibility to use GIS, showing the groups of buttons for property ratios, solvency ratios, performance indicators and individual buttons for Altman model and GIS

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Figure 6 represents the example of the work performed by the students, where the location of the enterprises is demonstrated according to the data entered into the DB by the players. The financial ratios in their numerical expression and in the form of a diagram are presented on the map created by means of the on-line ArcGIS (http://arcgis.online.com/). The data were calculated using MS Access.

Figure 7 Integration of the business game data into the ArcGIS 10.1 environment.

Figure 8 represents the geographical location of the simulated enterprises as chosen by the players. In selecting the site for the new enterprise, it is essential for the sales predictions and other business needs to get to know the density of the enterprises’ location. Consequently, the inner ring shows the enterprises occurring within the territory of 50 km radius, and the second ring – within the territory of 100 km radius. Figure 6 Location of the simulated enterprises on the map and presentation of the financial figures (assets and liability ratio) within the period of five years.

In studying by the e-learning method it is convenient to use the on-line ArcGIS software, however, its functionality is limited. KTU students enjoy good conditions to implement the academic ArcGIS version in their computers, which have better features than the on-line versions. That package is rather difficult to use for the students, so they find it difficult to choose the appropriate tools. A business game allows them to simulate realistic situations, which helps to acquire the skills of how to make use of the data visualization. Figure 7 shows integration of DB of the computer game ‘HARD NUT’ into the software package ArcGIS 10 Desktop version. On the right side, the tool for making a query is presented, by means of which the data to be represented are selected.

Figure 8 Location of the simulated enterprises on the map by the chosen radius

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The students carry out the analysis of the enterprise’s performance after each simulated fiscal year. After five years of activity, the groups imitating members of the enterprise’s board shall write the report on the enterprise’s performance.

3 Assessment results of using on-line business game and ArcGIS According to the model described in the paper the game was applied for the fourth-year students of Kaunas University of Technology who chose to study Business Administration program. The assessment of the education process was carried out in two ways: according to the assessment of the achieved results by simulating the enterprise’s performance; assessment of the students’ opinion. ◆◆

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In analyzing the database of the business game results, it was found that the organization of a profitable business is not an easy task. Predictably, (as the GIS were mainly used for debriefing) the value of the players’ capital and reserves (CR) was but slightly different both in using the geographic information system and without using it. The surveys performed show that 90% of the students taking part in the surveys were positive about the integration of the business game “HARD NUT” into the academic subject of business geographic systems. That form of studies facilitated awareness of the adaptability of ArcGIS for business needs. According to the students, preparation of the report on the performance of the simulated enterprise had a positive effect on clarity of the material.

4 Conclusions Multifunctional and multidisciplinary usage of the on-line business game has shown its versatility in the educational process. An additional data analysis on the basis of geographical elements creates conditions for making reasonable and substantiated decisions.The students maintain that even though the awareness of the business environment was raised, the relation between different decisions was still hard to understand for some of the students.

Acknowledgement This research is funded by the European Social Fund under the Global Grant measure.

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References Bagdonas, E., Patašienė, I., Patašius, M., & Skvernys, V. (2010). Use of simulation and gaming to enhance entrepreneurship. Electronics and Electrical Engineering. Kaunas: Technologija, 6(102), 155—158. Bagdonas, E., Patašienė, I., Patašius, M., & Zaukas, G. (2012). Extension of Computer Business Game: Connection with Real Market. Bonds and Bridges: Facing the Chalanges of Globalizing World with the Use of Simulation and Gaming. Warsaw, Kozminski University, 77—83. Bekebrede, G., Warmelink, H.J., Bajnath, G. S., & Mayer, I.S. (2010). The Net Generation: Review, Research, Critique. Changing the World throgh Meaningful Play, East Washington University, 107—113. Bielecki, W. T. (2012). Social responsibility of Business Simulation Games. Bonds and Bridges: Facing the Chalanges of Globalizing World with the Use of Simulation and Gaming.Warsaw, Kozminski University, 27—33. Crookall, D. (2010). Serious games, Debriefing, and Simulatio/Gaming as a Discipline. Simulation & Gaming, 41, 898—920. Jucevičius, R., & Ilonienė, I. (2009). Žinių organizacijos kompetencijos: valdymo modelių perspektyva. Economics and Management, 14(2), 778—793. Mockus, J. (2010). E-education Environment for Scientific Collaboration and Graduate Studies: Optimization, Games and markets. E-Education: Science, Study and Business, Technologija, 65—69. Motzev, M. (2010). Intelligent Techniques in Business Games and Simulations – A Hybrid Approach. Changing the World throgh Meaningful Play, East Washington University, 81—86. Motzev, M. (2012). New Product – an integrated Simulation Game in Business Education. Bonds and Bridges: Facing the Chalanges of Globalizing World with the Use of Simulation and Gaming. Warsaw, Kozminski University, 63—75. Skrudupaitė, A., & Jucevičius, R. (2011). Critical Success Factors for the Implementatio of the Synchtonized Production System, Social sciences, 74(4), 16—23. Stankevičė, I., & Jucevičius, G. (2012). Innovation Strategies in Diverse Institutional Settings: Conceptual Linkages and Interactions. Social sciences, 81(3), 65—76. Smaiziene, I., & Jucevicius. R. (2009). Corporate Reputation: Multidisciplinary Richness and Search for a Relevant Definition. Economics and Management, 14(1), 91—101. Targamadzė, V. & Butkutė, V. (2010). Kompiuteriniai tiksliniai žaidimai kaip pedagoginės sistemos kaitos agentas, E-Education: Science, Study and Business, Technologija, 57—63.

Authors/Contact Irena Patasienė, Martynas Patasius, Grazvidas Zaukas Kaunas University of Technology, Lithuania [email protected]

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Business Simulation Vial+ — An Interactive Learning Environment for Developing Management Skills Vitalii Pazdrii, Oleksandr Gryschenko, Petr Banschykov

Abstract In this article we describe the most recent Ukrainian business simulation ViAL+. It is an interactive system, modeling main business processes. The interactive learning environment focuses on the competition between “real” participants in a virtual economy. Keywords business simulations, ViAL+, business game, training, practical skills shaping

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The main goal of the ViAL+ is to create opportunities for acquiring practical skills in dealing with integrated business process management, taking into account the whole chain of production, distribution and sales in a market economy. The online use of ViAL + aims at training bachelors and magister in economics. In addition, we use ViAL+ for organizing business-championship for pupils, and students (in Ukraine and world), and for training young entrepreneurs.

2 Specification of the Design of VIAL+ The most important challenge of our project was modeling the market and creating opportunities for online business competition among players, representing different companies, operating in the same market. The main features of ViAL+ are: Building a realistic model of business processes in a market economy; Constructing realistic mechanics of a production firm in relation to consumer behavior in a competitive market; Enhancing clear understanding about the links between analysis, decision-making, and feedback on results; Participants are free to make super rational or irrational, effective or ineffective decisions; Including in the design are the most advanced ideas of economy science and business practice; Including in the design, real transformation economic (for post-socialistic states of CIS) and market conditions; Taking into account knowledge and experience from key people of leading companies; Taking the milk production and distribution as the referent system for the business simulation; Adaptability of the simulation to other referent systems, implying that all parameters and relationships can be adjusted according to the needs and wishes of clients/customers of ViAL+. Currently, more than 500 parameters can be estimated and tuned to verify the business model; Consulting scientists of the National Academy of Science of Ukraine, Kyiv National Economy University, and practitioners such as, middle and top managers, to provide input to the design of ViAL+; Using real forms of accounts according to Ukrainian legislation, and adjustable for example to Polish and EU legislation; Creating opportunities among the participants for shaping a communication network: a ViAL+ community. ◆◆

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1 Introduction Finding a solution for the problems of practical training in the context of basic education, and deepening the knowledge and skills of professionals is becoming more and more urgent in post-industrial information economies. Creating a business simulation close to real economic processes, including market processes, we distinguished two approaches of practical management skills training: on the job training - learning in real work conditions, and learning through business games. In the first option, real risks and the price of making errors may be very high. The second approach offers a safe learning environment for experimenting with various solutions to management problems. Current advances in information technology enable the development of business simulations close to real situations. Under the auspices of “Vadym Hetman Kyiv National Economic University” and the industrial research-and development centre of The National Academy of Sciences of Ukraine, a group of young scientists and practitioners developed the business simulation ViAL+, which is a large-scale interactive simulation system. ViAL+ creates a realistic virtual business economy and a lively competition between the participants, while pursuing practical solutions to realistic business problems.

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In retrospect, modeling the market was the most important and one of the most difficult tasks to accomplish. Since it is the accuracy, and degree of closeness to real market processes that define the quality of ViAL+. We distinguished three phases while modeling the market (business environment): 1. Identification of factors and instruments that influence the market: the company policy and measures that impact on end-users. During our research we gathered the following key factors that influence the market: volume of sales, price, nomenclature and assortments of company’s products, marketing activities (branding and advertising), long-term market presence, and the sales (commercial, trading) network. 2. Evaluation of the influence of each factor on the market and the competitive strength of the whole company. We evaluated the impact of each factor on the market by identifying its additional growth of the market share, neglecting the influence of the competition. 3. Building a model of the distribution of power between the participating companies, based on their marketing strategies. During each step of play each company develops and implements their particular marketing strategy, which immediately generates their market share.

Figure1 Representation of market share among three competitors

The strength of the competitive position of the company is its ability to both retain and enhance their competitive advantages in a market economy. We defined it as a function of the previous competitive position and the total effects of marketing strategies of the competing firms, during that period. The following system of equations expresses the structure of the market model. For:

We have taken into account two important preconditions at the start of the simulation: 1. The competitors have already divided the market, each of them gaining their market share. Newcomers, entering the market, have not yet acquired a market share. 2. Each of the competing firms takes measures that aim at preserving and (or) increasing their market share. To determine the company’s new market share as a result of the effectiveness of their actions, we based our model on the following game theoretical notions. Figure 1 illustrates the underlying logic for a market in which three companies compete with one another. Figure 1 shows the actual distribution of market shares (KOL, LOM, MOK) between the three companies. Determining the market share, based only on historic and present claims, will not produce accurate results. This is due to the fact that the power of the company, to keep their customers, was not yet taken into account. Therefore, we introduced an additional parameter, called the “strength of the competitive position of the company.

N ― set of companies; ― the market share of company N in period t; ― The market share of company N in period t-1; ― lost market share by N as a result of company j; ― the absolute strength of the competitive position of N.

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For: – marketing claim of company N in period t, that means market share company want to receive in market competition with other companies. This means sum of effects from volume of sales, price, nomenclature and assortments of company’s products, marketing activities (branding and advertising), long-term market presence, and the sales (commercial, trading) network.

3 ViAL+ MODULES ViAL+ contains an administrative and a user’s module. The administrative module The administrative module is the heart of business simulation ViAL+. It plays three roles: 1. Tuning of all parameters of ViAL+ for modeling the market, according to the visions, wishes, and needs of clients. It creates general conditions and many opportunities for modeling, and experimenting with different market conditions, and different types of markets behavior of participants. ViAL+ can reproduce various types of markets ― from perfect competition to monopoly, and oligopoly. 2. Actual modeling of the market. 3. Processing management decisions of the participants and sending them feedback about their performance. The following table summarizes the major management decisions and performance feedback variables, see table 1.

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ving profitability. In the future, we plan to create a model of individual consumers, reacting to and changing the market. It’ll make the business simulation more realistic, offering opportunities to influence the individual consumer. The main task of modeling the market in business simulation is the process of redistributing power between the participating companies, based on their actions to influence the market. During our research, we focused on finding the driving forces and activities that allow companies to maintain and (or) increase their market share. The user module The user module manages the interface between the users and ViAL+ (Figure 2. It allows them to implement the decisions made during the subsequent steps of play, and by doing so it facilitates simulating the functioning of the company. Through the user module ViAL+ realistically reproduces the managing process of running a manufacturing company, starting with product release, and ending with the distribution of goods to different types of market – ranging from a duopoly to monopolistic competition.

Table 1 Typical management decision structure of ViAL+ Management decisions (# of decisions per period)

Performance feedback (output/goal variables)

Production level;

Actual production;

Scheduling of production;

Production costs per unit;

Purchase of raw materials;

Sales;

Maintenance;

Inventories;

Plant capacity;

Turnover;

Selling price;

Total Costs;

Marketing expenditures;

Profits (before and after tax);

Purchasing market surveys;

Market share per product:

Credit applications;

Consumer satisfaction;

R&D expenditures;

Selling price of stock;

Developing the market model was the most difficult task. We have been improving and changing the market model five times to make ViAL+ more realistic, flexible and sensitive to the decisions of the participants. The participants develop a set of measures aimed at gaining the desired market share and impro-

Figure 2 Interface of User Module of business simulation ViAL+

With ViAL+ we followed a discrete time simulation approach, moving forward during steps of play, covering each time a three months period. This business simulation enhances learning - not by pursuing a single and correct solution - but by applying economic logic that corresponds with the situation on virtual market, a situation that is a product of actions previously taken by the participants. We created an interactive learning environment that corresponds well with busi-

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ness management, by including in ViAL+: business economics, rules and procedures compatible with the law, and business logic, compatible with realistic business management decisions. Participation in ViAL+ offers participants the opportunity to gain practical management skills through managing economic processes ‘from the driver’s seat.’ The participants make management decisions that are necessary for starting and continuing the business operation. They make use of theoretical knowledge presented prior to the start of the simulation. The participants: Formulate and realize tactics and strategy plans; Use the standard financial instruments; Determine the nomenclature of production (the product mix); Monitor the production; Expand and modernize the production technology, Recruit & maintain personnel, and schedule their work; Arrange the marketing and sales of the products, using appropriate marketing tools. ◆◆

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Product development: developing and exploring new kinds of products; Controlling: accounting and formation of the company’s balance sheet.

Participation in ViAL+ organizes such as: 1. after registration participant receive at the mail letter with file for run ViAL+; 2. participant must install business-simulation ViAL+ (before download installer from site: kint.com.ua) at his computer; 3. run ViAL+ and make decisions on all department of virtual company – production, marketing and sale, personal, finance, accounting; 4. save decision and send to mail [email protected]; 5. during night work administrative module at the server and formulate new start file for participants.

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Competition in the virtual market motivates the participants to not only search for effective ways of promoting the company products, moreover, it invites them to adjust the production process, to improve the product’s consumer appeal, and optimize production costs

4 User Manual The participants start the business simulation by registering at the site: http://kint. com.ua (Ukrainian) or http://vial-kint.blogspot.com (English). After registration, a company is being allocated to each participant. That company operates in a market economy. One time period in the business simulation corresponds with three virtual calendar months. Upon receiving the user’s manual, the participants have access to the following management options: Arranging the production process; Finance: managing credit and deposit instruments; Allocating the financial budget; Managing the production processes; Personnel management: recruiting, maintaining, and training of staff; Public Relations: managing the product consumer appeal; Marketing: market survey, development of products realization strategy, and tactics; Sales; Improving production efficiency; ◆◆

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During the period of participation in business simulation ViAL+ participants goes through several stages: 1. adaptation to the simulation environment during 3-4 sessions takes place; 2. formulate by participation an integrated vision of the company as a  system, which, simultaneously, consists of interrelated functional units during 8-10 sessions; 3. an understanding of the causeand-effect relations in economic management of the company in a competitive market environment (15-18 sessions); 4. after the 20th session the participant can consciously implement and correct the earlier formed plan of action, he begins to professionally analyze the results; 5. the reinforcement of acquired competences and practical skills is observed after 25 sessions. Also the main part of ViAL+ is rating system, which integrates result of participant’s decisions. Rating include 13 indicators integrated in 4 groups: 1. general indicators of company condition – income, market share, productivity, profitability of company; 2. financial indicators – net cash-flow, liquidity, assets; 3. marketing activity – amount of the contracts, assortments; 4. indicators of inbound condition company -- load of equipment, efficiency of retail space, efficient use of resources.

◆◆

◆◆

◆◆

◆◆

◆◆

Process of formulate end rating indicator include 3 steps: 1. Ranking of participants according to them results – maximum mark for the best result and 1 for the worst result. 2. Ranking mark multiplies by indicator weight. 3. Summarize multiplying indicators and formulate ending mark.

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5 Assessment Quality and efficiency of ViAL+ are ensured b regular modernization according to user’s recommendation. Business simulation ViAL+ has been tested with the participation of more than 500 participants in the format of focus-groups, trainings and practicum during the 2011-2012 years (years of active creation ViAL+). The participants of the testing were participants and teachers of the leading universities of the country, scientists of the National Academy of Sciences of Ukraine, representatives of the real sector of the economy. During 2013-2014 years students of different Ukrainian universities, pupils take part in trainings, tournaments with using ViAL+. Today on the basis of business simulation ViAL+ following activities are held: 1. business-tournament/championship for students in Kharkiv National Economic University; 2. interactive business practice at the Kyiv National Economic University, European University; 3. business-tournament for pupils (14-16 age) “Strategy firm” (organised by Kyiv National Economic University, Company of Intellectual Technology and KPMG; 4. the negotiations about its usage in other 3 Universities of Ukraine. Business simulation ViAL+ ranked first place at competitive projects «Pegasus-2013» in Belgorod, the third place at competitive projects on the Innovative technologies festival in the framework of the II All-Russian festival of science in 2012. Also Company of Intellectual Technology became leader of branch in 2012 (at the rating by The Ukrainian Chamber of Commerce and Industry). Also Kyiv National Economic University with Ontario University (Canada) and Schecin University (Poland) want to organize International business-championship at the base of Business-simulation ViAL+. The main areas of the usage of business simulation ViAL+ are: 1. Conducting of trainings, seminars on the economic processes management of the company at higher educational institutions as well as at training, study centres. 2. Conducting of production practice for participants. 3. Conducting of tournaments both within the higher educational establishment and between the different higher educational establishments in Ukraine and abroad. 4. Conducting corporate trainings for staff development. Learning efficiency of ViAL+ is providing by such factors: 1. Participation in ViAL+ gives an opportunity to get practical management skills of management of economic processes, in the context of individual functio-

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nal services of the company, and of the process of companies management in whole. 2. Participant can make all decision in ViAL+ environment, what he/she want. We create entrance conditions – market, modelling consumer, source of resources, pricing parameters and etc, -- and also create potential ideal functional production system, which work without human factor (all decision realize, equipment forecast work). But the main purpose of participant – build production and marketing system according to his/her knowledge and skills. 3. Trainer can make different learning situation for students. And participant can show competence in practical conditions in very small time and without risk. 4. ViAL+ is bridge between real situation and theoretical knowledge.

6 Comparison between ViAL+ and typical business simulations History of business simulation is very long. Nowadays, there are more hundreds of providing business-simulation. The main analogous to business-simulation are: Corporation plus - from Moscow State University. MV University, is designed mainly for higher education in economics, training and retraining courses management training, as well as - for self persons of different categories. Party controls of virtual enterprise operating in a competitive environment. Game course lasts 6 years with a monthly conditional step. There is an integrated assessment of the effectiveness of management, called rating. A user task - to achieve maximum rating by the end of the course of the game. Users are more than 300 schools and centers, hundreds of individuals. Source: http://www.vkkb.ru. Capsim / Capstone Business Simulation - business simulator of production company, which produces high-tech products. Participants run the company with a turnover of 100 million USD for 5 - 8 years of virtual, under competition with others (4-6) teams (for individual lessons, competing teams can be artificially generated by a computer. Used in 500 universities, business schools in the world on programs like Strategy, Strategic Management, etc. Sources: http://www. capsim.com/. Cesim Business Simulations - Finnish development under the brand Cesim, powerful tool for modeling market with the participation of several companies engaged in producing and selling. The interface is not difficult to master and intuitive to play, but at the same time, the game uses a complex mathematical model of the market environment. Participation takes more than 300 educational institutions in Europe, 100 thousand participants. Source: http://www.cesim.com, http://www.globalchallenge.ru. Global Management Challenge (GMC) - computer simulator of management processes of the company in the context of global competition, during the compe◆◆

◆◆

◆◆

◆◆

486

--



+





+

+

+

+

+/―





+





6

+



+

+

n/a

+

6





+

+

n/a

1

+

2

+



+

+



+



+

+

n/a

+



+

+



+

11

+

18



1

+

30

decisions

Commands

+

1

interface

+

+

Variability of

+

+

unlimited

intelligibility

Commands

+

+

Number of

+

+

3

command

+

no

duration

Commands

indicators

Adjusting of

+

Rating of 13

Language

+

interface

from 2 days

commands

Indicators of

100 (person)

+

victory

practice

Create case

from $56

Competition

3 weeks

Free entrance

More detail of comparison ViAL+ and business-simulation presents at the table 2.

training,

sertification

Width of process

The main key advantages of ViAL+ are: 1. reconstruction of the virtual economic space as close as possible to reality and logic of doing business; 2. no pre-planned development scenarios, as the participants fill their decisions interaction environment, full immersion participant in the business environment; 3. unlimited number of participants unlimited time to make decisions, to Crime and intuitive interface, all causality of decisions; 4. free entry into the penalty area and the possibility of certification of their skills.

2-3 days

Autonomy of start

◆◆

ViAL+

Take part—free,

On-line

◆◆

Businesssimulation

Duration

◆◆

Table 2 Comparison table of ViAL and classical, standard business-simulation

Price, $

◆◆

tition, the team managers have to analyze the company’s management reports and weekly take more than 60 decisions in marketing, finance, production and personnel management. International competition in strategic management takes place in the 38 countries of the world. Source: www.gmc.in.ua. Celemi - Swedish development, family business simulators Celemi. A distinctive feature of CELEMI is the availability of specialized equipment (playing fields, where different methods are presented values, processes, people and money to the company) for wiring rounds, which makes decision-making in the board game. This family of simulators has the ability to “fine tune”. Source: http:// www.celemi.com. TopSim - German family business simulators TopSim. You can customize the model for the market of any goods and services, including job characteristics such as: customer behavior, market structure, company profiles, brand characteristics, etc. Sources: http://www.topsim.com/en. HarvardBusinessPublishing - represents the family of online simulators. Simulations cover the key areas of study: Finance; marketing; service management; of organizational behavior; strategic management. Data system simulators are widely used in training or receiving certain skills in key areas of business. Source: http://www.globalchallenge.ru. Oak Tree - a family business simulators, which are intended for training of students, graduate students and corporate employees the skills of effective business. The source: http://oaktreesim.com, http://www.globalchallenge.ru.

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Аналоги

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Corporation Plus (Корпо рация

Income, ROE, stock price

2-30

плюс)

CESIM

GMC

60 (person)

1200 (command)

3 days, 4 weeks

15 days

year income stockholder

MAX stock price

2-8 (3-8)

5-8 (3-5)

MAX income, CAPSIM

n/a

from 2 days to 6 weeks

+

Commands Computer

+

revenue, market share, stock price

MAX income, CELEMI

n/a

from 1 days

+

Commands

+

market share

Harvard Business

MAX EPS n/a

2 days

--

Commands

--

Publishing

(earning per share)

TOPSIM

n/a

Oak Tree

n/a

2-5 days

+

+

Commands

commands computer

+

MAX income

3

+

+

profitability

1

+

4-5 (3-5)

2-25

Source http://www.globalchallenge.ru/wp-content/uploads/2012/11/Табличка-С-текстом-.jpg

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7 Conclusion The main results of article about business-simulation ViAL+ are: 1. In Ukraine was creating no scenario and complex business-simulation ViAL+, which modeling production company and real competitive environment. The fundament of VAL+ is maximum approaching to real market and situation. 2. We create autonomy real business environment. Because business-simulation ViAL+ can be base for standardization of level economic and manager competences. 3. Business-simulation ViAL+ includes two main parts: user and administration module. User module is modeling production company with 5 departments: production, market and sale, personal, finance, accounting. Admin module is modeling market and consumer behavior, is accessing adjustment of all parameters of ViAL+, registration new market and participants. 4. ViAL+ is adaptive to experimental learning – training, practice for developing management skills. Also ViAL+ will open opportunity to assess of competence level.

References Banschykov P., & Skiteva G. (2009). Forming of system trainings: experience of strategy firm department of Kyv National Economic University (Банщиков П.Г., Скитьова Г.С. Формування системи тренінгів: досвід кафедри стратегії підприємств / П.Г. Банщиков, Г.С. Скитьова // Тренінгові технології як засіб формування знаннєвих та практичних компетенцій: досвід факультетів і кафедр: зб. матеріалів наук.-метод. конф. 3-4 лютого 2009 р.: у 2 т. – Т.1. – К.: КНЕУ, 2009.— c.114—117.) GlobalChallenge, http://www.globalchallenge.ru. Kotler Ph., & Armstrong, G. (2003). Principles of Marketing, 11th edition, 2003 (Котлер Ф., Армстронг Г. Основы маркетинга, 9-е изд.: Пер. с англ.—М.: Издательский дом «Вильямс», 2003.—1200 с.). Kundyscheva E. (2004). Mathematic modeling in the economy, (Кундыщева Е.С. Математическое моделирование в экономике: учеб. Пособие.— М.: Дашков и К○, 2004.—352 с.) Serdjuk V., & Zajukov I. (2007). Modern (Сердюк В. Р., Заюков І. В. Сучасні підходи до професійної підготовки економічно активного населення як складової інноваційного розвитку економіки України: Монографія. – Вінниця: УНІВЕРСУМ-Вінниця, 2007. – 177 с.) Shoptenko V., & Kajsina O. (2008). Experience of using of business-simulation at the integrated educational courses, (Шоптенко В., Кайсина О. Опыт использования бизнес-симуляций в интегрованных образовательных курсах// Менеджер по персоналу.—№3.—2008.—с.32—42.) Stigler J. (1995). Theory of Firms. (Стиглер Дж. Теории фирмы.—СПб.: Экономическая школа, 1995.—245 с.)

Authors/Contact Vitalii Pazdrii, Oleksandr Gryschenko, Petr Banschykov Company of Intellectual Technology (KINT) Kyiv National Economic University, Ukraine [email protected]

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Conceptualizing the Essential Role of Gaming Simulation as a Risk Communication Technique for Enhancing Urban Resilience against Natural Disaster Sarunwit Promsaka Na Sakonnakron; Paola Rizzi

Abstract An emergence of the disaster resilience concept broadens the idea of urban risk management and, at the same time, enhances a theoretical aspect in which we can develop our cities without making it more vulnerable to natural disasters. Nevertheless, this theoretical plausibility is hardly translated into a practical implication for urban planning, as the concept of resilience remains limited to some scholars’ debate. One of substantial factors that limits the understanding of people about disaster risk and resilience is a lack of risk awareness and risk preparedness, which can be solved by restructuring social learning process that enables a process of mutual learning between experts and the public. This study, therefore, focuses on providing insights into the difficulties of disaster risk communication we face, and how gaming simulation can be taken as a communication technique in enhancing social learning, which is regarded as a fundamental step of disaster risk management followed by a mitigation process. The study argues that the gaming simulation can facilitate planners in acquiring risk information from the community, conceiving the multitude of complex urban physical and socio-economic components, and conceptualizing innovative solutions to cope with disaster risks mutually with the public. Keywords gaming simulation, risk communication, social learning, urban resilience

1 Disaster resilience in the modern urban planning While cities around the globe have been developing and transforming their built

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environment and socio-economic characteristics, the consequences of these urban development efforts bring about changes of built and natural environment. Those developments and transformations change the cities from agricultural-based to industrial and commercial-based development in such a way that leads to increased complexities of urban metabolism. Besides, the pressure of capturing globalization stimulates huge investments in the city and creates more dense urbanized areas, especially in the disaster-prone zone. In fact, the vulnerability in terms of environmental changes and natural disasters is not just emerged, but it has been a major threat to the urban fabric of our society since rapid urbanization changed the urban landscapes and socio-economic characteristics (Mitchell, 2010). Dating back to the industrialization era in the 1970s, the capitals of major countries in the world had depended on a large-scale production of middle and heavy industries, which drove the urbanization. Nevertheless, the economic prosperity through the industrialization brought about other negative impacts in where factories were located. The industrial development without proper urban management, such as allowing factories to build in a residential area, led to several urban problems related to the environmental degradation and social inequality. Inevitably, there were considerable side effects on the sanitation service provision with decent housing and the quality of life of the inhabitants. After that, in the late 1970s and 1980s many old industrial cities, especially in England, experienced the urban crisis in terms of accelerating declines in their traditional manufacturing industries (Bramwell & Rawding, 1996), corresponding with a stepping increase in the substantial concern on urban revitalization. As a result, a process of urban revitalization, which aims at restructuring cities’ economy towards services and tourism, has been initiated since the 1980s. Nowadays, even though the tourism contributes to the economic prosperity, the tourist flux and tourism causes a sharp rise in waste production as well as in the demands of urban facility and utility beyond the carrying capacity. Since the man-made and natural disasters tend to be more severe than the past, human beings have been forced to seek for a suitable strategy in which it enables us to protect our lives against the perceived risks, and to respond these risks through detecting vulnerable spatiality, social and economic attributes that can lead to a catastrophe. Such a kind of that strategy has been developed over time, corresponding to the shift of human understanding of the interactive relations between human society and nature (Table 1). After the experiences from a variety of destructive disasters in 1980s, we have been aware that natural disasters are not amenable to technological quick fixes alone. The attention of risk management strategies has increasingly been paid to behavior changes and disaster risk awareness that follow upon the environmental sustainability campaign. The increase of risk awareness of world leaders association has shifted the role of human society in dealing with disaster impacts from re-active to inter-active. Besi-

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des, it has also stimulated human thinking and cognition about social-natural relations. Correspondingly, the risk response approaches have been innovated. This innovative thinking leads to a series of shifts from adaption, via sustainability, to resilience, which is regarded as a core approach defining the way we enhance our capability and aptness to cope with natural disasters. Table 1 The shift of human cognition toward social-natural relations Theme

Pre-1980’s

1980’s

1990’s

Urbanization trend

Industrialization

Garden City

Globalization, Commercialization, and Tourismization

The exist of nature and culture

Culture is nature

Nature is culture

Nature and culture have a reciprocal relationship

Risk response approaches

Adaption

Sustainability

Resilience

Human-environment relationship

Human is re-active to the environment

Human is pro-active to the environment

Human is inter-active with the environment

Human centric perception

Environmental crises hit human

Environmental crises are caused by human

Environmental crises are caused by socio-natural interaction

The perceived risks

Environment is dangerous for human

Human is dangerous for the environment

Neither is dangerous if handled carefully, both if that is not the case

Applied tools and strategies

Apply technofixes

No new technology

Minimalist balanced use of technology

Dynamic perspectives

“Milieu” perspective dominates

“Environment” perspective dominates

Attempts to balance both perspectives

Source: Adapted from Van der Leeuw & Aschan-Leygonie, 2000

2 Conceptualizing a resilience approach against disaster Even the concept of disaster resilience has been proposed since a couple of decades ago, there is still no unique understanding of this term. Its definition depends on how scholars apply the resilience concept to achieve their goals and objectives. Nevertheless, the practical use of this concept somehow shows remarkable insight into its theoretical plausibility and the difficulties that we face in defining this term. Focusing on the theoretical background of the term “resilience”, a concept of resilience is developed from its predecessor term, “vulnerability”. The term vulnerability based on the social sciences was proposed in order to respond to the pure hazard-oriented perception of disaster risk in 1970s (Schneiderbauer & Ehrlich, 2004). After that, this term has increasingly been taken as a starting point for risk reduction programs. For instance, it is heavily promoted in “Hyogo Framework for Action 2005-2015” (UNISDR, United Nations Office for Disaster Risk Reduction, 2007).

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Vulnerability is broadly understood as the degree of or potential for loss, or as a predictive variable that can potentially be affected by external threats (Armas & Gavris, 2013; Bohle, 2001; Cutter, et al., 2008). Nevertheless, the conceptual framework of vulnerability proves its weaknesses, as it partially defines a group of people or systems exposed to risk without concerning the flexibility and adaptability of those to react and respond the external stressors. In fact, it is, undeniably, necessary to underline the distinction between exposures to external threats and the adaptive capability coping with the threats. The concept of vulnerability has, therefore, been developed and brought about a concept of resilience, which does not only focus on potential impacts on a defined system, but also the essential of coping capacities of the system under pressures from the external perturbation. The concept of resilience was originally constructed as a concept referring to a system’s capability to absorb shocks and persist in an equilibrium state that focuses on maintaining the basic function of the ecosystem. Resilience is understood, to some extent, as the opposite of vulnerability as if the flip side of a single coin, while some scholars view the relations between resilience and vulnerability differently. Based on the interdisciplinary approach, resilience and vulnerability can overlap each other as they shares a common ground referring to the susceptibility. Resilience generally refers to the adaptability and capability of the defined system that can resist and recover from changes either in terms of physical, social, or natural environment. However, when urban systems are not resilient, the status of the system does not automatically become vulnerable; its state is in a continuum between resilience and vulnerability in which this sliding state gradually changes into vulnerable. Hence, vulnerability and resilience are not a static state, but they are a dynamic process in which they were misleading in the measurement process that views them as a static state.

3 A social learning process as a tool for enhancing disaster resilience of cities Based on the lens of urban planners, urban resilience to disaster mainly comprises of three adaptive capacities: 1) the stability, 2) the reactive responsibility, and 3) the innovative recoverability. The stability refers to a capability that absorbs stress or destructive forces through resistance or adaptation, whereas the reactive responsibility determines a capability to manage or maintain some essential functions and structures during disastrous events. On the contrary, the term innovative recoverability is used to express complementarily a capability to recover or ‘bounce back’ quickly after disasters. To express how those three cover a great proportion of the different elements of resilience, we divide a city state into pre-, during-, and post-disaster time, and the characteristics of urban resilience can be identified by the overall state of city (Figure 1). However, this state based on a re-

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silience approach may not reflect all practical situations as it merely presents the idea of reconstruction process rather than the restoration process that are more related to the theoretical resilience. The other weak points towards concepts of resilience are not represented through absolute terms, but the representation is simply compared with a status quo level of the defined system’s functionality. Notes 1. Ability to absorb or avoid impacts of hazard events: Enhancing resilience decreases the magnitude of impacts of hazard events on the community. 2. Ability to recover from hazard events quickly: Enhancing resilience accelerates recovery time. 3. Ability to adapt to changing conditions: Enhancing resilience builds the capacity of communities to learn from experience. 4. The threshold state in which a community can qualitatively maintain their basic structures and functions Figure 1 Role of Resilience in Determining the Urban System’s Response to Hazard Source adapted from Twigg, 2007 and UNISDR: United Nations Office for Disaster Risk Reduction, 2007

Thousands of scholars and philosophers have been trying to re-define the concept of resilience and invent a variety of variables to describe an ideal resilient system. This concept is re-defined to amplify the principal capability and adaptability of the system — rather than the qualitative capacity — for processing self-renewal, self-organization, and the innovative development beyond its principle from the ecological discipline. Nowadays, a resilient system is measured by its unique characteristics instead of its dynamic state during the perturbation. To enhance the understanding of the resilience, Cutter and colleagues (2008) shed the light on resilience indicators that involves different aspects in the indicator development; those include ecological, social, economic, institutional, infrastructural, and competent aspects. Within this indicator development, the resilient system is surrounded by various elements and characteristics referring to, for example, the robustness, adaptability, and transformability of the defined system. Through integrating those constituents into a disaster cycle, a model of key dimensions of resilience was framed by Galderisi, Ceudech, Ferrara, & Profice (2012) (Figure 2).

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struction. Whereas urban resilience to natural disaster means that components of urban system — built and natural environment, human capital, and socio-economic activities — are able to withstand disaster impacts without qualitatively losing its basic functionalities and physical structures that are necessary to maintain livelihood of their users. Urban resilience here is the dynamic process that shifts the urban system from vulnerable to resilient, and then advances to innovative urban transformations. Nevertheless, this active movement requires sufficient adaptive capacities and a better social learning process as a set of catalysts to a resilient urban transformation.

Figure 2 The key dimensions of resilience in the disaster cycle Source Galderisi, Ceudech, Ferrara, & Profice, 2012

In sum, the resilience of a defined system is not only the sum of each component, but also a dynamic interaction of individual and collective processes at different levels, which contribute to the adaptability and capability to the system to withstand changes. Hence, components of each realm — such as socio-economic characteristics, built- and natural environment — contribute to the capability of the system to turn negative circumstances to opportunities. This dynamic interaction between the system and changes may eliminate or transform some components of the process in order to maintain the system’s continuity and growth as an entity. This study proposes a conceptual model of urban resilience to guard against disaster risk (Figure 3). Resilience in this model is interpreted as both an outcome and a process of disaster preparedness and recovery. This recovery after disaster should be considered as a restoration process rather than a regular recon-

Figure 3 The conceptual model of urban resilience to disaster Source adapted from Twigg, 2007; U.S. Indian Ocean Tsunami Warning System Program, 2007; Chapin, 2009; and Galderisi et al., 2012

4 Improving a social learning process through utilizing the gaming simulation Under the aforementioned framework of urban resilience to disaster, risk information sharing and transfer has been recognized as one of the crucial problems of the social learning process. Theoretically, disaster risk management can be integrated into the urban planning field for achieving disaster resilience goals depending on how well the risk assessment is conducted by and conveyed to the public. We need to realize that the risk assessment cannot be a standalone tool of disaster risk management, and it is indispensable to take three board actions of risk analysis, communication, and management into account (Bendimerad, 2008). Based on the top-down approach of disaster risk management, a traditional goal of urban risk management aims at producing a hazard map and risk management policies, and after that bringing them into the locality’s consideration. As a

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result, a delicate concept of risk zoning policy has been increasingly considered as the fundamental discipline for urban and infrastructure planning in Europe and North American continents in the mid-nineteenth century. However, the production of those hazard maps and its relevant policies, in many cases, ignores the essentials of public participation and implicit data arisen from the public, which results in increasing risk and vulnerability of the cities. We have experienced from thousands cases which those actual outcomes of risk zoning policies are significantly different from the plans. Besides, in some cases, the vulnerability of cities and people living in those cities is continuously increasing instead of decreasing. Those situations can refer to a breakdown of administrative management or a failure of risk communication between experts and the public. In fact, before a formal risk analysis is initiated, risk information related to both physical attributes and social vulnerability must be obtained from the public, whereas the outcome of risk analysis should also be transferred to the public in the way that can cultivate them the risk awareness. The study proposes, therefore, a new conceptual framework of disaster risk communication, which can contribute to a better result of disaster risk management and enhance the urban resilience. Figure 4 illustrates the role of risk communication as a means of overcoming the main problems of the contradictory risk perception and awareness between the public and risk managers, while retaining the advantages of sophisticated computer-based risk assessment. In order to enhance the public cooperation, results of dynamic modeling of risk assessment should be conveyed effectively to the public in a proper way that can raise public awareness of environmental hazards. Thereby, the disaster risk managers and planners are expected to develop their risk communication skills as well as to invent an innovative risk communication approach, which enables local community members to get involved collectively in risk communication and management processes.

Figure 4 The integration of risk communication with spatial risk management Source adapted from Hatayama, 2007

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Risk communication plays an important role in an interactive exchange of risk information and opinions among risk assessors, risk managers, the public, and other stakeholders (World Health Organization: WHO, 2012). Applicable in the situations where either the qualitative information or precious consideration of hazards is undertaken, risk communication can be used for two different purposes: the data collection and information transfer. It is a useful action to obtain the risk information from different vulnerable groups for the increased effective risk analysis as well as to disseminate risk information among individuals, groups, and institutions in order to educate the public about possible effects of hazards (Ng & Hamby, 1997; Morrow, 2011). Therefore, the formation of risk communication should be taken into consideration as a common action in the disaster risk management. Decision makers have to receive little attention to the paradox in which the intricate risk modeling may provide qualities of risk assessment, but its outcome seems to be incomprehensible to the public (Figure 5). The remarkable issue is how far we can go along with sophisticated risk mapping techniques in visual risk communication, while the risk information and warning can be accessible and simply understandable for them.

Figure 5 the sophistication spectrum of risk mapping techniques to visually model and communicate risk; Source: Neil, n.d.

Among the risk communication techniques in the Figure 5, the simulation is respected as a communication technique, capable to convey a massage that falls in a middle range between the understandable simplicity for the public and the expert-let difficulty. Additionally, this simulation technique can be used as a communication tool of urban planning and design in which it can be transferred from a traditional computerized simulation into the gaming simulation. By this way, a sophisticated simulation that provides a complex context of the reality can be represented coherently by a pleasant and playful game, so-called “gaming simulation”, that offers the players to play and make changes to a mock-up of the reality, in order to broaden and deepen understanding the reality that surrounds them. Besides, the gaming simulation offers representatives of stakeholders the opportunity to meet each other, discuss and exchange their different information

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and opinions on a specific issue, which enable a fruitful communication avoiding a risky judgment on wrong terms. Additionally, the comparison between two different sciences of urban planning and that of gaming simulation can make better understanding on the differences and the overlapping parts between them. The science of urban design and planning deals with analysis and synthesis on the issues related to infrastructural engineering and social construction of the reality, while the science of urban gaming and simulation mainly emphasizes the importance of building metaphor of the reality under a specific purpose to pursue defined goals (Klabbers, 2006). In a process of producing the urban gaming simulation, the planner can take double vital roles as a designer and a facilitator. Those roles can help the planner in addressing questions that fit into the realm of resolving chronic policy problems related to, for example, a policy implementation issue of the difference between the public risk awareness and desirable behaviors. On the other hand, designing an urban gaming simulation and facilitating the play allow the planner to use this mechanism for collectively representing tangible solutions to real-world controversial risk management, which often faces the conflict over the different interests as well as tricky interpersonal and institutional social issues. The gaming simulation is not only the risk communication technique and the problem-solving tool, but it is also considered as a learning technique that enable social learning to be efficient, as an environment that facilitates learning, and as a focus of attention leading to the mutual learning effort. Those three ingredients are necessary for a learning activity (Buckler, 1996). This simulation reconsiders the social learning as a thinking process which people do and realize by themselves, rather than a procedure which is done to people. Through this thinking process, people are motivated to relate what they have learnt to their own experiences in which deliver the benefits of active participation, innovative creativity, continuous improvement, and adaptive transformation to any disasters. In order to capture the urban complexity and diversity integrating with the stepping rate of disaster risks, a regular gaming simulation is, thereby, developed into “Urban Gaming Simulation (UGS)” and “Disaster Imagination Game (DIG)”. To visually illustrate how UGS and DIG can transform today’s individualism risk awareness that is limited to group of experts to the collectivism one, VADDI (Vallo a Dire ai Dinosaur) designed by Rizzi and et al. (2010) can be taken as an example. This game, as a gaming simulation on urban planning and disaster risk management, shows how UGS and DIG work in exchanging information either between experts and the layman or among experts. The game characterizes as a role-playing game giving players a scenario that they were living in coastal regions where are enriched with environment resources such as mountains, forests, rivers, and the suitable land for pastures and cultivations. Players are given roles of government, planners, developers, and citizens who live in one of three

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neighboring cities: a metropolis, a seaside town, and a picturesque mountain village. This game simulates the reality where different stakeholders have different concerns on urban development according to an individual’s role, which possibly bring about the conflict. Additionally, every player is given personal projects to carry out and to make decision under the consensus of community member whom the play lives and works with. During the play, the climate change scenarios — such as urban heat, overwhelming rainfall, summer fires, landslides, and floods will be given as a mark of the seasonal transition, whereas some areas are subject to prolonged periods of drought. Thereby, the players are put into the situation where environmental problems are no longer under control. During the last phase of the game, players will be motivated to think about their risk and city vulnerability, which let them express their ideas and solutions related to the future of regional development concerning on environmental risk. Remarkably, this game simulation can reach its ultimate usefulness when the political advocacy translates the messages from the discussion into risk management projects, strategies and law.

5 Discussion Decision-makers and planners nowadays know well how to apply their computer skills to obtain and analyze the urban physical attributes contributing to disaster risk and vulnerability, but they are rarely capable of bringing the risk analysis to the public consideration. As a result, this phenomenon manifests the failure of risk communication and a methodology used to identify the problems as well as to reveal a complexity of urban system and its social vulnerability. On the other hand, this reminds human beings that the successful efforts to render the adaptive capability to interact with disaster risk is not only limited to reducing the vulnerability of urban systems, but also alleviating the vulnerability of social structures. The idea for risk communication, in the face of disaster, can make the urban planner and risk managers deepen their understanding about the reasons behind people’s actions that either impede or motivate them to perform desirable protective measures corresponding with a risk zoning policy that is enacted. Similarly, improving urban risk communication through applying the gaming simulation provides the urban planners and practitioners a bridge between their viewpoints on urban risk management with the public risk awareness that actually exists. An integration of the gaming simulation and the urban risk management innovates a traditional simulation to a metaphor of complex urban and social systems, which is so-called “urban gaming simulation”. This urban gaming simulation can enable a mutual social learning environment that is regarded as a fundamental principle of enhancing urban resilience against natural disaster.

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References Armas, I., & Gavris, A. (2013). Social vulnerability assessment using spatial multi-criteria analysis (SEVI model) and the Social Vulnerability Index (SoVI model) — a case study for Bucharest, Romania. (A. Steinführer, Ed.) Natural Hazards and Earth System Sciences, 1481–1499. Retrieved from http://www.nat-hazards-earth-syst-sci. net/13/1481/2013/nhess-13-1481-2013.pdf Bendimerad, F. (2008). State of the Practice in Disaster Risk Management: Urban Risk. Earthquake Megacities Initiative. Retrieved November 10, 2012, from PreventionWeb: http://www.preventionweb.net/english/hyogo/gar/ background-papers/documents/Chap5/thematic-progress-reviews/urban-risk/EMI-Urban-DRM-Practice.doc Bohle, H.-G. (2001, February). Vulnerability and criticality: Perspectives from social geography. International Human Dimensions Programme on Global Environmental Change (IHDP). Retrieved from Managing the risks of extreme events and disasters to advance climate chance adatation (SREX): http://ipcc-wg2.gov/njlite_download. php?id=6390 Bramwell, B., & Rawding, L. (1996). Tourism marketing images of industrial cities. Annals of Tourism Research, 23(1), 201—221. Retrieved from http://www.sciencedirect.com/science/article/pii/0160738395000615 Buckler, B. (1996). A learning process model to achieve continuos improvement and innovation. The Learning Organization, 31—39. Chapin, T. (2009). Concept and strategies to address sustainability in a changing world. Alaska, United State: Living on Earth: EPSCoR. Retrieved from www.alaska.edu/epscor/living-on-earth/Terry-Chapin.ppt Cutter, S. L., Barnes, L., Berry, M., Burton, C., Evans, E., Tate, E., & Webb, J. (2008). A place-based model for understanding community resilience to natural disasters. Global Environmental Change: Local evidence on vulnerabilities and adaptations to global environmental change, 18(4), 598—606. Galderisi, A., Ceudech, A., Ferrara, F. F., & Profice, A. S. (2012). Del. 2.2: Integration of different vulnerabilities vs. natural and na-tech hazards. ENSURE : Enhancing resilience of communities and territories facing natural and na-tech hazards. Retrieved from http://www.ensureproject.eu/ENSURE_Del2.1.1.pdf Hatayama, M. (2007, September). Integrated Database Management Method for Disaster Risk Governance. Retrieved November 13, 2012, from International Institute for Applied Systems Analysis (IIASA): http://webarchive.iiasa. ac.at/Research/RAV/conf/IDRiM07/Papers/Hatayama.pdf Klabbers, J. H. (2006). A framework for artifact assessment and theory testing. Simulation & Gaming, 155—172. Mitchell, D. (2010, October). educing Vulnerability to Natural Disasters in the Asia Pacific through Improved Land Administration and Management. Retrieved April 14, 2012, from FIG: Federation Internationale des Geometres: http://www.fig.net/pub/monthly_articles/october_2010/october_2010_mitchell.html Morrow, B. (2011). Risk behevior and risk communication: Synthesis and expert interviews. Silver Spring: the Food and Drug Administration (FDA). Neil, M. (n.d.). Using Risk Maps to Visually Model and Communicate Risk. Using Risk Maps to Visually Model and Communicate Risk. London, Queen Mary, United Kingdom. Retrieved October 25, 2013, from http://www. agenarisk.com/resources/Using_Risk_Maps.pdf Ng, K., & Hamby, D. (1997). Fundamentals for establishing a risk communication program. Health Physics(73), 473—482. Rizzi, P. (2010). VADDI: Kit didattico di giocosimulazione sui cambiamenti climatici. Rome: ISPRA. Schneiderbauer, S., & Ehrlich, D. (2004). Risk, Hazard and People’s Vulnerability to Natural Hazards: a Review of Definitions, Concepts and Data. Brussels: Office for Official Publication of the European Communities. Twigg, J. (2007). Characteristics of a disaster-resilient community: a guidance note, version 1. the DFID Disaster Risk Reduction Interagency Coordination Group. Retrieved from http://practicalaction.org/docs/ia1/community characteristics-en-lowres.pdf U.S. Indian Ocean Tsunami Warning System Program. (2007). How Resilient Is Your Coastal Community?: A Guide for Evaluating Coastal Community Resilience to Tsunamis and Other Hazards. Bangkok, Thailand: USAID: the United States Agency for International Development. Retrieved from http://www.preventionweb.net/files/2389_CCR Guidelowresatiq.pdf UNISDR: United Nations Office for Disaster Risk Reduction. (2007). Hyogo Framework for Action 2005-2015: Building the resilience of nations and communities to disasters. ISRD: International Strategy for Disaster Reduction. Retrieved from http://www.unisdr.org/files/1037_hyogoframeworkforactionenglish.pdf Van der Leeuw , S., & Aschan-Leygonie, C. (2000). A Long-Term Perspective on Resilience in Socio-Natural Systems. Santa Fe Institute. Retrieved from http://samoa.santafe.edu/media/workingpapers/01-08-042.pdf World Health Organization: WHO. (2012, November 13). Definitions of risk analysis terms related to food safety. Retrieved from World Health Organization: http://www.who.int/foodsafety/publications/micro/riskanalysis_definitions/en/

Author/Contact Sarunwit Promsaka Na Sakonnakron, Paola Rizzi Department of Architecture, Design and Urban Planning, University of Sassari, Italy [email protected]; [email protected]

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The Windmill Product Life Cycle Game Rosa Garcia Sanchez, Jannicke Baalsrud Hauge, Hendrik Kraume

Abstract The growing consumption of limited reserves of fossil fuels and their impact to the environment have raised global interest in renewable energy. Proper knowledge of renewable energy production and product life cycle management is lacking in among large groups of the society. Even though several educational and vocational courses have been developed, mostly as a part of engineering education or within vocational training aiming at educating specialists, there is a general need within other branches to understand the main specificities and requirements of the wind energy sector, both regarding off-shore and on-shore installations as well as requirements on products in use. It is known that serious games can be used for awareness raising, thus in this article we first discuss the approach using Serious Games for on-line training, before we present a concept for explaining the complete life cycle of a windmill as work in progress. The game is built by using an engine, e-Adventure and has been prototypical implemented and tested. Keywords wind energy sector, product life cycle, serious games for awareness raising, learning experience, game based learning

1 Introduction The Renewable Energy Directive (2009/28/EC) [1] has contributed to high growth within wind energy sector [2]. The directive implies that minimum 20% of energy consumption should come from renewable sources by 2020. Consequently, there is a need to invest more in renewable energies, like windmills, hydropower stations, bio and solar power station etc. Considering the wind energy sector in Europe, most installations are on-shore with 101 GW of installed capacity at the end of 2012 [3], but with a clear trend toward more offshore wind farms. For 2012, the off-shore capacity was increased by 5 GW [4] and 14 wind farms are under construction increasing the capacity with 3,326 MW in to the grid [5]. On-shore and off-shore installations of windmills have to face several challenges throughout the whole life cycle. Some of these challenges are related to the product itself- i.e. construction, material usage and environmental impact during operation but also in

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the recycling- others are more related to the handling –production and installation of rotor blades, maintenance activities, etc- and also logistics, like transport of large parts. The wind energy sector needs to transport over 60 m long rotor blades by truck and/or vessels [6], working under specific weather conditions and related safety and security issues [7] as well as solve problems related to the foundation of off-shore windmills. The challenges described above shows complexity of the topic and that several persons with different background and skills are involved in the production, installation, maintenance and recycling of on/off-shore windmills. The remote locations put new requirements on the competencies and skills of those being involved [8, 9] comprising the whole life cycle from a technical point of view. All these issues require that all involved stakeholders have an overview of all processes in the product life cycle.

2 Rationale and educational needs As stated in the introduction the developing, manufacturing, implementation, operation, maintenance and recycling processes of windmills are complex processes requiring stakeholders with specific knowledge [8]. Sustainable production in complex, dynamic environment puts high requirements on the workforce that operate [10, 11], as they have to be able to work in a changing system [12]. The Accreditation Board for Engineering and Technology (ABET) has defined 11 competencies that an engineer should have leaving university [13] for instance like applying knowledge of mathematics, science and engineering, identify and solve engineering problems, applying advance engineering tools. The main objective of universities is to foster these competencies among their engineering students. However, there are some studies showing that they have not managed so well so far [14,15,16]. It might be because a passive learning process, fostered by traditional classes, is not supporting the development of the required skills. In 2012, we carried out an analysis of which courses are relevant in the area in Germany and Spain. The analysis showed rather theoretical topics, but as mentioned above, there is a need for practical skills [17], and this could not be found [8]. Consequently, we need to look at methods that allow more active experience. Game-based learning (GBL) [18, 19, 20] and serious gaming could provide a suitable environment.

3 Syllabus and course design As described in the introduction, the course is intended to be used for awareness raising and mediation of basic knowledge on wind energy and product life cycle management. The target groups are different types of engineers, students coming from subjects like operational research and supply chain management, as well as

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young professionals coming from different areas, but working in the area of wind energy. The game may also be used for awareness raising of general public. Figure 1 shows a complete life cycle of a wind mill. This is also the main subject of the course. This is a basic course that aims at providing to stakeholders working in either in any area related to development, construction, production, operation, maintenance and recycling some basic knowledge, both from technical point of view as well as from handling and logistics point of view. It is expected that the students have basic skills in supply chain management.

Figure 1 Product life cycle of Wind mills

The course “Windmill Supply Chain” has a modular structure. The modules are divided according to the part of the product life cycle as shown in figure 1. Thus each participant can select the course element fitting his needs and his competence. In the module “research and development”, the aim is to get to know the current state of the art, the methodology as well as to experience the largest challenges regarding material selection, production approach, etc, all from a holistic product life cycle, i.e., the student will look at how it is possible to reuse material, what they have to think of in the beginning of life. In this course, the learner will also learn about the component of a windmill as shown in figure 2. In the module “production”, the focus is on current production process, the challenges and specific attention will be paid to material science and resource consumption- where do they normally see problems in with the material, in order to reduce the risk of material failure as well as material waste. In the module “logistics” the learners will experience how the different parts have to be transported from suppliers to installation field, evaluate when it is the best period of the year to install windmills and experience the difficult con-

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ditions, but also the need of proper techniques that support the use and handling of big components, the impact of needing to use infrastructure with specific care and also typical supply chain management topics. In the module “erection”, the learners will look at the installation of rotor blades that until now has been done hoisting the complete rotor as a unit or to affix two of the rotor blades to the hub on land (so-called “bunny ears”) and they install the third blade at sea. Currently, manufacturers are working on a third single blade installation. This new technique is saving space at harbour in comparison with the space needed to assemble and store the rotor stars from the old technique. In the same way there is a saving of space in vessels, and even the installation is faster as Lutz Wiese from Vattenfall´s comment [21]. In this module, they will also learn about the maintenance of windmills at a general level. Finally, due to the fact that wind energy is a young industrial sector, today the reuse of parts from old windmills is still a problem, since the windmill were not designed to reuse or recycle. However, this is relevant in the future and will thus be considered in this course; the learners will analyse how this issue has to be considerate already at the design level. The “end-of-life” module will be connected to the first module, also supporting the learners to remember what they learned early in the course.

Figure 2 Windmill components

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4 Game description for Product Life Cycle Management of Windmills The Windmill Product Life Cycle Game is a game designed for supporting the learning objectives described in the syllabus description above. It is developed using the open source e-Adventure editor tool. During game play, the player will discover different inbuilt information on PLM which he needs to apply to perform and to solve the task. This supports the knowledge acquisition process.The game is a single player game lasting around 30 min, depending on the computer and game skills of the player. A player plays through a complete life cycle of a windmill. Each level represents one phase of the life cycle and thus the story line is kept throughout the game. Each level consists of several mini games where the player gets information or gadgets. The mini games are for instance a wind energy quiz integrated in the research and development level or to match properly the materials used in each component of the windmill that is installed and under operation. These mini games are sometimes clearly specified by the story line, like for instance in the production level when the manager of the rotor blade manufacture invites the player to visit the factory. In other cases the player needs to explore the game environment, like the case of the research and development level where the player needs to check the computer and the pin board hanging in the office. The content provided in the game is visual and interactive content for two main reasons; to provide insights into the real processes and appearance of product life cycle of windmills as well as to rouse students’ interest into product life cycle management and wind energy. Automatic feedback is provided in each of the mini games along the game. The feedback is instantaneous and it is showing if the player took the right or wrong decision as well as that the mini game or level was successfully completed. The game have been developed using the e-Adventure platform. The e-Adventure platform is developed by the e-UCM e-learning research group at Universidad Complutense de Madrid [22, 23] within a project with the same name. The concept is layered, so that content and game mechanics are divided. It has a game engine and uses XML Markup. It offers a graphical editoring tool, thus it is not necessary that the author has any programming skills, he create the game directly using this interface. Figure 3 shows the editors interface, in which an author will implement his scenario.

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Material needs in Windmills Production steps for rotor blades Waste produced on the production Disposal possibilities for production waste

The planned playing time was 30 minutes and the aim of the game was that the students should discover the information hidden on the different topics within the mini games. In order to get a first impression of the usability and the user acceptance of the game, a post-test in form of a questionnaire with 20 questions was completed by the students. The outcome will be used to improve the game play regarding motivation, engagement and learning outcome of the game. In addition to the self assessment, we also collected results directly from the game play using the inbuilt performance measures and possibilities for trace the user’s interaction as well as observing the players during game play.

Figure 3 Editors interface

5 Experimental set-up A first development of the game with basic content on product life cycle management for windmills is developed. The levels developed have been prioritizing by the availability of visual material, the possibilities of the e-Adventure engine for interaction and the resources available for development. The course and the game have been tested in the course “Material Sustainability of Products in Wind Energy” of International Summer University for Women in Engineering in Bremen during August 2013. The sample group comprised 11 female students and professionals, both undergraduate and post graduates, coming from different subjects like industrial engineering, environmental engineering, economics and politics. The age of the students ranged from 20 and 50 years old. The main motivation for the participants was to learn about product life cycle management, sustainability of products and renewable energies. We used a blended learning concept, starting with a general introduction to the course. The participants played the game introducing them to the topics mentioned in the curriculum (see section 2), product life cycle management and sustainability of products, during the course. The topics addressed in the Windmill Product Life Cycle Game during the game play are as follows: Product life cycle Management Product Life cycle Phases Renewable energies: Wind energy Sustainability of products ◆◆

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6 Discussion of preliminary results The preliminary results are from the e-Adventure editor tool, the feedback provided by the students to the game as well as the observations made while the students were playing. Based on the results of the first test, table 1 shows the pro and contra arguments for using the e-Adventure editor tool after the first experience. Table 1 arguments for using the e-Adventure editor after the first experience Pro

Contra

Big amount of Pictures and facts information in short time

Difficulty of incorporation of video

Platform compatibility (editor tools run on Win & Mac, games can be played online)

Movements and motions are limited, old-fashioned appearance compared to modern game standards

No programming language required

Designing skills required

Shorter programming time than with normal programming languages

Restricted game elements and features to be integrated

Unequivocal feedback is provided

Difficulty to provide score to players

One of the first observations was that two of the players completed the whole game within 10 minutes. These players answered that they played computer games frequently and had high ICT skills, where as we observed that a less experienced player used 50 minutes to finish the game. She also needed support and guidance during game play. A second observation was that some players didn´t complete all mini games before reaching the end of the game. That was possible due to the lack of restriction to advance from level to level, so as long as one mini game was success-

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fully completed some players thought that the level also was completed and they did not explore further in that level. The feedback from the students also indicated that more fun and useless objects would have improved the motivation and engagement within the game and thus their interest to explore and discover the entire game environment. The lessons learned from the first test of the Windmill Product Life Cycle Game can be summarized: The duration of the game play is depending of the ICT skills of the player. More interactive content is required. More game connection between phases is asked. Motivational and engagement features are desired by players, even when they have nothing to do with the topic addressed. ◆◆

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Acknowledgement The research reported in this paper has been undertaken within the GALA project, which is funded by the European Community under the Seventh Framework Programme (Grant Agreement FP7-ICT-258169). We the authors of the paper wish to acknowledge the Commission for their support. Furthermore, we wish to thank Pablo Moreno-Ger, Baltasar Fernández-Manjón, Javier Torrente, Ángel del Blanco and Iván Martínez-Ortiz, for their valuable work and contributions to this paper by supporting us on using e-Adventure.

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7 Conclusion and next step Based on the pre-liminary test results the following changes were implemented in the game: Improvement of the warm-up provided by the game in order to make more understandable and intuitive the use of all interaction possibilities during the game play. Inclusion of fun elements like a cactus in the office level that hurt the player when he is touching it, further motivational elements will be integrated in other levels. Incorporation of gadgets along the game that can and should be taken by the player in one phase and delivered in another phase to continue the game play, otherwise the player need to go back to earlier phases to collect the gadgets. The acquisition of gadgets ensures that the player has discovered the game environment entirely at the end of the game. More interactive content was included on the research and development level and in the production level. ◆◆

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All changes have been integrated in the Windmill Product Life Cycle Game but have not been tested yet. New tests will be carried out on May 16, with high school students as test-candidates. This group is more homogenous than the previous one, and the main focus will be to look at the knowledge acquisition as well as to get more feedback on user acceptance and usability for this user group. They are digital natives and their feedback will support our continuous improvement activities on the game. The feedback from different stakeholder groups and different ages is required, since the game want to be also used for general public in awareness raising on product life cycle management and sustainability of products using the example of the renewable energy of wind energy.

References / Endnotes 1. GWEC. (2011) http://www.gwec.net/index.php?id=127 accessed 14 April 2011 2. REN21(2011) Renewables 2011 Global Status Report. Paris: REN21 Secretariat 3. EWEA Wind in Power http://www.ewea.org/fileadmin/files/library/publications/statistics/Wind_in_power_annual_ statistics_2012.pdf accessed 04 July 2013 4. EWEA The European off-shore wind industry: key trends and statistics 2010 http://www.ewea.org/fileadmin/ ewea_documents/documents/publications/statistics/EWEA_OffshoreStatistics_2010.pdf accessed 23 May 2013 5. EWEA The European off-shore wind industry: key trends and statistics 2012 http://www.ewea.org/fileadmin/files/library/ publications/statistics/European_offshore_statistics_2012.pdf accessed 23 May 2013 6. Garus, K. (2013) Gamesa Advances Offshore Project. http://www.sunwindenergy.com/news/gamesa-advances-offshore project accessed 23 May 2013 7. Iken, J. (2012). Weak point. Sun&Wind Energy: Offshore Wind Industry (02). 8. eliceo.com. (2012). http://www.eliceo.com/proyectos/formacion-en-energia-eolica-una-formacion-con-futuro.html accessed May 2012 9. Baalsrud Hauge, J., & García Sánchez, R. (2012). Supporting on-line training of engineers in the wind energy sector by using games, In Hoeborn, G. (Eds.), Proceedings of the 16th IFIP WG 5.7, Workshop on Experimental Interactive Learning in Industrial Management, Wuppertal, S. 27-36, 3—5 Juni 2012 10. Baalsrud Hauge, J., Pourabdollahian B., & Riedel J. (2012). The Use of Serious Games in the Education of Engineers, International Conference in Advance Production Management System, Greece, Rhodes, 24—26 September, 2012. 11. Beverly, J, D. (2005). Reinventing Manufacturing Engineering: Refocusing and Exploring Future Opportunities for Students, Proceeding of American Society for Engineering Education Conference, Session 1163. 12. O’Sullivan, B. Rolstadås, A., & Filos E. (2011). Global education in manufacturing strategy”, Intellectual Manufacturing, 22: 663—674. 13. ABET Engineering Criteria Program Educational Outcomes http://www.foundationcoalition.org/home/keycomponents/ assessment_eval/ec_outcomes_summaries.html accessed 4 July 2013 14. Kerns, S.E., Miller, R.K., & Kerns, D.V. (2005) Designing from a blank slate: the development of the initial Olin college curriculum, in Educating the Engineer of 2020:Adapting Engineering Education to the new century, http://www.nap.edu/catalog/11338.html, accessed 20.12.2012 15. Cheville A., & Bunting. C. (2011). Engineering Students for 21st Century: Student Development Through the Curriculum, Journal of Advance in Engineering Education, Summer. 16. Beyerlein, D.D., Thompson, S., Gentili, P. & McKenzie, L. (2003). How Universal are Capstone Design Course Outcomes, Proceeding of American Society for Engineering Education Conference, Session 2425. 17. RTVE (2012). A la carta Tv y Radio http://www.rtve.es/alacarta/audios/uned/uned-necesidades-iniciativas-formacion energia-eolica-22-02-11/1029953/accessed March 2012 18. Ebner, M., & Holzinger, A. (2007). Successful implementation of user-centered game based learning in higher education: An example from civil engineering. Computers & Education, 49 (3), 873—890. 19. Gee, J. P. (2003). What video games have to teach us about learning and literacy. New York: Palgrave Macmillan 20. P rensky, M. (2003). Digital game-based learning, ACM Computers in Entertainment, 1, 1. 21. T homas, T. (2012). ADIEU rotor star. Sun & Wind Energy: Offshore Wind Industry, Issue 2012, 32—35. 22. Torrente, J., del Blanco, A., Marchiori, E.J., Moreno-Ger, P., & Fernández-Manjón, B. (2010). : Introducing Educational Games in the Learning Process. Proceedings of the IEEE EDUCON Conference pp. 1121—1126. 23. Moreno-Ger, P., Burgos, D., Martínez-Ortiz, I., Sierra, J.L., Fernández-Manjón, B. (2008). Educational Game Design for Online Education. Computers in Human Behavior 24(6), 2530—2540.

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Authors/Contact Rosa Garcia Sanchez, Jannicke Baalsrud Hauge BIBA – Bremer Institut für Produktion und Logistik GmbH, Bremen, Germany [email protected] Hendrik Kraume University of Bremen, Germany [email protected]

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Business Games — An analysis of Growth in the Knowledge of Business Administration Skills in Non Business Administrators Simone Six

Abstract In today’s professions, business administration skills and the ability to think and act with an entrepreneur’s mind are attributes that are essential not just for business administrators. Business simulation games which OTH Regensburg can offer to non-business students as well as to students of business subjects seem to be effective tools for imparting specialist skills, i.e. for business empowerment and for developing entrepreneurial thought and action. As part of this work, business studies teach an understanding of concepts of business administration, while ‘entrepreneurial thought and action’ is more concerned with business administration contexts. The extent to which this applies has been examined as part of an empirical study at OTH Regensburg. The object of this study are students of subjects other than business administration, i.e. engineering and the social sciences, computer science or architecture. The aim of this empirical study is to ascertain the growth in specialist knowledge gained by taking part in business games. The quantitative part of the study is based on a comparison of test results before and after the business game course. The study is not concerned with comparisons between business simulation games and other course formats such as lectures. The study’s qualitative part consists of interviews with the gamers and is used as an aid to interpreting the quantitative results. Possible approaches to optimising these gaming courses are then developed from the results of data analysis. The study is only concerned with subject-related skills and disregards other skill areas such as social or method skills. Keywords business simulation game, study, business administration

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1 Empirical study method 1.1 Target group of the empirical study The target group of the empirical study are students at OTH Regensburg who attended the “Business Game” course during the survey period (23 July to 12 December 2012) and who were not pursuing a course involving any kind of business studies during this time. The empirical study was conducted in six course formats and eight courses spread across seven faculties and one organisation. The students were split into three courses owing to the large number of participants from the Faculty of Microsystems Technology.

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Statistical data Questions about knowledge of business administration Questions about entrepreneurial thought and action

The statistical data comprise nine personal statements and two feedback questions about the course. The personal statements include questions about the faculties to which the participants belong, their work experience and their existing theoretical knowledge of business management. These statements are not required in the exit test. The feedback questions appear in both tests and are designed to gauge whether the participants’ expectations of the course were satisfied. The ten specialist questions about business administration and on entrepreneurial thought and action are the same in both the entry and the exit test, and relate to all areas of business administration such as Purchasing, Human Resources, Sales and Accounting. The answers to these questions are conveyed through teaching modules in the business simulation game session and are experienced during the course of the session. A specialist question consists of four multiple choice options, with more than one answer being possible, i.e. a question can have between one and four correct answers. The quality of the questionnaire was assessed in a pretest which resulted in its form being revised. The face-to-face distribution of the questionnaire at the gaming courses ensured a 100% return rate, allowed answers to any queries which participants put, and was implemented with a minimum of technical complexity. As the following table shows, a total of 125 students (population) took part in the study, the same as the total number of participants at the courses:

Course formats offered in each faculty (source: internal graphic)

The empirical study conducted with the stated target group involved both quantitative and qualitative data collection. 1.2 Quantitative data collection The purpose of quantitative data collection is to determine the learning success (knowledge gain) achieved by the target group through business simulation gaming. The participant’s knowledge is surveyed and compared using questionnaires both before the gaming course and after. To provide an individual comparison while ensuring the anonymity of the survey, participants were required in both tests to enter a personalised password in the form of a five-letter sequence. Beside the password, the standardised three-page questionnaire comprises the following three sections:

Figure 2: Participant numbers per faculty und course format (source: internal graphic)

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Question What were the challenges in the business game? What advantages does the game offer compared with other teaching methods? What disadvantages does the game have compared with other teaching methods? Would you recommend simulation gaming to your fellow students?

Intention u

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What ranking does the team achieve in the game?

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To identify analogies with the results of the quantitative data collection Rating of the business simulation game as a teaching method Deriving strategies for optimisation in practical usage Determining the attitude to the game Assessing the meaningfulness of the game Identifying synergies for meeting expectations (queried in the quantitative data collection) Finding links between the team‹s result and statements about the above interview questions

Data gathering Programme items of a gaming course

Participants depart

Announcement of results

Exit test

Class test

Presentation

Interview Creating the final presentation

Simulation of individual periods in combination with teaching modules

Introduction to competition

“Financing” module

Creating the business plan

Presentation of the business plan tool

Team creation

Introductory presentation

Entry test

1.3 Qualitative data collection As well as quantitative data collection, a qualitative data collection exercise was carried out using a guided interview. The main purpose of this interview was to provide support for interpreting the results of the qualitative study and to develop strategies for optimising the business gaming course for practical usage. As well as a discussion opener and closer, the guided interview consists of five central questions which pursue the following intentions:

1.4 Time of data collection

Comprehension test

The number of returned questionnaires (entry and exit tests) was not 250 but only 240, as five exit tests could not be matched with an entry test and five entry tests could not be matched with an exit test. This is due to the absence of students, e.g. through lateness on the first day or sickness at the time of the exit test. The ten unidentifiable questionnaires were excluded from the data analysis. In a further entry test and a further exit test the response rate to the questions was less than 80% (The minimum response ratio was defined by the author), i.e. fewer than 16 of the 20 questions were answered. These four questionnaires are also excluded from the data analysis. The data analysis is therefore based on 226 questionnaires completed by 113 students (random sample).

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Welcome to participants

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Gaming course agenda (not to scale)

Assessments as required Figure 4

Time of data collection (source: internal graphic)

An average of four teams competed in the eight courses, resulting in 32 interviews: Course format

interviews

Part-time course in “Microsystems Technology”

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Elective module for the Master in Management and Communications at the Centre for Continuing Education and Knowledge Management

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Specialist elective module for the course in “Industrial Design”

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Specialist elective module for the course in “Social Work”

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Part of the general sciences option module “Business Thinking and Acting”

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General sciences option module “Mixed Leadership”

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Intention of the guided interview questions (source: internal graphic)

The last lead question about the ranking in the game was not put to the students but to their teacher, as the students were not aware of the result of the game at the time of qualitative data collection. The interviews were conducted personally (face-to-face) by the author so as to perceive nonverbal as well as verbal communication signals put out by the interviewee and to respond to these accordingly. The individual teams were interviewed while the final presentation was being prepared so as not to delay simulated game course by the process of qualitative data collection. At this time, experience with the gaming process was collected and the participants were as yet uninfluenced by the final results:

Figure 5

Number of interviews conducted (source: internal graphic)

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1.5 Data preprocessing Before they could be analysed, the data collected in the quantitative and qualitative surveys had to be preprocessed. Preprocessing qualitative data The responses given by the individual groups to the interview questions were noted and clustered accordingly. This made it possible to identify predominant as well as controversial views of the students and to incorporate them in the data analysis. Preprocessing quantitative data The purpose of evaluating the quantitative data is to determine the knowledge gain (learning success) of the students as measured by different criteria. The knowledge gain is shown by the difference in points gained in the entry and exit tests.

x 100 / Maximum possible score. The absolute knowledge gain is the sum of the attainable points in the exit test less the sum of the points obtained in the entry test. The values used to create the total depend on the assessment criterion. For example, if we wish to determine the knowledge gained by students who have career experience, then only the points obtained by those experienced students will be used. The maximum possible score for question-specific assessments is a function of the attainable score per question or question block. With the other assessments, the maximum possible score is obtained by multiplying the number of students who represent the object of the study by the total score that can be attained. The preprocessed data form the basis for the data analysis.

The outcome of the assessment depends on where the crosses are placed, with each student being awarded one point for each box correctly crossed. A penalty rule was used to discourage guessing on the part of students, i.e. a point was deducted for each incorrectly placed cross. Negative scores are not possible under German higher education laws, i.e. the attainable score for a single question and for the whole test must be between 0 and the maximum score (see Figure 15), so if a student places more incorrect than correct crosses he gets 0 points. Boxes that are not crossed – whether in error or correctly – are ignored, i.e. awarded 0 points (see Figure 14):

2 Results and Discussion 2.1 Data analysis The data analysis which is broadly based on the questionnaire analysis can be divided into three main categories and yielded the following results:

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Figure 6

Points awarded in the entry and exit test (source: internal graphic)

Figure 7

Points awarded for negative total points (source: internal graphic)

The maximum possible score on a questionnaire is 36 points, with 19 points available for questions on business administration knowledge, and 17 points for questions about entrepreneurial thought and action. The knowledge gain – the primary object of the data analysis – is presented as a weighted mean and determined as follows: Absolute knowledge gain

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Data analysis / data results (source: internal graphic)

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2.2 Weaknesses and ideas for optimisation From the results of the data analysis and the findings of the interviews we can identify the following weaknesses and suggest ideas for optimisation:

Method

Description

Brainstorming/ Knowledge pool

Ideas which students call out are added around a core term/issue which is shown in the centre of the board. How the ideas are arranged is of secondary importance.

Buzz group

The issue is first discussed with one’s immediate neighbour. Several groups can (should) ultimately present their findings to the plenum.

Think-Pair-Share

Phase 1: Each student thinks about the given topic on his/her own. Phase 2: The answers are exchanged in pairs between the students. Phase 3: The answers of the pairs of students are compared with another student pair.

Inside / outside circle

Two rows of chairs are lined up opposite one another, with one row for the listeners and the other row for the speakers. The speakers tell their immediate listener (the person sitting opposite) everything they can think of about a topic set them by the teacher. The topics vary from speaker to speaker. The listener notes down what the speaker says. After a certain time each speaker moves on a chair so each one has a new interlocutor. At the end of the course their findings are collated.

Info market

Students work in groups to generate ideas which they present on posters or pin boards. When they are ready, one half of each group (= the explainers) stays at the board while the other half (= the wanderers) moves clockwise on to another group, i.e. the explainers of one group are joined by the wanderers of another group. The explainers present their ideas to the wanderers, discuss the results and note down any additional suggestions made by the wanderers. After a certain time all the wanderers move on to the next group. Once the wanderers are back with their team, they switch roles, i.e. the wanderers are now the explainers and the team members who were the explainers move on to the next group.

Figure 10

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Figure 9

Weaknesses and ideas for optimisation (source: internal graphic)

The analysis of specific questions revealed knowledge deficits in business administration skills. At the same time, the students also appear to have difficulty understanding the flow of values within the company. The following measures will help close these knowledge gaps and optimise the simulation game course: Teaching modules Students like simulation games for their practical, clear presentation and because they allow active participation in the course. This must be implemented both in the didactic design of the teaching modules and in their content: Didactic methods in teaching modules ◆◆

Active involvement of the students in the teaching modules leads to an increase in attentiveness and knowledge. Use of the following didactic methods (among others) is advisable in order to achieve this end:

Didactic methods (source: internal graphic)

Providing a business tuition unit ahead of the simulation game

Although the assessment of the existing theoretical knowledge of business administration indicated a lesser knowledge gain in students with previous knowledge than in the comparison group, the students with previous training can be assumed to better retain their existing and acquired knowledge. The students also expressed the explicit desire for some theoretical business administration learning in advance of the business simulation game. It is therefore considered advisable to provide a business administration tuition unit in advance of the simulation game. Consideration should be given to business administration concepts such as the different items on the balance sheet. ◆◆

Optimising the “Accounting” and “Cost Accounting” modules

During the course of the business game it might be advisable to consider the annual accounts of known medium sized companies (GmbH) as part of the “Accounting” module so as to introduce and expand on the elements of a balance sheet and profit and loss account in a practical way. The annual financial statement should be read, i.e. problems of an actual company should be identified and suggestions offered for optimisation. For example, the advantages and disadvantages of a high level of stock and measures to improve the company’s success can be reviewed and discussed in small groups. In the “Cost Accounting” module, the

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students should be introduced to fundamental concepts and made aware of decision-relevant costs. ◆◆

Introducing a “Logistics” module

The weaknesses which students have when it comes to recognising the links between Purchasing, Production and Sales can be overcome by incorporating a “Logistics” module into the simulation game and with a haptic game. A “Logistics” module is not just about explaining the process chain from the raw material to the finished product, it is also important to consider the impact of the individual processes on the balance sheet, the profit and loss account and on cost and activity accounting. Here again, teams e.g. with the Think-Pair-Share format in which logistical issues are discussed are ideal for involving the students. The pros and cons of keeping stock, the impact of buying a new machine or the consequences of sub-standard products are just some examples of issues suitable for team analysis. The study also showed that there are terms such as ‘machine capacity’ or ‘machine utilisation’ which require explanation.

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Course formats The students achieved different knowledge gains in different course formats, indicating that there is potential for optimisation. Because tutors cannot readily change course formats but can only make suggestions for change, this study could only pinpoint ideas for optimisation rather than actual optimisation measures or processes: Course cycle ◆◆

In view of the amount of knowledge gained by students, block courses are to be preferred over weekly or weekend courses. It is currently proving difficult in practical terms to set aside two to three days per semester for business simulation games during course time unless the timetables are changed so that the courses in the different faculties have to be taken in blocks, similar to the MA course in Management and Communications. Otherwise, the best chance for block courses seems to in the first or last week of the semester break (similar to part-time courses in the Faculty of Microsystems Technology), though this is currently only possible with optional subjects such as Mixed Leadership. ◆◆

Business board games With business board games, students model the effects of business transactions by moving coins and tokens over a board. As well as the balance sheet and profit and loss account, the board represents the various stages in a company’s delivery of goods and services, such as Purchasing, Production and Sales. The participants see not just the changes in cash and assets, they can appreciate at first hand the effects of their actions on the business in the balance sheet and P+L account. For example, the production process – the transfer of goods from stock to production – is simulated using tokens. The board also demonstrates the decrease in the balance sheet total when stock levels are reduced, and the drop in profits as expenditure rises. Unlike computer games, board games offer a more accessible simulation of business processes as students consciously and deliberately move a product symbolised by tokens as well as their impact on balance sheets and P+L accounts. The business administration concepts represented on the board are present at all times and so enhance the learning effect. Board games prove to be a worthwhile additional tool before the computer game is played. The computer game can be shortened by one to two periods if time is tight due to teaching modules being extended or added or the inclusion of the board game.

Group number and group size

The knowledge gained by the students is greatest in a course involving twelve to sixteen persons divided into four groups or three or four students. Limiting the number of participants to sixteen is possible with optional and elective subjects. With compulsory subjects, all students would have to be guaranteed a place which would only be possible with a significant increase in available space and personnel. At the same time, constructing the timetable poses a major challenge to the particular faculty owing to the greater number of courses that would have to be accommodated. If the knowledge gain were enhanced with two tutors acting as gamemasters and they were only available to two or three teams of entrepreneurs, then the group size could be enlarged without sacrificing quality. Shortages of space and time could be mitigated in this case. This aspect was not surveyed in this project and provides material for further study. Assessments While the comprehension test provided greater knowledge before the course, students who completed a final class test achieved the greatest knowledge gain in comparative terms. Although the assessment took the form of either a comprehension test or a class test in the courses which were studied, we suspect that both forms of assessment would produce maximum success. Changing the formalities for student assessments is not a straightforward

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matter: The nature and scope of these assessments are laid down in the study and examination regulations or in the course programme and can only be changed by a decision of the senate or faculty council.

3 Conclusion To sum up, the findings of the empirical study can be presented as follows.

Figure 11

Summary of the empirical study (source: internal graphic)

Author/Contact Simone Six Ostbayerische Technische Hochschule Regensburg, Germany [email protected]

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Using the “Stakeholders” Simulation Game to Understand Social Problem: An Application of a Frame Game to Assess Environmental and Health Conflict Resolution Junkichi Sugiura

Abstract The purpose of this study is to develop the “Stakeholders” gaming simulation as a frame game for examining the procedure of resolving conflicts regarding environmental and health risks. Generally, simulation games create possibilities for exploring social phenomena that would be difficult to observe directly by recreating the relevant situations in a simple and safe environment. “Stakeholders” was initially studied as an educational program on consensus building (Sugiura, 2009). In this game, players experience the stakeholders’ process of consensus building on the distribution of risks. “Stakeholders” was also designed to examine the process of balancing conflicts within a group. Participants aim to maximize their own profits, while also considering other people’s interests. Participants make a social decision through joint deliberation. In previous research, the process of consensus building among stakeholders about the distribution of risks was examined through the simulation game. First, the simulation game was developed to visually depict each participant’s preference and perform consensus building based on that preference. Subsequently, the process of balancing conflicts within a group was examined using the developed simulation game. This research builds on the idea that, as in parliamentary elections, social determination begins with gathering individual preferences (Davis, 1973). One idea is that it is necessary for individuals to participate in an argument to adjust their own interests in a conflict by diversifying their sense of values. According to a viewpoint on deliberative democracy, it is important that an individual thinks deeply through deliberation (Renn, Webler & Wiedemann, 1995). However, in actuality, people pay more attention to their In the present research, the process of consensus building among stakeholders was examined using the “Stakeholders” simulation game, which was de-

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veloped as a tool for both education and research. The game requires a group to determine one unanimous preference from a set of options. Participants list their preferences at the beginning of the game. In this game, participants’ various senses of values are shown as preferences. The game visually represents each participant’s preference and facilitates consensus building on the basis of their preference. When a social decision is made, the deliberation procedure leading up to making the social decision is examined, referring to the mutual preference. Keywords stakeholders, social problem, frame game, conflict resolution

1 Health risk regarding food menu choice as a basis of the game design “Stakeholders” is a simulation game that was developed as an educational tool. Herein, this game is interpreted as a tool of research. The simulation required a group to determine one unanimous preference from commercial food menus. At the beginning of the game, the players listed their preferences on the stakeholder’s sheet. Next, one menu that referred to their preference was chosen in the group. The next step was for each player to calculate their individual score by referring to the difference between the result and their listed preferences. The sum total of an applied number serves as an individual score. For example, if the preferences listed in the columns labeled +4, +2, +1 and −2 agreed with the result of group decision making, these figures were added (4 + 2 + 1 − 2), resulting in an individual score of 5.

Figure 1 Stakeholders’ sheet

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The relation between the group’s decision and each individual’s score distribution was discussed within the group. Finally, different groups compared the score of each group among themselves. Food choices enable the consideration of both benefits and risks. Benefits include aspects such as high nutritional value and good taste, whereas risks involve health hazards (such as an allergy), food additives, and threats to the environment. When people’s recognition of benefits or risks is different, it is difficult for them to share or eat together which is a main topic of this game. Groups of approximately five persons gather and eat the same soup. Each of the five members chooses and tries one of five German packaged soups. All members deliberate on the basis of limited information and make a group selection. The score distribution of each group is compared between groups. The relationship between the score distribution of each group and the degree of satisfaction with the result is considered. A total of 116 students at a Japanese university participated in the “Stakeholders” simulation game. The participants were divided into 24 groups. Materials used were a stakeholder sheet, five types of packaged soups (potato, pumpkin, tomato, beef, and bean). A relation was found between the size of the variance of each score within the group and the degree of satisfaction with the group result. Acceptance of the result was so high that the variance of the score within a group was small, and the evaluation of the process of discussion was also high. A relation was found between the fair distribution of risks and the acceptance of the result.

2 Using the contents of a participatory conference on environmental policy The purpose of this study is to develop a game for environmental education that involves understanding conflicts about environmental planning and a fair distribution of individual risks. In Sugiura’s (2010) study, a participatory communication program for environmental education was developed using “Stakeholders.” Through the player assuming the role of a stakeholder and reviewing their experience, it may be possible to understand the advantages and disadvantages of an environmental plan. The game simulation requires a group to reach a unanimous preference among alternatives concerning 2R (reduce and reuse) behavior. The content is based on an actual participatory stakeholder meeting on environmental planning in Nagoya, Japan. In that meeting, the participants discussed the diffusion of 2R behavior and found several conflicts among the stakeholders. In the game, in contrast, players are informed of the stakeholders’ preferences at the beginning of the process. The group then chooses one alternative that refers to a preference. Group decision

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making is used to avoid individual risk and to maximize social benefit. Subsequently, each participant calculates their score by comparing the difference between the group result and their initial preferences. The relationship between the result and the score distribution of an individual is discussed by the group.

Figure 2 Example of Stakeholders’ sheet regarding 2R policy.

A total of 90 students at a Japanese university participated in the “Stakeholders: 2R” game. The participants were divided into 18 groups. The participants understood the fair distribution of risk in the case of interest adjustment and the fact that people differ in terms of their interests and risks. The range of the individual scores in a group was negatively correlated with the degree of satisfaction with the result (r = −.47, p < .05). This result was suggested that the degree of satisfaction with a result becomes high when a fair distribution of risk is achieved. Participants discovered a new criterion for decision making that referred to others’ preferences. Consequently, the decision-making criteria used in the actual life of a player may change. It was confirmed that the “Stakeholders” game can be used as a teaching material to encourage participants to consider risks and benefits to others. Participants could reach a compromise by considering the relationship between the fair distribution of risks and the acceptance of a result. The risk of the chosen alternative was low for each player within the group. The preference of each player may have been similar. A task with a definite conflict by the difference in each preference will be required to provide a further test of this application of the game. Finally, through this game, stakeholders can address various subjects involving interest adjustment. It is possible for researchers to examine the analysis of deliberation and the system of evaluation, and to explore which type of determi-

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nation method leads to greater acceptance of a deliberation result. The process by which preferences and the sense of values change is also discussed. Future work should use the game as a frame game, adapting the contents and focus to gather results on a range of applied uses. The analysis of deliberation and the system of evaluation should be developed further. The game can also be used to examine which methods of determination lead to acceptance of the deliberation result and to explore the process of change in a player’s preference and sense of values, as each stakeholder’s interests may change as the discussion progresses.

3 Visualizing the decision making system: introduction of wind power energy Sugiura and Motosu (2012) developed a variation of this game that used the contents of other frame game. The original contents were drawn from “SNG: Wind turbine” (Motosu, Sugiura & Arakawa, 2011), which examines the risks and benefits involved in wind power usage. Although wind energy is expected to make a contribution to global environmental protection, wind turbines also have negative effects on host communities, including landscape destruction and noise. Because of this local environmental influence, there is increasing opposition to wind projects by inhabitants. Players discuss introducing wind turbines, considering the positive and negative impacts using the frame game SNG, Settoku-Nattoku (“persuasion” and “assent” in Japanese) Game (Sugiura, 2003). The SNG is used in various fields concerned with risk communication, including areas related to the environment, health, and consumers’ issues. In “SNG: Wind turbine,” an information card about the advantages and disadvantages of seven types of wind turbines was prepared, and two positions introducing each wind turbine and the residents receiving the wind turbine were provided. “SNG: Wind turbine” differs from the original SNG in several ways. Players are assigned to role play the position of one of six types of residents: elderly people, people who earn their livelihood primarily by fishing, member of an animal protection group, housewife/ househusband with children, person who has experienced environmental pollution, and a public officer planning the revitalization of the town. While role playing the six types of residents, in “Stakeholders: Wind turbine,” players are tasked with unanimous unanimously deciding which of seven types of wind turbines should be introduced. The wind turbines (WT) considered are the floating offshore WT, the basic offshore WT, the WT by the sea, the WT on a hill/ mountain, the WT on flat terrain, the horizontal-axis small WT, and the vertical-axis small WT. Sugiura and Motosu (2012) suggested that the evaluation of a group result depends on differences in the rules of opinion manifestation. The “declarati-

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on-of-intention board,” which can be used to refer to an individual preference, is used with the task of unanimously selecting one of seven choices. The seven aforementioned types of windmills are drawn on the declaration-of-intention board, and each of the players has a cube that they can place on the WT they prefer. In the study of this game, each player received a cube of a different color, and the number of cubes was also manipulated. In conditions where there were no cubes, the declaration-of-intention board was simply placed on the table. In conditions where the number of cubes was one per player, the preference of each player was shown at all times. In conditions where the number of cubes was three per player, players distributed three cubes within three choices according to their preferences. A total of 143 students at a Japanese university participated in the “Stakeholders: Wind turbine” game. The degree of satisfaction of discussion was lower when one cube was assigned per player than under other conditions [F (2,139) = 11.6, p < .001)]. Moreover, when the number of cubes was three per player, the evaluation about comparisons of opinions and the expression possibility of an individual opinions was high [F(2,139) = 6.4, p < .01)]. It was possible to express an internal preference conflict between two or more choices, because a player was able to use three cubes. When each player had only one cube, it was difficult for players to change their opinions or commit to their own preference, and compromise was difficult between players with conflicting opinions. It was confirmed that combining this game with an intention manifestation board could be an effective tool for experiencing the persistence and resolution of conflicts in individual interests.

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health, and consumers’ issues, collected through this game may be treated as data for analysis. Each interest and risk may change within individuals, and this process is vital for this game. Each player expresses their interest before the group considers their mutual interests. The examination of this game revealed three main points: First, differences were observed when the initial preference criteria were prepared in a game, compared with situations where the players listed their actual preferences. When the criterion to choose was prepared, a common criterion could be used compare mutual opinions. When players listed the criteria themselves, a new criterion that was not expected could enter the discussion, potentially creating a new value. Second, in this game, mutual interest is visualized rather than being presented as a reality. Through this system, players compromise with their profits and come to accept a risk fairly. Third, the preference of the individual in group decision making is also visualized, for example, using an intention manifestation board. This rule makes the differences between the original opinions conspicuous, and it may contribute to the formation of a stronger opinion through comparison of one’s own opinion with those of others, making compromise a difficulty. In this research, it became clear that it is necessary to adjust the rules according to topic. The rule differences by topic of are explained in Table 2. Table 2 Comparison of Stakeholders by topic Creation of a criterion

Sharing of a criterion

Diversity of a criterion

Topic

Selection of food

Selection of an environmental policy

Selection of an energy policy

Difference of a rule

Players list, by themselves, favorite foods and the foods that should be avoided.

Players judge the priority of both the social desirability of a policy and individual risk.

Players assign 12 points of argument about wind power generation to a merit and a demerit.

The feature of each system

Diversity of the point of argument by players.

Evaluation of a social benefit and an individual risk can be compared in the point of argument of the policy by players.

Evaluation of the point of argument of players becomes both a merit and a demerit by the position of players.

Table 1 Means (SD) and F-Values of evaluation of discussion (Sugiura & Motosu, 2012) The number of cubes

0

1

Satisfaction of discussion

4.1 (0.7)

3.6 (0.6)

4.2 (0.7)

11.6

***

Comparison of opinions and the expression possibility of a self-opinion

3.7a (0.7)

3.8 a (0.7)

4.1b (0.6)

6.4

**

a

3 b

F-value a

***p < .001, **p < .01

4 Conclusion In group decision making, the “Stakeholders” simulation game visualizes the interest of each player and uses a score to express the relation between the profits pursuit of an individual and the final group decision. It was confirmed that this game can be considered a frame game, which can be used to understand a social problem. Information regarding risks, including those linked to the environment,

As can be seen, while the rules specifics may vary with stakeholders, overall similarities remain, and a rule in one can in turn be utilized again as an input for a different stakeholder. For example, the list of each food in “selection of soup” can be prepared in the gaming beforehand. As a result, the game is changed into one having a rule of prioritizing both a benefit and a risk. This is application of the rule of a version of energy policy. As mentioned above, in stakeholders, rule variations promulgate themselves by topic as necessary rule changes are introduced to accommodate the speci-

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fics of that topic. Thus, the following was clarified from the process of modifying the stakeholders’ rule. First, by using the contents of a game for another game developed in a different field, common features and differences of problem structure that are relevant to both original sets of contents can be discovered. Second, by moving the contents of a certain frame game to another frame game, the original game undergoes a process of rediscovery and re-contextualization that can change the availability of the original game and its contents. This occurs specifically because a new viewpoint is acquired by moving the contents to another rule. For example, by using the contents of “SNG: WT” as contents of “Stakeholders,” stakeholders’ theme is introduced into the original SNG. That is, the rule that the criterion of acceptance of persuasion changes with the players’ interests becomes newly introduced into SNG. By examining actual themes utilizing the same rule, the essence of the rule can be understood on a deeper level. A gaming simulation can thus be seen as a metaphor for the real world. The viewpoint that captures reality changes simply by changing the rule that expresses the real world.

References Davis, J. H. (1973). A theory of social decision schemes. Psychological Review, 80, 97—125. Motosu, M., Sugiura, J., & Arakawa, C. (2011). Science technology communication of wind turbine implementations by Settoku-Nattoku Game: Understanding for benefit and impact of wind power usage, Studies in Simulation & Gaming, 21(2), 105—114. (In Japanese with English Abstract) Renn, O., Webler, T., & Wiedemann, P. (Eds) (1995). Fairness and competence in citizen participation. Dordrecht: Kluwer Academic Publishers. Sugiura, J. (2003). The Development of the Persuasion Game. Proceedings of the 34th Annual Conference of the International Simulation And Gaming Association (ISAGA), pp. 713—722. Kazusa Akademia Park, Japan. Sugiura, J. (2009). Process of balancing conflicts about risk distribution and its acceptance using the gaming simulation ‘Stakeholders’. 8th Biennial Conference on Environmental Psychology, Zurich, Switzerland. (Program & Abstracts, p. 48). Sugiura, J. (2010). The process of balancing conflicts on environmental planning using the educational game “Stakeholders.” 21. IAPS Conference 2010 -, Leipzig, Germany. (Abstracts of presentations, pp. 307—308) Sugiura, J. & Motosu, M. (2012) The effect of opinion manifestation procedure on interest adjustment. Proceedings of the 53rd Japanese Society of Social Psychology, p. 104. (In Japanese)

Author/Contact Junkichi Sugiura Keio University, Tokyo, Japan [email protected]

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Fundamentals of Game Design Richard Teach; Joan K. Teach

Abstract The methods of almost all games include the use of stochastic events or chance to partially determine outcomes. The first part of this paper describes standard playing cards or dice to incorporate chance in games and game design. In most games, chance is introduced by using symmetric probability distributions. However, sometimes gamers may wish to give some players an unfair chance in order to demonstrate a specific social phenomenon. The methodologies discussed use simple games to demonstrate various points. The second part of this paper includes some games that emphasize the role that sense and perception portray in gaming. As individuals we bring a multitude of experiences to the game, and a multiplicity of learning styles. Therefore game design becomes as complex as the individuals for whom the game was designed. Keywords design; decision rules; distracters; learning; stochastic

1 The use of chance in gaming by a deck of cards It is often useful to begin the discussion of game design by using simple examples in order to lay a solid foundation before addressing more complex structures. This makes sense as an architect does not begin by building a one-hundred story structure, nor does an engineer start by building a rocket ship. Each starts by examining the basic fundamental of the science. The study of games begins with simple examples, such as card games. What is pictured in figure 1? Obviously it is a deck of cards. To a gamer, it is much more, it is a probability distribution. More specifically it represents a discrete probability distribution without replacement. What this means is that as a game is played with a deck of cards, the probabilities of guessing the next card to be dealt changes with each card displayed. In addition a deck of playing cards contains 4 uniform distributions, one for each unique suit. The odds can be easily changed simply by using multiple decks, as used in a casino when playing the game of “BLACK JACK.”

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Figure 1

A deck of cards

This game uses six decks of cards to reduce the possibility of a player counting the cards and thus have knowledge of the probabilities of the cards remaining in the dealer’s deck. Not all card games use the standard deck of 52 cards that consists of 4 suites with each suit having 13 cards. Game designers use many versions of card decks from a simple variety of only colors to cards with 2 dimensions (colors and numbers) and in a few cases with 3 or 4 dimensions configured in one deck, depending upon the degree of complexity designated in the game design. The game of OBSERVATION is an example of a highly complex card game that starts by using only a single deck of the common 52 card deck of playing cards. This game can be played by 3 to 5 players. Let us illustrate it by showing a five-sided table with 4 players plus the dealer, each sitting at a side. The game table at the start of the game is shown in figure 2. The dealer deals each player 5 cards, then turns the next card face-up, and places it in the middle of the table. The remaining cards are placed face down, in the middle of the table, next to the face-up card.

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The dealer instructs the players, “This game is played starting from my right, one player at a time. When it is your turn show me one card from the hand of cards that you are holding and I will respond by saying, ‘I accept that card’ or ‘I reject that card.” If I accept the card, place it face-up on the face-up card already on the table. If I reject the card, place it in the space in front of me as the dealer. After you dispose of the accepted or rejected card, you are to draw a card from the set of face down cards in the middle of the table. The purpose of this simple game is to determine how quickly you, as a team, are able to determine the decision rule that is being used to either accept or reject the offered card. Figure 3 shows the playing table after a few rounds. The dealer then remarks that since this is a binary decision rule, maybe the cards in the “Rejected” pile contain as much information as the stack of “Accepted” cards. As a result of this comment, the players attempt to re-order the discarded pile of cards, but they rarely agree as to which card was played in what order. Since it went to the reject pile, no one paid much attention. The players either agree to the sequence of the rejected cards or they agree to only order the yet-to-be played rejected card in the order that they will be played.

Figure 3

The gaming table after a few rounds

Figure 4 shows the gaming table after this consultation. The dealer makes the following observation, “All four of you are holding your cards in a way that the other players cannot see them.” “Why?” You were told at the beginning that the objective of the game was to determine how long it would take the team to determine the decision rule.

Figure 2

The initial gaming table

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answer found within a reasonable amount of time. It has also been observed that the higher the education level of the players, the harder it is to find and agree on a solution. This game is useful as it demonstrates that finding something obvious does not mean it is easy to be found. An example of this problem is confirmed whenever someone says, “Look around and you will know it when you see it, it will be obvious!” The game table now looks as shown in the diagram, figure 5. The solution is obvious, although most do not recognize it because the solution is in two dimensions, not one. If you would like help in recognizing the solution, please email us at either of the addresses listed at the end of this paper and we will send you the answer. Figure 4

The gaming table after the first consultation

There is no advantage to the group when you hide your cards from your fellow players. In fact, there is a distinct disadvantage to this method of play. (The reason players hold the cards so none else can see them is simply; that this is the way card games are played.) Figure 5 shows the gaming table after the second consultation and the gaming table does not change after this last consultation. Thus, the structure of the game is contrary to what is normally expected. This is an advantageous trick when used in designing games.

Figure 5

2 Dice The next most commonly used component of a game is the die. It is also a discrete uniform probability distribution and comes with many sides, but let’s discuss the most common 6-sided die with the number of dots on each side ranging from 1 to 6. Most games use two dice, as shown in Figure 6, but one is common in young children’s games and a few games use more than two dice.

The gaming table after the second consultation Figure 6

At this point, all the factors of the game are discovered or revealed and the game continues. In playing this game, we have had players, after seeing all the players’ hands, offer to buy or trade for another player’s card, in order to confirm or deny a hypothesis about the decision rules. Here again, the assumed card game rules forbid the playing of another player’s cards, but this assumed rule does not apply to this game. Usually, this game appears to end when there are no more cards, this occurs when all 52 cards have been played or are in the hands of the players. However, at this point the dealer picks up a new deck, shuffles the new cards and places the new deck on the table. Typically the solution to the decision rule is not found. This game has been played many times and only once was the

A pair of 6-sided dice

In the usual 2 dice game, the sum of the 2 dice is the number of spaces a player moves the playing piece on a path of the board game, such as the one shown here in figure 7. But, the choice of the number of sides of the dice and the number of the dice to be used, creates some of the constraints of the game. For constraints of the game. For example, if one adds the number of dots on the 2 dice in the figure, the number of spaces the player moves his or her piece is 10 spaces. If one moves 10 spaces on the game board as shown in figure 7, the player wins. As a result this game could use only one six sided die and one may limit the number of spots on the die to 1, 2 and 3 and use each number twice.

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Figure 7

A child’s board game

Why do you add the number of dots together? The sum of two randomly selected elements from a uniform distribution of integers ranging from 1 to 6 resulting in a distribution with a single mode of 7 and a range from 2 to 12. If one desires the players move more slowly, ending on more board positions per round, the absolute value of the difference of the dice values could be used. The distribution of the absolute values has a single mode, but is not symmetric. This distribution is shown in Figure 7.

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As an example, one of the authors built a board game called the assassin, where one player with a small number of pieces (the cops) was to move according to the absolute value of the difference of the values on the dice plus 1. The opponent (the assassin) had many characters to move and played by moving his or her characters by the sum of the values on the dice minus 1. One could also use the product of the 2 values shown on the dice. This is a highly skewed series and many values are not present. It could, however, be used to provide a skewed distribution of money for the players participating in a game. Another method to determine the number of spaces to move on a board-like game could be to use 3 dice, 2 white and 1 red, as shown in Figure 9. One could add the white dice and subtract the red one. This configuration would allow a minimum number of minus 4 and a maximum number of 11. Thus, a game using this configuration of dice must be able to have the playing pieces move in both directions. The combination of 2 white and 1 red die is used in a game called ROSES AND PETALS. The red die is used as a distractor. Using a distractor is a common device in many games, as it looks like it is important but, in fact, it has no impact upon the game at all. In ROSES AND PETALS the gamer throws 3 dice. He (she) then announces that there are N number of roses and M number of petals and then rolls the 3 dice again, repeating the announcement of the number of roses and the number of petals time after time. The on-lookers are to determine what makes up the roses and what makes up the petals.

Figure 9

Figure 8

The absolute values of the difference in 2 six sided dice

Three Dice, 2 white and 1 red

The answer is: a dot in the center of a die determines a rose and all the dots on the dice with a center dot (all odd numbers) count as roses and when a dot is not in the center (all even numbers) all dots count as petals. A simple but difficult task to determine by observation, especially if the gamer rolls the dice rapidly.

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It is difficult to remember the values of each dice when you do not know the decision rule.

3 Gaming Strategies Combining Short Term and Long Term Decisions A fast playing business game demonstrates that short-term tactics may have unintended consequences in the long term. MIRROR — MIRROR, named after the mirror used by the wicked queen in the Snow White fairy tale, is a very simple game that uses a hand of playing cards as a decision making factor to create results in a simulation of a business strategy. This game has often been played by senior level managers from an assortment of firms. It was designed in the 1980s, by Clive Loveluck, an ISAGA member. It is a two part game; Part 1 is based on attempting to shore-up profits resulting from one year’s operations and Part 2 is a longer term strategic planning issue. In Part 1, the team-based game begins with a simple income statement and a balance sheet of a manufacturing firm at the end of year N and each participating team receives identical game playing spreadsheets. Table 1

MIRROR MIRROR game playing spreadsheet

Data term Industry Sales

End of Year N

Firm Sales

38.000.000

Firm Assets

22.000.000

Number of Employees

% Change in Value

Result in Year N + 1

80.000.000

2.000

Firm Total Costs

27.000.000

Profit

11.000.000

Performance Measures

Market Share

47,50%

Profit as a % of Sales

28,95%

Profit per Employee Profit as a % of Assets

5,500 50%

The game administrator shuffles a deck of playing cards and deals one card to each team. The value of that card represents the annual percentage change from the prior year’s accounting value of the firm’s financial statements as shown in Table 1. (An Ace equals 1%, and all face cards equal 10%. Red cards indicate a percentage of decrease and a black card indicates the percentage of increase). This first card represents the change in the value of industry-wide sales for the year. The second card dealt to each team represents the change in company sales

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during the year. The third card dealt represents the change in the amount of assets controlled by the firm. The fourth card represents the changes in the number of employees of the firm and the fifth card dealt represents the change in the total costs incurred by the firm during the year. The teams are then asked, “Who won in the year N+1?” This simple question often results in a heated discussion within each team as to how to best present their financial results in a way that would show them in a winning position. By now no firm is exactly equal to any other team and no one wants to lose. The result is an excellent discussion of how should a firm’s short term financial performance be compared with other firms, with unequal financial structures. In Part 2, each team is ask to rearrange the cards they were dealt into any order that will increase their firm’s financial performance. Recall that originally each card was specifically assigned to a single outcome; this specificity is now relaxed. This change in the rules results in a great deal of team discussion within the teams. When all of the teams have completed this task, the game’s administrator asks each team how they altered the order of the cards that they were dealt. And as each team responds, the administrator explains the long-range strategic consequences of each change. Decreasing industry sales to increase the year’s market share reduces the viability of the industry. Decreasing the number of employees to increase profit per employee increases hiring and training costs in the future. Most changes have explicit long-term strategic impacts or unintended outcomes. Therefore, there are many approaches to game development containing cards, dice, boards and forecasting strategies, but there is another facet of gaming, that factor of what the individual brings to the game from his or her own background.

4 What is the Sense of Gaming? In gaming we provide an opportunity that may make sense, may portray a perception, involve the many senses we utilize, enhance our operational style and definitely effect learning. Each player is different as we all have variations in our styles of learning. We all come from a variety of backgrounds, have a wide and varied set of experiences and come with pre-formed judgments. Often those participating in a game have definite notions as to what is right, wrong, or how a function must work. The astute gamer considers all of these issues as they consider the process inherent in the game. For, if a game is to be successful, the game designer must not only define what the learner is to learn, but also consider how that learner learns.

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DRIVE — ALIVE Let’s begin exploring the senses and how different prompts create different responses in each unique individual. If you are going to address the learner’s style of learning, you must address the variation of the individuals collected to play the game. One strategy is to present the material that is to be learned in a wide variety of sensory modalities in order to reach a wider variety of learners and their operational styles. DRIVE ALIVE is a game designed to prepare teens and young adults with learning difficulties a chance to learn the rules of driving with a more hands on approach than the usual ritual of read the manual, memorize it and take the test. Analyzing the task at hand, it was determined that there were both facts that had to have meaning, situations that had to be interpreted as well as the actual driving consequences that needed to be addressed. In designing the game DRIVE ALIVE, each fact, situation, and consequence was addressed in several learning modalities. The acronym DRIVE then is an acronym for: D Demonstrate The player will nonverbally role-play the situation presented on a card. Other players may be called upon to assist so the situation can play out successfully. A collection of hats, scarves, and sunglasses enhanced the ability to role-play, portraying the mood of the event. Figure 10 shows the variety of accessories that are possible to use. Learning Modality: Active Movement

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Three by five index cards were designed with a street sign, shape or traffic sign on one side and its appropriate label and description on the other. With the timer set to two minutes, the player labels and describes as many signs as possible before the buzzer sounds. Figure 11indicates one of the signs that is included. Learning Modality: Visualize, Identify

Figure 11

An example of street sign with definition

I Illustrate The player will draw and illustrate specific driving rules and regulations outlined on the card. Printed icons, stickers and other aids will be available so that those with grapho-motor difficulties will be able to be successful. Figure 12 shows readily available materials that can be used to demonstrate knowledge of a driving rule. Learning Modality: Tactile Kinesthetic

The variety of accessories available for players

R Rapid Recall The player will identify and describe the meaning of as many road sign, shapes and signals as possible in 2 minutes. Figure 12

An example of the assortment of materials used to illustrate

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V Visualize Using printed street plots, the player will demonstrate the situation presented on the card. Some situations will relate to rules of the road, others will relate to common courtesies needed to be a good driver. Blocks will represent cars, school busses, police cars, fire trucks, etc. Street signs on posts, people, and other items such as bushes that obstruct your view, are all made with magnet bases and can be placed on the cookie sheet to demonstrate and enhance the proper explanation. Figure 13 shows actual scenes that were used on roads that the driver would travel such as curves in the road, solid yellow lines, and no passing zones. Learning Modality: Visual-Kinesthetic

Figure 14

Figure 13

Driving imagery

E Explain The player will examine a scenario and determine whether or not the situation was legal, proper for a driver to have done, or if some part of the event needed to be done differently. Clear and concise understanding of good driving habits should be used as well as indication that the player understands the implication these social situations have to driving. These scenarios enhance the understanding that being pulled over after drinking can have immediate consequences as in figure 14. Learning Modality: Verbal Analytical

Consequential learning

Instruction cards are drawn for each play. The color and icon on the card indicates the type of activity requested. Materials necessary for play are in boxes, sorted by the type of play. Actual road scenes, cars, school buses, railroad crossings were captured from Google Images to assist in demonstration. It was determined that the closer to reality the visuals became, the more realistic the image reinforcement, the more serious the output. Figure 13 shows a typical driving scene. For consequential learning and enhanced decisionary factors, scenes from automobile accidents and other serious outcome images were used.

5 Personality-Operational Style Connection Along with the varied operational styles of a learner, one must also address the emotional impact the subject matter, or scenario has on the individual. Some players will have an intense sense of right. How they view an issue is absolutely the only way it should be addressed. This creates emotional breaks for some. Some are reticent to play due to a fear of failure. Others have a quest for total control, and like a four year old are devastated if the “roll of the dice” is not in their favor. In today’s society we are all attuned to success, and because of this are often emotionally vulnerable. Events of chance impact both learning and emotional outcome. Behavioral responses due to these factors often are shown as passivity, those who refuse to participate, or only do so under a great restraint. Some players have trouble focusing, staying on task and need frequent prompts, are easily distracted and

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their impatience makes them jump to conclusions. Others are overwhelmed by the amount of data, rules, and instructions and are definitely out of their comfort zone. This person may even go so far as to sabotage the game by playing outlandish moves, or implementing bizarre strategies. This often comes from the fear of failure, being criticized, or confusion. Therefore, the astute gamer understands the emotional vulnerability of the players. SHOP ‘TIL U DROP Another example of multisensory learning is imbedded into the game SHOP ‘TIL U DROP. The board for this game is shown in figure 15 and was developed to address the insecurities of young females who are immature, and apprehensive to go shopping in a mall where other more mature teens excel.

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This design was created to be more life-like, eliminating the usual strategy of the Monopoly board that wraps around, giving a certain amount of money whenever you pass GO. Instead, as in today’s economy, a person could stop by a bank and withdraw money, if there was still cash in the account, or if she had a card to do so. She can also negotiate to borrow money from a friend. Another could have unrestricted access to money by being given a credit card to use for whatever she wished to buy. Accounting sheets were used to keep track of money and penalties given for certain breaches in spending.

6 Personality Types In reflection of personality styles, the girls played out their own approaches to experiential learning as observed when the shy gal spent nothing and went home empty-handed. She observed and wandered the corridors, almost as if she wasn’t there, a symbol of her own internal insecurity. Others spent meticulously, purchasing only what they were requested to spend, and never touched any of their own “mad money.” Some ventured further, but often after purchasing cosmetics or trinkets, spent the rest on food, which is a normal teen-like behavior. Another was the impulsive spender who bought everything in sight. She was down to her last dollar, and compulsively bought a sugar cone for that dollar, even though she didn’t have enough to buy the ice cream to go with it! Our behaviors so often align with our own personality types, and games bring these out in all of us.

7 The Use of Dice in Shop Til U Drop The corridor design of the mall was blocked into three columns. Therefore, if you wanted to go into a store, you had to move the correct number of spaces to get into that store. This established the need to have a choice of movement options that could be controlled by the player. Yes, the game uses two dice as movement decision makers, but the usual rules were changed. The player rolls the dice, but has a choice as to how many moves she wants to take. She can accept the usual addition of the two numbers on the dice, or she can also choose to subtract the numbers on the dice, or she can also pick to use either number. Figure 15

The SHOP TIL U DROP game

The design of this board game is to provide a chance to play- act the mall experience in a safe environment. It has a multi-level group of activities that range from the simplistic act of learning how to manage money, how to budget what you spend, or being able to follow a directive from the family as to what is to be purchased. Other issues addressed include using dice as a strategy system. The mall is designed as a cross of four corridors with a food court in the middle.

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Mall corridors were arranged in three channels encouraging multidirectional movement.

With a three-column corridor you may need to move across the hall in a strategy to reach your chosen store. In this way the pawn can be moved anywhere on the corridor, forward, backward, or sideways. This again breaches the expected interplay of dice and pawn on a normal board as is shown in figure 16.

8 Examining Consequences As seen in many malls, the food court was placed at the confluence of the corridors. This enabled the gamer to develop a social emotional component to address this population’s specific difficulty. When a player moved through the food court area to get from one corridor to the other, a situational consequence card was drawn from a deck placed on the food court. Situations related to realistic events that may happen in any mall. Discussion among the players analyzed the situation and each player had a chance to have input as to how she would handle the situation. Ample time was given to prompt discussion among the players. Figure 17 shows the outline of the Food Court.

Figure 17

Food Court

Once again, personality styles greatly influenced how players responded to the situational prompts. Considering the group dynamic, several positive as well as negative responses occurred. Teens often responded in keeping with their unique cultural backgrounds and understanding. Some became more engaged as the trust factor increased and they realized they could offer their own opinion, and that it did not have to agree with others. They learned that opinions are just that and that they were not right or nor wrong and that different situations had many answers and that there were many ways to look at an event. This area of the game requires an astute facilitator to be entirely successful. Figure 18 shows samples of some of the situations used. Therefore, this is a game that breaks the traditional rules of play. It is on a board that has unlimited movement potential, uses dice in different decision-making modes, includes consumer math in reality form, and imbeds social-emotional consequences. Deliberately it approaches personality styles and embraces these differences.

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Figure 18

Consequence Cards

9 Gaming to Learn Our job as gamers is to represent the issue, not to absolutely replicate it. Considering that our players come from varied backgrounds, from all walks of life, and all cultural backgrounds, games must approach each learning situation from many view points as possible. Given the individuality of the players, stochastic events can be deliberately skewed and the symmetry of the probability distribution enhanced. Therefore, addressing the form: be it dice, pawn or card, and imbedding rules that determine how they are used, enhances the game and enriches the total playing field. However, if the issues brought out by the unique factors of the learner are ignored, the game becomes severely limited and the success and charm of truly thinking outside of the box or of producing an inspired and new sense of learning is impaired. Our challenge to you is to explore the many fundamentals of gaming so you too can design a game that is truly unique with its own set of decisionary factors, yes, a Game with a capital G! Authors/Contact Richard Teach Scheller College of Business Georgia Institute of Technology, Atlanta, USA [email protected] Joan K. Teach Community Resource Center Atlanta, USA [email protected]

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GamEducation — A Game for Learning to Create Game Sun-Teck Tan

Abstract It is an undisputable fact that computer and video games are part and parcel of our life. Either we play it ourselves or someone near to us is playing. Most of the time, people are spending too much of their time playing the games and their normal life are affected. Students would neglect their studies and even adult would become unproductive. The worst effect is that people are detached from each other as each of them is minding their own business. In this paper, we describe a system that addresses some of these problems related to computer games. Instead of spending time playing games created by others, we would like to nurture a new generation of young game developers so that they can put their creativities to good use. We would also encourage more interaction between children and their teachers so that they can learn when they play the games created themselves which have core subjects matter inserted in the games. GamEducation is the name. Keywords education, learning, game development

1 Introduction 1.1 Proliferation of computer games PC games, also known as Computer Games, are video games played on a general-purpose personal computer instead of on a console or arcade machine. With the proliferation of information technology (IT) in recent years, number of gamers increase rapidly. Video games have become a popular activity for people of all ages, especially children and teenagers, as video games bring about a variety of new experiences and activities. There are many surveys conducted and results all shown the same statistic. Entertainment Software Association (ESA) in 2013 concluded that 58% of Americans play video games with an average of one dedicated game console, PC or smartphone per U.S household. 32% of gamers are under 18 years old according to the statistic. The survey conducted by PEW research Centre shown that out of 1102 teenagers aged from 12-17, 97% play video

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games, either on computer, web, portable or console games. The frequency and duration of teenagers playing video games also vary. The study shows that nearly 31% of teen gamers play games on a daily basis, and another 1 out of 5 play games three to five days per week. Furthermore, 80% of this group of teenagers played at least 5 different types of games. And about 21% of student below the age of 18 plays game 3 to 5 days per week, average 2 to 3 hours per day, which means they spend about 13 hours a week playing games. 1 out of 10 students admitted that their reason for playing game was to keep themselves away from studying (Lenhart, 2008). However, space has been enlarged for games that support educational purpose. 18% of teachers use games in class on a daily basic with 95% of them use digital games created specifically for education and 70% agree that using educational game increase student engagement (Dunn, 2012). 1.2 Positive impacts of computer games According to a research conducted by Barlett, Anderson and Swing in 2009, playing video games can have a positive impact on players’ visual attention performance (Barlett, 2010). This implies that gamers not only are more focused but also obtain better results in visual related tasks, compared to non-gamers. In addition, players’ ability to analyse patterns and relationships in geographic space also improves thanks to video games. Moreover, Barlett’s research shows that educational games not only teach educational skills and knowledge but also enhance children’s creativity. This is due to the fact that children can experience the freedom of creation while playing. Better creativity enables individuals to discover their personalities, thus develops self-awareness and independence (Correia, 2011). When playing games, children can fully comprehend the consequences resulted by a specific behaviour, hence become better in their decision making. They can then apply that to their real life. Another study was conducted by Feng S. Din on the effects of educational games in learning (Din, 2001). The study was conducted to two groups of children, the experimental group and the control group. Both groups were to take 2 tests. However, between the 2 tests, only the experimental group played video games while the control group did not. According to the result, both group’s score was increased; the experimental group had a slightly better improvement then the control group. This experiment implies that educational games can have positive impacts on children’s academic results. Besides its effects on academic results, games in general, and educational games in specific, have enhance children’s thinking ability as they can freely exercise. As stated by Eric Klopfer, there are 5 types of freedom that children at play can experience, unlike in reality: freedom to fail, freedom to experiment, freedom to fashion identities, freedom to effort and freedom to interpretation (Klopfer, 2009). Children do not actually fail at play, but feel what failure will be like in other contexts. This is like the first time anyone trying to ride a bicycle, people fell many times but they

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keep standing up and try until they can ride. However, it is different in academic world, where many parents fret their children about the cost of failure. Fortunately, children at play do not have their parents around so they can freely learn from their failure. Children are free to experiment. This correlates with the freedom to fail; children can try out whatever task they want, in whatever approach they want. They do not have any constraint in game. For example, they cannot fly in reality but in game, it is possible. Children are free to fashion identities. At play, children do not simply discover the nature of the physical and social worlds, but also figure out their own self in those worlds. (Sharma, 2013) Children are expected to put in effort continuously as they work toward a goal. Children are free to interpret when learning about games and learning with games takes place at the same time. Two players playing the same game might have different understanding and experiences about same scenario, hence use different methods to achieve the goal. 1.3 Negative impacts of computer games However, games also have potential negative influences when children are highly addictive to it. One study on the correlations between students’ time spend on studying and gaming was published by the National Bureau of Economic Research. The report showed that, gaming took up lots of children’s time, which should have been used on studying or revision (Timmer, 2009). Besides being time consuming, games with inappropriate contents such as violent, blood and gore, sexual, or strong language definitely have negative impact on children. These negative influences lead to aggressive thoughts and behaviour, social isolation and confusion between reality and fantasy. The interactive nature of the games worsens the violence in children. In many games, children are awarded to be violent. This repetitive active participation in violence has negative impacts on learning. Besides violence, according to child experts, too much of video games detach children from the real world. Children no longer wish to spend time in real life conversations and physical interactions as they are more engaged in the virtual world (Raise Smart Kid, 2013). Silvern and Williamson (1987), stated that the prosocial interaction of a child is inversely proportional to his engagement in video games. They will gradually lose several basic social skills. Thus video game is not a platform to teach social behaviour and social cohesiveness. Furthermore, playing video games for a long period of time might cause computer vision syndrome (Vision, 2008). Several eye illnesses such as screen eyes discomfort, fatigue and blurry vision are caused by extensive viewing of the game. Since children are engaged in video games without supervision, they do not give their eyes a suitable break. This long game play without rest might impair their eyes permanently.

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2 GamEducation Mindful of the pros and cons of computer games, we created GamEducation to serve as a platform where children can learn basic concepts of game design as well as use their creativity to create their own games. Jenkins (1998) had shown that children gain better knowledge about qualities and values exhibited by the general game worlds when they are provided tools to construct their own play spaces and then given the freedom to do what they want. Hence, our project’s aim is to create a platform to allow children to design their own video games, thus help children to be more aware of the potential positive and negative impacts video games possess. The created game is a simple 2D tiles-based game with different obstacles to avoids and treasures to collects. However, users can make it more interactive by adding quizzes to certain obstacles or limit certain resources (such as ‘lives’ or ‘time’). Users can also come up with a story themselves and lead the player through stages with interesting dialogues. In order to add in more educational factors to the game, we built a short story which, after finishing, players can understand the basic concept behind game development’s progress. GamEducation consists of two modes. 2.1 Story mode As the name suggests, players will go through a story where they play a role of hero standing against evil. Since the target audience is children, the idea of being a hero is attractive to them. In this mode, we emphasize the importance of learning programming and it shows students how to think logically. This unit starts by introducing to children the basic concepts of programming including using a simple “create” function or undo their mistakes by a “delete” function. Moreover, they are also taught about how to create and place some primitive graphics on the screen such as square and circle as well as how to combine them to make real obstacles in their game. It is then followed by introducing to students how to make the game more entertaining and attractive, since games are made to bring joys to players. In order to do so, “goals” and “rules” of a game are the two essential factors. Children will have a chance to learn that different types of goals lead to different levels of difficulty and fun. In addition, we introduce 2 kinds of rules in our game, which are ‘time’ and ‘life’. We let them know that changing those rules may affect the playing style of their games and also they must be used appropriately, otherwise, they can lead to the game unwinnable i.e. Game lasts forever. All of the above will be shown one after another as the player play through the following story:

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The story begins with a guy named Markus, who has just moved into a high school in South America. This is where he meets Larry, a normal high school student with extraordinary skill of game development. His self-implemented game achieves many successes, which brings trouble to many big game development companies. One of them decided to take action. Company Peelevilish’s head of program, Gauro, sent Larry a program which turns him into a game’s character and trap him inside a game until someone finishes the game. Fortunately, Markus was invited to Larry’s house that day. He saw the whole thing, and decided to help. Suddenly, when Markus started to play, a mouse-soldier appears calling himself, Ostro. He was created by Larry, and he helped Larry in creating many games. Now he will help Markus in rescuing his master. Currently, the game has 5 stages: The first stage is an introduction stage, where player learn about controlling unit, Larry, to move around and reach the goal (due to space constraint, we will not show the figures when describing the stages beside the following figure).

Figure 1 GamEducation

The second stage is where player learn about ‘function’. Using a console, player will be asked to input a certain command to create obstacle in the screen to prevent the monster from moving and safely advance through the stage. The third and fourth stage are about controlling the game “rules”, where stage 3 is about “life” rule and stage 4 is about “time” rule. In specific, stage 3 is unwinnable with only 1 ‘life’. Therefore, player has to edit this in order to survive through the stage and advance. Stage 4 is about controlling ‘time’ rule. Player is given 5 seconds to go through a long tunnel, which is impossible. Hence, the guider helped by allowing the player to edit the time so that it is enough for Larry to advance through the stage. The fifth stage shows another feature of our application, which is important for education purpose, pop-up question. Throughout the game, there will be vari-

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ous obstacles where a question will pop up. In order to pass through that obstacle, a correct answer must be provided 2.2 Create mode This is where users can have their hand-on experiences on making a game using the provided APIs and built-in components. Below is the list of features provided in GamEducation’s create stage. (Again, we will not show all the figures except the first one). 1 Drag and Drop This is a common feature. A list of ‘obstacles’ will be shown on the left side panel. Users will drag the obstacle they want and drop it into the game-field to add it to the game.

Figure 2 Drag-and-Drop features Left: Dragging, Right: Dropped

2 Use imported self-made obstacles Besides the provided obstacles, users can use their creativity to create their own obstacles. After creating the obstacles, they can upload it to our server. The list of these obstacles will be retrieved from an URL link sent from the server at the beginning of the application. The obstacles uploaded will be listed below the provided obstacles 3 Use imported self-made game backgrounds Similar to the self-made obstacles, users can upload their self-made background. These background will also retrieve from an URL link. Background of the game can be changed by clicking on the “+ Screen” button. A list of provided screen together with the uploaded ones will be shown to choose from. 4 Use uploaded self-made quiz A little different from the previous two points, instead of uploading images, users will submit a list of questions with provided answers and hints. These questions will be shown on the ‘teacher’ webpage and wait for his/her approval. This

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needs to be done since we do not want to have questions with incorrect answer. This must be prevented since the aimed target group is children. They learn fast, hence, any incorrect answer may lead to them gaining incorrect understanding of the subject matter. After the approval, the list of questions will appear if users click on the obstacles and choose ‘Question’. By choosing the question they like, the question will be attached to that obstacle. Later, while other people come and play his/her game and collide with that obstacle, the question will be popped up. This is where it adds in educational value to the application. Teachers can setup their own series of questions, then they create a game with the questions attached inside the obstacles and tell their student to play. Through playing, student will come in contact with the obstacles and the questions will pop-up. After answering the questions, the system will send to the server the statistics: whether the question is attempted, answered correctly or incorrectly. The statistics will then be showed on the users (or teachers in this example) webpage. Based on this, teachers can have clearer view on how their students perform on certain topic. 5 Modify resources (‘lives’ and ‘time’) Same as in the ‘story mode’, the user can click on the ‘lives’ and ‘time’ icons to modify how many lives the players have and how long they have to finish the game. This is where users put what they have learned inside the game to use. Whether they put the value for these resource too high or too low will have effect on the outcome of the game. It may reduce or increase the interesting level of the game. 6 Modify collectible treasures Users are able to import their own obstacles, hence, they can import their own treasures for their game instead of using provided treasure ‘coin’. As we allow users to define their own story; in their story, they may not want people to collect just the coins over and over again. They may want them collect ‘wood’, ‘water’, etc. Hence, we allow them to choose the treasure that is the most suitable for their story. There is a limitation that one game can only have one collectible treasure. 7 Enter dialogue for the game As stated in previous part “Modify collectible treasures”, we allow users to define their own story. The only way to show the story is through dialogue. Therefore, users can enter their story in the given panel. Each time users press ‘ENTER’. It will record it as own ‘dialogue line’. The whole dialogue contains many ‘dialogue lines’. While playing, each time the player presses a key, the dialogue will display a new ‘dialogue line’ until it runs out of lines. 8 Implement enemies with attributes (type, speed, image) A game is not interesting if players only go around, collect items and reach the goal. Having an enemy is one of the key parts in development of an interesting adventure game. Hence, we provided users with tools to add in enemies to their game. Each enemy will have 6 images to choose from.

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9 Besides, users need to define enemy’s speed and type. Below are the two provided types: 9.1 Patrol enemies Basically, this type of enemy will patrol around certain defined points on the grid. User can choose to let the enemy patrol in ‘circle’ or in ‘reverse’ mode. ‘Circle’ mode means that after reaching the last point, the enemy will go to its starting point and start a new loop. Since enemy can only go vertical or horizontal, the last point must be in the same row or column with the starting point. ‘Reverse’ mode means that after reaching the last point, the enemy will go back through previous points until it reaches the starting point. Then it repeats the same path again. ◆◆

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Since ‘Patrol’ enemy needs to have specific points in order for it to move around, upon choosing the patrol enemy, users will be asked to input its starting position if they did not do it. After that, user will proceed to choosing either ‘reverse’ or ‘circle’ mode and starting choosing points afterward. Due to the fact that the enemy can only go horizontal or vertical and cannot go pass the obstacles, system will highlight the tiles that users can choose from. Any selection beyond these tiles will not be accepted. After done with selection, any tiles in the enemy’s path will be marked in red and user cannot drag and drop into these tiles. 9.2 Follow enemies Unlike ‘Patrol’ enemy, this type of enemy will not go to any specific points but will take player’s position as the target point, and find a path to it. This enemy is implemented using A* finding algorithm so there is no need to do any pre-processing. Pathfinding’s objective is to find the shortest route between two points. This is done given a start tile (enemy’s current position) and known destination tile (player’s position). It starts with examine all tiles adjacent to the start tile that are not part of the path yet or not blocked by obstacles. Since enemy can go horizontal or vertical, no diagonal tiles checking is done for this game. For each examined tile, three values needed to be computed: G: the cost of moving from start tile to the examined tile. Since all tiles has the same size, the cost of moving from one tile to another is always 1. H: the estimated movement cost to move from that examined tile to the end tile. The easiest way is using Manhattan distance (the sum of the absolute values of the horizontal and the vertical distance). F: G + H ◆◆

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◆◆

Below are two sample steps of how A* algorithm is applied inside GamEducation.

Figure 3 A* algorithm applied inside GamEducation

Among the examined tiles, the one with the lowest F value will be picked. The enemy will move to this tile and it will be marked as ‘visited’ and be pushed into path vector. ‘Visited’ tiles are part of the path, hence, they will not be examined in the following checking. The process is repeated using the picked tile as start tile. After taking some steps, there are two situations that can happen: Found the end tile (player). Player takes damage. Enemy stops for a while. Cannot find a legal move (all adjacent tiles visited or blocked). It will backtrack the store path until it found a new shortest legal move. ◆◆

◆◆

Upon player’s movement, the destination tile will be updated and all the horizontal and vertical tiles of that tile will be marked ‘unvisited’. This is done in order to prevent problems such as: enemy moved all the tiles in one row, meaning all tiles in this row are visited, and the player and the enemy are on two sides of

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that row. This happens due to the fact that the player is always faster than the enemy, otherwise, it would be impossible for them to get away from the enemy. The enemy cannot pass this row since all tiles are visited. This leads to the following event whereby the enemy goes around all tiles possible until it backtracks. By setting tiles to ‘unvisited’ on player’s movement, it guarantees that there will always be a short path to the player instead of wondering around checking all tiles. 10 Preview created game Upon clicking ‘Preview’ button, all information currently provided by users will be stored in the static variables and a new play screen will be created. 11 Save and publish the game Clicking on the ‘Save’ or ‘Publish’ button will store the current information in the server for later usage. ‘Save’ feature is used to save the current progress, users can continue on where they left previously. ‘Publish’ feature will publish the game to the gallery of our website.

2.3. Community GamEducation is a web-based game. In order to increase the interaction level, we implemented a community feature where users can sign up and interact with each other. Below is the list of features in the community: 1 Chat systems This is to allow the players to interact with each other during games. If a student encounters a problem that he/she is not able to solve, he/she can chat with either his/her fellow students or with the to get help in overcoming the problem. We hope this feature would help prevent students from isolating themselves while playing computer games. 2 Upload self-made image This is to allow the game to be more individualized. Students can create their own background for the game. They can also upload different images for resources and obstacles. 3 Upload self-made quiz (Student) This is a new idea that we think is important for learning. Instead of using only questions exercises provided by the teacher, we allow students to create and upload questions. As part of the incentives during the game, if the question uploaded by a student is not solved by other students, the creator of this question will score a high mark. To create a good question, students need to have a good understanding of the subject matter. Questions will need to be approved by the teacher before they are allowed to be uploaded to the question bank. 4 Approve quiz (Teacher) When students submit online their questions/exercises, the teacher will be

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notified about the submission and he/she will be able to view the questions and approve them if they are appropriate and correct. Otherwise, he/she could reject the question by informing the student giving them the reason for the rejection. 5 Quiz statistics This is the statistics about the quiz questions. Basically giving the teacher information about what topic the students are having problem so that he/she could take appropriate action to rectify the situation. For example, conducting remedial lesson to help students in that topic. 2.4 The Game Creation Process The following flowchart shows the game creation process Start Load User’s data Main Menu

Story Mode

Played before?

Yes

Current Stage Data

No Create Mode

Stage 1 Data

Got saved data? Yes

No

Load saved data?

No

Load Empty Data

Yes No

Retry?

No

Win?

Yes

Save Progress

Preview

Player’s Position?

Save

Save data and screenshot

Publish

Player’s Position?

Modify ‘Lives’ and ‘Time’ Create Screen

Add obstacles Add Characters

Next Stage

No

Choose Field

Yes

Load Saved Data

Play Screen

Yes

Preview Screen

Yes

No

Figure 4 game creation process

3 Conclusion The system is at the moment quite simple. It only provides a limited set of API for the children to create very simple game. But this is what we are trying to achieve. By giving something simple, children will not face a stiff learning curve in learning how to create a game. This will give them the confidence to do it. With the

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first step taken, we are hoping that they will become the next generation of game developers and have in mind about creating game that facilitates teaching and learning rather than making people waste their precious times.

References Ahmed S. K. (n.d). Internet socket. Retrieved April 9, 2014, from http://www.uotechnology.edu.iq/ce/Lectures/AhmedSaad-IT/part4.pdf Amir, J. (2014). Peer to Peer File Sharing Through WCF. Code Project. Retrieved April 9, 2014, from http://www.codeproject.com/Articles/614028/Peer-to-Peer-File-Sharing-Through-WCF Barlett, C. P. (2010). Video Game Effects – Confirmed, Suspected, and Speculative. Simulation & Gaming, 377—403. Becker, K. (2006). A Psycho-cultural Approach to Video Games. University of Calgary, Graduate Revision of Educational Research. Alberta: University of Calgary. Beswick, D. (n.d). Management Implications of the Interaction. University of Melbourne. Brewis, M. (2013). Candy Crush Saga review - the mobile game that’s deliciously addictive. Retrieved April 04, 2014, from TechAdvisor: http://www.pcadvisor.co.uk/reviews/google-android/3445581/candy-crush-saga-review/ Chuan, N.W. (2012). HoEonline – An interactive Educational Game: Multiplayer network design. Thesis. National University of Singapore, Singapore. Client-server architecture. (2014). In Encyclopaedia Britannica. Retrieved from http://www.britannica.com/EBchecked/topic/1366374/client-server-architecture 39 CNET. (2013, April 03). Candy Crush Saga for Android review: Great alternative to Bejeweled . Retrieved April 04, 2014, from CNET Web site: http://www.cnet.com/products/candy-crush-saga-android/ Dondlinger, M. J. (2007). Educational Video Game Design: A review of the Literature. Journal of Applied Educational Technology, 4, 1—11. Correia, A.C. (2011). Computer Games as Educational and Management Tools. In The Educational Value of Digital Games: Possibilities and LIMITATIONS OF THE USE OF Digital Games as Educational Tools (pp. 86-102) Denis, G., & Jouvelot, P. (2005). Motivation-driven educational game design: applying best practices to music education. Paper presented at the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology, Valencia, Spain. Dickey, M. D. (2005). Three-dimensional virtual worlds and distance learning: Two case studies of Active Worlds as a medium for distance education. British Journal of Educational Technology, 36(3), 439—451. viii Din, F.S. (2011). The Effects of Playing Education Video Games on Kindergarten Achievement. Child Study Journal, pp 99—101. Dunn, J. (2012, October 24). Why Teachers Are (And Aren’t) Using Educational Video Games. Edudemic. Retrieved April 9, 2014, from http://www.edudemic.com/why-teachers-are-and-arent-using-educational-videos-games/ ESA. (2013). Essential facts about the computer and video game industry. http://www.theesa.com/facts/pdfs/esa_ef_2013.pdf GameStar Mechanic Group. (2013). GameStar Mechanic Profile. Retrieved April 4, 2014, from Schoology Web site: https://www.schoology.com/apps/profile/35357735 Gamua Corporation Web site. (2013, Nov 3). Startling - The Open Source Game Engine for Flash. Retrieved Nov 3, 2013, from Gamua Corporation Web site: http://gamua.com/starling/ Gee, J. P. (2003). What Video Games Have to Teach Us About Learning and Literacy. New York: Palgrave/Macmillan. Gee, J. P. (2005). Good Video Games and Good Learning. Phi Kappa Phi Forum, 85, pp. 33-37. Hall, B.J. (2012). Beej’s Guide to Network Programming Using Internet Sockets. Retrieved April 9, 2014, from http://beej.us/guide/bgnet/output/html/singlepage/bgnet.html Jenkins, H. (1998). Complete Freedom of Movement: Video Games as Gendered Play Spaces. In H. Jenkins, & J. Cassell, From Barbie to Mortal Kombat (pp. 262—297). Cambridge: The MIT Press. Jennings, M. (2001). Best practices in corporate training and the role of aesthetics: Interviews with eight experts. Paper presented at the 2001 ACM SIGCPR Conference on Computer Personnel Research, San Diego, CA. Juul, J. (2007). Without a goal. In T. Krzywinska & B. Atkins (eds): Videogame/Player/Text. Manchester: Manchester University Press. http://www.jesperjuul.net/text/withoutagoal Juul, J. (2007). Swap Adjacent Gems to Make Sets of Three: A History of Matching Tile Games. Artifact Journal, 2, IX Juul, J. (2011). Half-Real: Video Games Between Real Rules and Fictional Worlds. Cambridge: MIT Press. Klopfer, S. O. (2009). Moving Learning Games Forward: Obstacles Opportunities & Openness. MIT. Klosowski, T. (2013). Hopscotch HD Introduces Kids to Programming. Retrieved April 4, 2014, from Lifehacker web site. Nair, J. (2004, July 26). Asynchronous Socket Programming in C#. Code guru. Retrieved April 9, 2014, from http://www. codeguru.com/csharp/csharp/cs_misc/sampleprograms/article.php/c7695/Asynchronous-Socket-Programming in-C-Part-I.htm

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National Intrument. (2012). Building Networked Applications with the LabWindows™/CVI UDP Support Library. Retrieved April 9, 2014, from http://www.ni.com/white-paper/6723/en Neumann, C., Prigent, N., Varvello, M., & Suh, K. (2014). Challenges in Peer-to-Peer Gaming. Retrieved April 9, 2014, from http://ccr.sigcomm.org/online/files/p79-v37n1p-neumann.pdf Lenhart, A. K. (2008). Teens, Videogames and Civics. Retrieved Nov 4, 2013, from Pew Internet: http://www.pewinternet.org/Reports/2008/Teens-Video-Games-and-Civics.aspx Rex, V.D.S (2012). Foundation Game Design with Actionscript 3.0 (second Edition), 331-387. Raise Smart Kid. (2013). The Positive and Negative Effects of Video Games. Retrieved Nov 3, 2013, from Raise Smart Kid:http://www.raisesmartkid.com/3-to-6-years-old/4-articles/34-the-good-and-bad-effects-of-video-games Rosewater, M. (n.d). Timmy, Johnny, and Spike. Retrieved September 7, 2012, from Wizards of the Coast: http://www. wizards.com/Magic/Magazine/Article.aspx?x=mtgcom/daily/mr11b Shapiro, J. (2013, Febuary 18). How Game-based Learning can Save the Humanities. Retrieved April 4, 2014, from Forbe Web site:http://www.forbes.com/sites/jordanshapiro/2013/02/18/how-game-based-learning-can-save-the-humanities/ Sharma, H. (2013). How to Learn Starling Framework. Retrieved 4 Nov, 2013 from Gamedevtut+: http://gamedev.tutsplus.com/articles/how-to-learn/how-to-learn-starling-framework/

Author/Contact Sun–Teck Tan School of Computing, National University of Singapore [email protected]

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The Relation Between Individual, Collective and Organisational Learning Through Business Games in the Management Field Luiz Antonio Titton

Abstract Three stakeholders — business schools, students, and businesses — have the same objective: a prepared workforce ready to work after some years of dedication. These stakeholders work together without formal communication. There is evidence that undergraduate students perceive a weak match between the skills obtained from their degree and those required by employers (LaPrince, 2013). The employment level for students after the course depends on the alignment of the competencies offered with those desired by employers. Within this context, this paper presents business simulations as one of tools used by business schools to achieve the desire of these stakeholders. The objective of this research is to explore the students’ perceptions about their acquisition of knowledge, skills and attitudes, self-engagement and comprehension through the business game by comparing the first year and last year of the same course using the same instrument. The investigated perceptions have a direct relationship with the competencies associated with the employers’ and the students’ needs. From this research, it is possible to conclude students presented different perceptions about the use of the business games that are coherent with the timing in the course. It is remarkable the higher level of perception about acquisition of knowledge in the first-year students and higher order thinking skills in the last-year students. This result could be a starting point for understanding and designing future research about the timing and purpose of this educational tool within the course. Keywords Business game; management learning; employability

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1 Introduction Business schools are part of a system providing a service that prepares the future workforce for corporations. The raw material is the human subject, starting as the first-year student. This scenario shows three stakeholders — business schools, students, and businesses — with the same objective: a prepared workforce ready to work after some years of dedication. However, it is not clear if there is alignment in the emphasis on the primary competences valued by each of these stakeholders. Three levels of learning affect these stakeholders: individual, collective and organisational learning. Individual learning refers to the students who expect to obtain knowledge leading to their greater employability. We could say that this is the scholar phase, where the adult learner is a person looking for knowledge that will represent a concrete result. It is not learning for the distant and unclear future — it represents a successful professional future. For a long period of dedication within the course, the students share a self-development process connected to their common interest in being prepared for their future lives. The classroom is a context in which people are motivated to take things seriously and where there is involvement. The classroom has a collective force that involves social pressure focused on their learning objective. The use of business games offers the opportunity to work together in a virtual reality that is quite close to a future professional life, and a sense of collaborative learning may arise not only within the teams but also within the entire classroom. In this context, business games can be used for collective learning. Collective learning in business schools seeks to provide future professionals with better preparation in desired competencies such as leadership, communication, team-work, relationship building, influencing, persuading — which are all developed by experiencing together how to solve problems and see the ‘bigger picture’. Businesses want employees with outstanding performance appraisals and these skills can be developed through business games. These stakeholders work together without formal communication. Students do not clearly express which competencies they expect from the business school. Businesses also do not ask the business schools if they can provide the competencies needed. All organizations are part of a society where an invisible hand directs the role of each stakeholder in the bigger objective. However, there is organisational learning after each success or failure in the process. The finished good — the graduated citizen — needs to get a job and to be successful in it. Businesses need a prepared workforce to play their role in society. Again, the invisible hand directs organisational learning to provide policies to the business schools; this organisational learning comes from social pressure for results. However, the system described is not perfect. There is evidence that undergraduate students perceive a weak match between the skills obtained from their degree and those required by employers (LaPrince, 2013). The employment level

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for students after the course depends on the alignment of the competencies offered with those desired by employers. Within this context, this paper presents business simulations as one of tools used by business schools to achieve the desire of these stakeholders

2 Competencies and employability One of the primary concerns of students is future employability. Among the many definitions about what is employability, the Enhancing Student Employability Co-ordination Team defines it as a set of achievements — skills, understandings and personal attributes — that makes graduates more likely to gain employment and be successful in their chosen occupations, which benefits themselves, the workforce, the community and the economy (Yorke, 2004). The mission of business schools is to prepare their students for employment after graduation. Although this objective is pursued throughout the course, we can conjecture about the possible factors indicating discrepancies between the competencies emphasised by the business school curricula and those valued by businesses (Abraham & Karns, 2009). The insertion of the business simulation in a competence oriented view is not new. The Competency-Oriented Business Simulations (COBS) is a framework developed to the training of civil engineering students and professionals. It is intended to inspire other areas and is designed as universally applicable as possible to allow the transferability to other domains (Karl, 2012). However, it is remarkable that business-schools do not emphasise competences in a uniform way to enable the production of business games that could attend all curricula. This fact makes imperative that each business game should be designed for each specific business-school to attend the COBS framework. Research was conducted concerning competencies and addressing the three stakeholders in the management field. The first stage identified 23 competencies that were in use by organisations as part of their performance appraisal programs for managerial employees. The second research stage addressed whether businesses and business schools agree on which competencies are important and are indicative of successful employees. The first stage research investigated 277 usable surveys resulting from a mailing sent to 2,500 organisations that are potential employers of management graduates. The most critical competencies identified are “communication skills, problem solver, results oriented, interpersonal skills and customer focus” (Abraham, Karns, Shaw & Mena, 2001; p. 850) .

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The second stage research resulted from 42 respondents out of 200 business schools chosen at random in Canada and United States. This research used the 23 competencies cited in the first stage. It found consistency between the two studies. However, it also identified discrepancies in the attributed relevance of the competencies between business and business schools. In other words, business schools emphasise competencies they deemed relevant but they are not consistent with what businesses deem to be relevant for their future employees. “There were eight competencies for which the difference between business and schools was greater than 20%: “customer focus, interpersonal skills, dependable, flexible/adaptable, staff developer, results oriented, quality focused and risk taker” (Abraham & Karns, 2009, p. 353) The objective of this long-term research was not to identify why these discrepancies exist. It was conjectured by the researchers that business respondents may focus on those competencies that lead to success in the business, whereas business schools respondents may have a wider focus that develops students in many degree paths to a more generalised concept of managerial competencies with focus on technical skill development and general education requirements across the curriculum (Abraham & Karns, 2009). Many skills overlap with one another. One could argue that skills are interdependent because of the mutual dependence on common skills. Furthermore, improving one skill may also improve a number of others (Prabhavathi, 2013). At the same time, it was noticeable that corporations prefer to recruit among candidates that offer more than formal learning — they want an experienced workforce. Furthermore, it is expected that employers also direct their selection procedures to the function that the employee will occupy in the company; however, this goes beyond the issue of competencies. Reflecting the need to establish a linkage between educational institutions and the labour market, the European Union sponsored the MISLEM Project to develop meta-level quality indicators. As part of this effort, a manual was produced for the project about education, employment and graduate employability. The project involved representatives from Higher and Vocational Education in four partner countries, Austria, Romania, Slovenia and the United Kingdom, and representatives from a major UK graduate employment agency and the Austria Quality Assurance Agency. The research survey was answered by 304 employers and 596 graduates to produce analysis that linked competencies with disciplines. This report identified and conceptualised the key employability competencies required by employers of business graduates. It also identified the extent to which key employability competencies are acquired by business graduates during study at the undergraduate level and are being used in employment (Andrews & Higson, 2007).

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Table 1 Competencies valued by graduates and employers to assist a transition from Education to Employment (Andrews & Higson, 2007) Competencies valued to employment

Competencies

Definition

Communication skills

The ability to communicate clearly and concisely, using a range of verbal and written methods

94

96

Team-working and relationship building abilities

The ability to work in teams and to utilise appropriate interpersonal skills to build relationships with colleagues, team members and external stakeholders

92

85

Self and time management

The ability to organise oneself, one’s time and one’s schedule effectively in any given work-related situation

92

82

Ability to see the ‘bigger picture’

The ability to see how things are interconnected and to approach work-related issues in a strategic and innovative manner

88

74

Influencing and persuading abilities

The ability to communicate at all levels using influencing techniques and negotiation skills to positively influence others

86

78

Problems solving abilities

The ability to analyse problems and situations in a critical and logical manner and to apply workable and logical solutions to such problems

86

75

Leadership abilities

The ability to lead a team whilst taking responsibility for a task, giving direction, providing structure and assigning responsibility to others

75

60

Presentation skills

The ability to prepare and deliver effective presentations to different audiences in a wide-range of circumstances

74

88

By By graduates (%) employers (%)

Although the report does not attempt to identify the discrepancies, Table 1 shows that the competencies valued by graduates and employers reflect the same aspects. It is expected that as students proceed through their undergraduate careers, their discipline-specific knowledge will develop along with their employability competencies as described. One key identified during the MISLEM Project that differs from previous research is the ability to see the ‘bigger picture’. This ability tends to be developed gradually as students’ integrate discipline-specific knowledge and skills with employability competencies and other life experiences (Andrews & Higson, 2007). Various learning and teaching strategies may be utilised to promote student competency in this area, including an emphasis on ‘contextual’ learning strategies, case-study learning techniques, critical and analytical essay writing, ‘real-life’ focused assignments and projects, and work-based learning (Andrews & Higson, 2007). The MISLEM Project cites ‘business games’ as a learning technique to develop these competencies: teamwork and relationship building, ability to see the ‘bigger picture’, influencing and persuading; and leadership (Andrews & Higson, 2007).

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Simulations and business games are a hot topic at the student, academic and corporate levels, especially as we consider the need to practice the concepts learned through the course. Business games are tools that connect theory and practice, and they can be used to create the tacit knowledge that moves academics closer to business reality. It is possible that the MISLEM project considered business games within the development of competencies, but these can also be developed by how the professor conducts the activity. Debriefing is considered to be part of business game activities. Debriefing is the reflexive time during which students evaluate their decisions, matching reality and theory to rethink their choices and analyse consequences. At this moment, tacit knowledge is produced. If we consider part of the business game technique to be the presentation of a performance analysis completed by each team for a debriefing session performed at each round, other competencies such as communication skills and presentation skills will also be developed. The value of the debriefing is consolidated, and this manner of debriefing by having students present their reflexions is a good option (Bascoul, Schmitt, Rasolofoarison, Chamberlain, & Lee, 2013; Salas, Wildman, & Piccolo, 2009). The competency of ‘self and time management’ is also developed naturally in business games because each member of the team is responsible for the time scheduled for decisions and their input in the system. Time pressure is created by conditions that entrepreneurs are likely to encounter (Corbett, 2005). The last competency that was not linked to possible development through business games is ‘problem solving ability’. In fact, experiential learning develops the capability to solve problems in a trial-and-error manner, as is done in a business game (Kolb, 1984). However, business games are not the only technique through which students can be in touch with real-life business experiences.

3 Real-life options to link business schools and business Business schools appear to be very limited in offering experience to their students. From a general point of view, business schools can offer three paths for accessing experience closer to the real management world: junior enterprises, internships and virtual laboratories. The first path, junior enterprises, are local organisations managed by students. They offer consulting services to the market related to their field of study. Junior enterprises are linked to a university or a higher education institution and obtain support from them, not only financial but primarily access to experienced teachers who drive the general conception of each consulting service. The junior enterprise concept started in France in the 1960’s, but by 20 years later had spread, reaching Switzerland (1983), Italy (1988), Brazil (1988), and Austria (1989). The ju-

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nior enterprise concept spread worldwide after the creation of the European Confederation of Junior Enterprises (JADE) (1992). The second path, internship, is a method of on-the-job training in which students work in a company for between a few months and a full year. The general concept is that through an internship, students can put into practice the knowledge learned in their courses. Students can use this method to help determine their interest in a particular career. Although internships also allow students some financial earnings, the objective is to keep them in touch with business reality. Finally, virtual laboratories are one or more simulators in which students can manage virtual companies as if they were in the real business world. It is difficult or quite impossible to leave students managing a company just to learn. For this reason, virtual laboratories gains relevance. Generally, these simulated worlds are competitive in that teams compete among themselves for the best performance. Business games are the most common instrument in these laboratories, but simulations that are not games can also be used to experience specific concepts without the competitive context. All three options should be offered to students because each has intrinsic good characteristics. However, we could argue that each may also have some questionable aspects. Based on my own experience with these options, I could propose some questions about them. Junior enterprises cannot offer consulting activities with the best timing and depth for each student. In fact, the themes and subjects are offered by companies based on their timing and are not attached to the students’ needs. Furthermore, after the end of the consultancy work, there is no monitoring of the consequences, i.e., there is no commitment to follow-up activities within the company or with the student. The student is limited to providing the service and, in a few cases, produces an internal junior enterprise report. This process represents a lost opportunity to researchers because possible empirical data could be obtained from these consulting services, which are generally based on theoretical academic knowledge. This lack of commitment may also occur in internships — the second path. The student enters a company to apply learned theory but finds a context in which he is an aspirant to a trainee. Very few companies offer a structured program for internships. In some extreme, but not rare, cases, the student works in routine tasks that require no technical knowledge such as transcribing data. I was in contact with a case where the student had an internship in a building company, and his job was to register production controls in the building area. The student was working in a container with no air conditioning and no ventilation under an average temperature of 30 degrees Celsius. This situation was noticed by the school only after months of conditions close to slavery. Some companies hire interns as an option for obtaining a cheap workforce.

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The third path — business games — may be attacked for lack of fidelity with the real business world or for an extreme fidelity that goes beyond human comprehension. The complexity paradox is a dilemma: if you try to include all elements from reality in the simulator, it becomes too complex and difficult to understand. However, the simplicity paradox occurs when the model is simplified in a way so that it lacks realism and disconnects theory from reality (Cannon, Friesen, Lawrence, & Feinstein, 2009). The worst case in business simulations is when invalid internal constructs are used. Business games based on false theories can lead to a misunderstanding of these theories. As an example, a simulator that generates product demand on a random basis ignores all economic theory, disables marketing actions and may lead the student to believe that the business world is a gamble. From the point of view of collaborative learning, junior enterprises and business games are a good option to motivate students as they work as a team. However, this condition is difficult to obtain in an internship program if the company has no commitment to teamwork. Among these three paths, this research focuses on business games that have internal constructs that are fully based on the theories adopted by the business schools. Using the virtual world in the first year of an undergraduate course could be considered to be a good choice because it can promote motivation over the subsequent years. Furthermore, it could be a good idea to use business games at the end of the course to provide an opportunity to experiment with the theory learned throughout the course. However, these thoughts comes from the professor’s desk and should be analysed against the students’ perceived needs when facing recruitment and selection for a job after graduation.

4 Rising expectations from new graduates The scientific approach uses frameworks to analyse how students perceive their own level of employability. It is known that students bring knowledge, skills and abilities (KSA) from previous experience to the learning environment. Along the course, not only is new KSA expected but also the acquisition of Higher Order Thinking (HOT) skills, meaning the ability to evaluate, synthesise and analyse. This analysis is based on Bloom’s taxonomy, which is used to produce a framework in which KSA is extended to encompass job expectations. Ramaswamy et al. (2008) used KSA as a starting point to understand how HOT skills are developed throughout the course (Ramaswamy et al., 2008). For this reason, the survey starts from this framework — KSA to HOT — as it is perceived in a business game and to compare these perceptions between the first-year and last-year students in an undergraduate business course. The combi-

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nation of Blooms’ taxonomy with employer expectations was the basis for a model created by Ramaswamy et al. (2008). This model proposes that future graduates expect to gain business, team, communication and technical skills to provide critical thinking, problem solving, abstraction and teamwork (Ramaswamy et al., 2008). The broader field of gaming addresses questions that go beyond the limited scope of game theory. It addresses organisational action and social change that easily cross knowledge domains. It draws from the social sciences, humanities, and engineering (in particular information technology) faculties that for various reasons question its added value. The paradox is that the weakness of gaming in academia is its strength in practice. Gaming is influential in the development of knowledge and experience with practical issues (Klabbers, 2009, p. 144). For this reason, the continuous investigation of the organisational role played by the business game as an educational technique remains relevant. From this systemic point of view, the business game is aligned with the development of competencies desired by stakeholders. What needs to be researched is the perceptions of students on the utility of the experience, considering its timing within the course. Motivation is one subject to be address by considering timing; different timing for business games within the course might affect motivation. In fact, studies show that the transition to higher education can be problematic (Andrews & Higson, 2007; Lawson, Fallshaw, Papadopoulos, Taylor, & Zanko, 2011; Weitz, 2011). First-year students are transitioning into a stage and a new school context that is directed toward adult learners with an accompanying change in teaching styles. It is not uncommon for undergraduate courses to start with an over-concentration on textbook activities. This focus sometimes leads students not only to be unexcited and unmotivated but also to be unable to apply the concepts learned to real scenarios. This focus on textbooks can also create graduates with poor employability skills. This concern may be greater for those students who present a lesser capacity for quiet study and who need challenging activities. In some areas such as engineering, it is known that ‘education requires integration of knowledge with practical skills, and this can only be achieved through implementation and realisation’ (Willmot & Perkin, 2011). Business courses are not so different. From this point of view, business games can be used at any time within the course. However, to establish this option as a rule, it would be necessary to produce curricular changes that include business games as a permanent activity within the course. In fact, it is difficult to believe this change is a concrete option for any business school. Furthermore, technical merit is not generally enough to justify curricular changes: ‘innovation persistence is negatively influenced by

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exogenous factors that disrupt the self-reinforcing relationship between structure and political action’ (Thompson & Purdy, 2009). However, the disrupted perception of the transition from learners to professionals cannot be the only reason to become strongly innovative in the academic curriculum to attend to employers’ needs — there must be a learning structure in the curriculum. The transition from academy to professional field is also not easy. Students that show strong technical skills may find it difficult to adapt to the environment of industry. The role of universities is not only to develop graduate attributes and capabilities but also to be responsive to the changing business environment, which includes improved business practices. However, the ‘student learning culture can be a particular challenge as many students do not fully engage in their education’. There is a significant portion of students who spend extra hours in paid employment and see ‘learning and work as unconnected activities’ (Lawson et al., 2011). The problem maybe one of defining engagement, which is not defined by a consensus in the academic literature (Willmot & Perkin, 2011). ‘Engagement refers to the amount of motivation, involvement, and interest that students dedicate to the task or situation, at an emotional, cognitive, and behavioural level’ (Kern & Thompson, 2005). For the purposes of this work, what matters is that it appears to be relevant to offer more than textbook activities at the beginning of the course. Therefore, engagement will be used here to refer to the declared involvement of the student. It must be recognised that involvement is a culturally dependent aspect regarding the stage in the course — first or last year. In other words, depending on the country, motivation may vary within the course because of the cultural context (Isiksal, 2010). The student at the end of the course — in the last year — needs to show practical experience after completing his or her academic formation and wants to show the characteristics desired by future employers. Business games are included as an option to meet this need.

5 Methods This research investigates the business game as an educational instrument used to connect theory and practice. The other modalities — junior enterprises and internships — are not the focus of this research. The objective of this research is to explore the students’ perceptions about their acquisition of knowledge, skills and attitudes, self-engagement and comprehension through the business game by comparing the first year and last year of the same course using the same instrument. These investigated perceptions have a direct relationship with the competencies associated with the employers’ and

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the students’ needs. It is an option to compare these two groups with different background to explore these aspects as an exploratory research to catch initial aspects to future researches directed to understand the use of business simulations along the management course to contribute to understanding the timing and purpose of educational games within a course regarding the whole curriculum. The research question is as follows: if it is good to use business games techniques within a management course, can they be used at any time? Or there is one opportunity better than another? If we apply the same example at the beginning of the course, will it work as well as at the end of the course? If the business game is used at the beginning of the management course, the students will have scarcely enough information about management techniques to gain benefits that are aligned to their needs. Can the complexity and theory used in depth by the game be applied at any time in the course? In this research, one unique business game was used at the same time in a first year class and in the final 6 months of a class (last year class) in a business school. This game is not too complex nor too simple, so that both groups of students could feel comfortable with its complexity level. To achieve comparable results, not only was the same business game used but also all other conditions were kept as similar as possible. Therefore, the same classroom, professor and simulator scenario were used. The students could talk to each other about the game, and so to prevent asynchronous advantages in the game, all rounds were processed on the same day for both classes. All briefings and explanations about the simulation were conducted equally for the two classes, and after the game was over, the same survey was applied to both classes on the last day. At the beginning of the class, the students were told about the research goal of comparing perceptions about the game across the two classes, and the research subject was presented again before the survey to remind them of the need for honesty. No obligation or bonus was offered for survey participation. The primary concept behind the game was to experience management in virtual reality using the business game. It was emphasised that the two classes were using the same game and that it would be interesting if the first-year teams had better performance than the second-year teams. This additional challenge was issued with the goal of promoting collective collaboration among the teams in the same class. The performance assessment of the students must be performed individually, and it was established as a criteria that performance in the game would increase the final evaluation instead of being used as part of it. Two written examinations about the general theoretical concepts used by the game were applied; these did not evaluate the use of the game. The business game used is the General Management Game (Titton, 2010). It is web-based under cloud computing (Byrne, Heavey, & Byrne, 2010), compu-

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ter-assisted (Crookall, Martin, Saunders & Coote, 1986), and clock-and-activity driven (Chiesl, 1990). The web-based simulation allows services to be rented for an interval of time such as in an Application Service Provider (ASP) or Software as a Service (SaaS) environment; this business model can solve previously prohibitive factors such as installing software in the business school’s internal net, and it results in savings in cost and time. SaaS is a business model that delivers software to the end user as a service instead of as packaged software that requires local installation. In cloud computing, information is permanently stored in servers on the internet and cached temporarily on clients. This game offers students the opportunity to directly work with the system in the cloud, accessing recent documentation, automatically accessing upgraded versions, participating in an internal forum that is private to the teams and public to the class, accessing an internal area to chat with others in the team or with the entire class, accessing public data from other virtual companies, and some other features that were possible only by virtue of being hosted in the cloud. However, the web-based simulators currently make use of SaaS and cloud computing only to deploy applications, and no possible further uses are identified (Byrne et al., 2010). Because of these characteristics, all decisions can be discussed anytime and anywhere by the participants — synchronously or asynchronously — although in this research, decisions were made in the classroom. This business game was developed before the recent researches about competency-oriented business simulation (COBS) that can be defined as follows: A competency-oriented business simulation is aligned in each phase to a valid and reliably developed, target group-oriented competency model. This model should motivate participants to develop specific capacities to act due to experience acquired in a realistic setting with conflicts and problems. The goal is to apply these specific capacities to act responsibly and successfully in a real and competitive context. (Karl, 2012, p. 37) Despite of this fact, the sample development took care about competency orientation because of its attachment to a specific didactic program of the business-school where it is used. The goal of this game is to be designed to be used in the first year of the course to motivate students about management and to promote systemic view of the main functions of management such as human resources, marketing, finance, operations and general management. The last-year students experience objective is defined by the business-school to promote the knowledge consolidation by using a business game. The structure of activities is in Figure 1: presentation, repetitive cycles and results.

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Briefing Students knows the simulator and scenário

Final debriefing Teams make decisions

Process the system

Analyse data

Strategic planning

Analyse results and strategies Connect decisions, results and theory

Revise the plan?

Debriefing

Testimonies

The team analyze and compare with the expected results

Figure 1 Dynamics of the business game activities

Although there exists latest models to represent the structure of the activities as Klabbers’ magic circle (Klabbers, 2009), the original structure is presented because it is the current model adopted by the business game. This business game development used this ancient but traditional model. In this business game, four participants occupy the board as the president and directors of finance, marketing and operations. All decisions are discussed in groups and input into the system individually by each participant. The board makes various decisions for the current brands and can issue new brands of the product, decides whether to buy the products from third parties or to produce internally, manages their financial resources, manages human resources, and makes other common corporate decisions associated with general management. The strategic analysis and decisions are discussed every round because all virtual companies compete in the same virtual economy. The business game can be conducted in Portuguese and English, which was important because some students were from other countries and the first-year students were not completely proficient in Portuguese. At the first round, a briefing about the game was presented, including how it works, how to input decisions and what happens during processing. The primary theoretical aspects were presented. For the first-year students, the content was new, and for the last-year students, it was a review of what had already been learned in previous disciplines. The teams were registered in the system and decisions were taken in the classroom for both classes. The classroom has computers for every student, and each team used its own table. After the briefing, the repetitive rounds started. At each round, we started the class with a debriefing of the results from the previous round, discussion in the teams and the new input of decisions. The debriefing was performed looking

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for collaborative learning opportunities focused on how to improve game performance considering not only each team but also the level of performance for each class. The two sub-populations were informed without details about the other’s performance. This approach is not new; previous research comparing team sizes in a population of students from Hong Kong and the United States also allowed sub-populations to compare their performance to benchmarks from the other group to promote friendly rivalry (Travikulwat & Chang, 2010). This approach increased the collaborative work among the teams in the same class. This increase in collaboration was newly detected; business games in previous years had spurred competition among the teams in the same classroom and always provided a sense of opposition between the teams. For the first time, members of different teams helped each other with usability aspects and some general ideas about how to increase performance. It is acknowledged that students try to cheat in these games, and I suspect that some little tips about how to cheat the game were also exchanged among the teams. This survey was based on a previous survey used to analyse motivation among students as they participate in a business game activity. The decision to use the same survey was taken after recognising that it was tested over years in a long-term project and has become a standard for research on this area in Brazil, where this research was performed. The research was conducted with a first-year class with 37 students and a last-year class with 45 students answering the survey. In the first sub-population, 3 students did not answer, and in the other class, 4 students did not answer. There was no obligation to participate in any class. The business school where the research was performed is a reputable business school in Brazil. The course year is divided in two parts with 15 classes each. The first-year students had already completed the first semester (first part of the year), and for the last-year students, this was their last semester. The first-year students had some disciplines that had transmitted basic knowledge about management and organisations, so they were not completely unaware of business theories.

6 Data The first-year students were presented the business game for the first time, except for one student who was in the discipline for a second time and another that knew it from the previous level of studies. All students in the last-year class were already familiar with business games because they were part of the first year of the same course. Three groups of questions were asked for each of the three KSA dimensions to capture the intensity of benefits from the business game activities. Regarding knowledge, they were asked about their perception of (a) ‘new knowledge

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acquisition’, (b) ‘knowledge integration’ and(c) ‘knowledge updating’. Regarding abilities, questions were asked about the benefits from (d) ‘practising problem analysis’, (e) ‘practising decision making’ and (f) ‘practising result control’. Finally, the behaviour benefits were explored in terms of (g) ‘adapt to new contexts’, (h)’search to explain the results’ and(i) ‘make analogies to the job’. For each question, students were asked to tick the intensity of the benefits for the item from 1 to 6 on a Likert scale, with ‘1’ identified as ‘low’ and ‘6’ identified as ‘high’. These data can be seen in Table 2: Table 2 Knowledge, skills and abilities intensity of benefits (1-6 scale) Class

1st-year students

Last-year students

Data

Knowledge a

b

Average

4,49

4.59

Standard deviation

1.10

0.98

Skills c

d

e

4.19

4.51

1.37

1.22

Abilities f

g

h

i

4.76

4.44

4.81

4.59

4.43

0.95

1.11

0.92

1.01

1.12

Average

3.91

4.60

3.76

4.56

5.00

4.53

4.18

4.69

4.31

Standard deviation

1.40

1.32

1.46

1.22

1.17

1.31

1.47

1.18

1.24

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It is interesting to notice that the first-year’s perceptions regarding the search to explain results and make analogies to the job was higher. Meanwhile, the last-year students’ perceptions about adapting to new contexts was higher than the first-year students. However, both groups of students presented low level of perception regarding the benefits on this topic. The next topic investigated addressed involvement; the results are shown in Table 3. The investigation of engagement was made difficult by the lack of a conclusive definition about what engagement is in the scientific literature (Willmot & Perkin, 2011). This problem could be transferred to the survey and prejudice the real intention about the question, which refers to how the self feels about involvement in the activity. The question used to evaluate engagement was ‘indicate the intensity of your involvement at the phases’: (a) ‘initial presentation’, (b) ‘business simulation’ and(c) ‘results evaluation’. Table 3 Self-declared intensity of involvement

Class

In the first group of questions in Table 2 — knowledge — the highest average in the first-year students shows that despite the fact that the business game was not designed to transfer new knowledge, the perception regarding the acquisition and integration of knowledge was significant. However, the last-year students indicated the aspect of knowledge integration as the significant benefit from the business game experience. Note that knowledge integration had the lowest standard deviation. It is relevant that the first-year students showed a higher cohesion of opinions measured by the lower standard deviation. It is remarkable that both groups of students presented quite the same level of perception regarding the benefits of ‘knowledge integration’ (b). The second group of questions in Table 2 addresses the perceived intensity of benefits associated with skills. The three questions focus on the practice of knowledge, asking about the intensity of benefits perceived from the ‘practice of problem solving’, the ‘practice of decision taking’ and the ‘practice of result control’. Based on the data, it is clear that there is a consensus that the business game is useful because it provides a virtual environment in which to practice skills. Both groups presented quite similar averages and standard deviations for this aspect. The third group of questions in Table 2 refer to abilities, asking about the perceived intensity of benefits from learning to ‘adapt to new contexts’, ‘search to explain results’ and ‘make analogies to the job’. The first question was more highly evaluated by the first-year students.

Self-declared intensity of involvement

Data

1st-year students

Last-year students

a

B

c

Average

4,54

4,62

4,38

Standard deviation

1,12

0,89

0,92

Average

4,13

4,51

4,73

Standard deviation

1,46

1,20

1,21

It can be noted in Table 3 that the involvement of the last-year students in the initial presentation and the activity itself was lower than the other group. However, the involvement of the last-year sub-population was higher in the ‘results evaluation’ activities; however, ‘results evaluation’ also presents a higher standard deviation, which may suggest that some of these students did not follow the average. Another question aimed to catch the students’ perception of their engagement related to complexity and the technical-behavioural characteristics of the game. Three questions were presented with a scale from 1 to 6, ranging from “little” to “much”, asking how much they agree about potential changes to increase their involvement in the experience. The answers can be seen in Table 4: Table 4 Perceptions about what could increase involvement (scale 1-6) concerning the business game Class 1st-year students

Last-year students

Data

Agree Higher complexity

More technical

Average

2.29

2.86

More behavioural 3.95

Standard deviation

1.42

1.11

1.25

Average

3.34

3.34

3.82

Standard deviation

1.24

1.27

1.28

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The first question shows that the students do not perceive that increasing the complexity of the business game would produce more personal involvement. However, it is a fact that the last-year students show a slight preference that a somewhat more complex business game. The other two questions show that both groups of students would prefer more behavioural simulation. The last-year students also showed a slight preference for a more technical business simulation. Another group of questions regarded perceptions about what changes to the experience itself could increase involvement; these are presented in Table 5: Table 5 Perceptions about what could increase involvement (scale 1-6) concerning the experience Agree Class

Data

Longer duration

More participants

Participate again in this game

Participate in other games

1st-year students

Average

3,84

2,95

4,84

4,65

Standard deviation

1,24

1,37

1,26

1,42

Last-year students

Average

3,91

2,59

4,27

4,14

Standard deviation

1,54

1,34

1,35

1,56

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Table 7 Declared comprehension about the game — continuous cycle Class

Table 6 Declared comprehension about the game — Presentation Class 1st-year students

Last-year students

Data

Presentation

Average

4,08

Standard deviation

1,23

Average

4,49

Standard deviation

1,27

After the presentation of the game, the continuous cycle begins and the management of the virtual company occurs. The comprehension of this phase is shown in Table 7:

Continuous cycle Decision

Management

3,73

4,03

1st-year students

Average Standard deviation

0,90

0,90

Last-year students

Average

4,42

4,22

Standard deviation

1,27

1,17

The last phase consists of analysing the data and evaluating the results. This last phase is the debriefing phase, and it occurs after each round in a retrospective view; at the end, a final evaluation occurs during which all of the activity is analysed. The aim of this phase is to connect decisions taken with results based on management theory. Table 8 Declared comprehension about the game-debriefing Class 1st-year students

These data affirm that the duration of activities was quite appropriate. Both disciplines had 15 classes — 100 minutes each per week — in the second semester of 2013, and 10 classes were designated to the game activities. The groups were formed by the students, so the size of the groups was based on their preferences, which explains why there was no significant need to have more participants. The indication about participating again in the game and other games was also interesting: this perspective was stronger in the first-year students. Another group of questions was asked concerning their self-understanding and comprehension about the game. The data are presented considering three time points for the activities: presentation, repetitive cycles and results. These phases were described previously as how these activities occurred (Figure 1).

Data

Last-year students

Data

Debriefing Retrospective

Final

Average

3,92

4,30

Standard deviation

1,12

0,97

Average

3,51

4,16

Standard deviation

1,20

1,17

7 Discussion The objective of this research is to explore students’ perceptions about how the business game influenced their acquisition of knowledge, skills and attitudes, self-engagement and comprehension by comparing first-year and last-year students in the same course using the same instrument. The research is relevant to understanding the role that business games play in developing the competencies needed by stakeholders in management education, providing individual, collective and organisational learning. From these data, it is possible to conclude that the two groups of students presented different perceptions about the use of the business games that are coherent with the timing in the course. The average intensity of benefits from the business game activity is 4.46, with a standard deviation of 1.09, which indicates that students perceived benefits from the use of this learning technique. This result could be a starting point for understanding and designing future research about the timing and purpose of this educational tool within the course. The benefits perceptions about business games indicate increment on employability at the end of the course.

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Both groups of students showed that the business game offered high intensity in terms of ‘knowledge integration’ (K), ‘decision making’ (S) and ‘making analogies to the job’ (A). It is remarkable that all students showed a preference for a more behavioural activity. The first-year students showed a slightly higher perception regarding the acquisition of new knowledge and its upgrade than the last-year students. The last-year students showed a higher perception of the benefits of the business game associated with knowledge acquisition, integration and upgrades. However, it is significant to note that first- and last-year students saw the same level of benefits from knowledge integration, with a higher score. It is relevant to note that the perception regarding analogies to the job was high for both groups, although it was higher in the first-year students. It is important to note that the higher level of complexity suggested by this group of students is somewhat consistent with the lower level of convergence for the question about ‘adapting to new contexts’, indicating that the need for a more complex game at the end of the course is concrete. It is expected that the last-year students would prefer a more complex business simulation. It must be remembered that the same business game with the same complexity level for the scenario was used in both classes. The finding that deserves attention is that both groups of students would prefer the experience to be more behavioural to increase their involvement. This result is an indication that, as adult learners, their perception is that the real job world needs not only technically well prepared workers but also particular behavioural skills — what these skills may be could not be investigated in this research, but this finding has a strong relationship to the employers’ point of view as cited previously in this paper. It is relevant to add that beyond these data, the long experience of the professor of these two classes offers an additional view on the general behaviour of the students. It was the first time that a collaborative climate was noticed among the teams in the same class. The effort to motivate the students by suggesting comparing the overall results of one class to another in the same year of the course is common to this researcher. However, it was observed that this approach had never before appeared to be motivating. For this class, information about how to do things or even how to make better decisions was exchanged among teams in the same class, despite the fact that these teams were competing for better performance in the same class; however, there was no way to register this change within the research, so it relies on the professor’s perception. This observation shows that the first-year students did not want to perform at a lower level than the last-year students. Further, the last-year students were concerned about being beaten by the beginners in the course. The creation of a real communal work context in the classroom is a signifi-

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cant aspect. This collaborative mechanism led the students not only to work with the simulated company within the team but also to enrich their learning process by sharing their insights and experience. Considering only these data, it is possible to infer some points that cannot be generalised because of the reduced population researched; however, these can be indicators for future research. The first-year students showed great interest in the activity as a way to acquire knowledge (K) as well to develop skills (S) by practicing what was being learned in the course. The students from the last year perceived greater benefits from the business game regarding employability and less perceived benefit regarding the acquisition of knowledge (K). All students agreed with the benefits from acquiring abilities (A) by experiencing the business game activity. Engagement was measured by self-declaration regarding involvement. Both groups showed a high level of engagement, but involvement in the ‘results evaluation’ task was higher in the last-year students. This result may suggest that Higher Order Thinking skills, meaning evaluate, synthesise and analyse, may be present in this group. This suggestion is reinforced by the lower intention of the last-year students compared to the first-year students to participate again in this or other games, which suggests that these skills are already understood or the game is not as interesting as it was before. In terms of comprehension, the overall analysis suggests that the first-year students were really learning something new, while the last-year students showed less interest in the final debriefing because they appeared to understand the partial analysis already performed along the continuous cycles.

8 Conclusion In this paper, we have presented research conducted with two classes at a management course in a business school. One sub-population is formed by first-year students, and the other is formed by last-year students. The students’ perceptions about their acquisition of knowledge, skills and attitudes, self-engagement and comprehension through the business game is explored. Business game activities present different perceptions of benefits between the two groups, indicating that the game should be explored differently depending on the stage in the course. Although this research did not directly investigate perceptions of businesses — future employers — or of business schools, there is sufficient evidence about their needs in terms of competencies and the role of business games in the course. Based on the evidence presented in this paper, it is possible to conclude that learning in business schools through business games can meet organisational needs. This conclusion was inferred based on how this informal organisation, driven by management activities, perceives the student: a prepared workforce.

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Although the stakeholders in this system present a different emphasis on the primary competencies listed in Table 1, all of these competencies are developed through business games. This conclusion confirms the need to use business games in business schools; the differing emphases do not affect the utility of this apparatus in the courses. In other words, business games are useful independent of whether the emphasis is placed on one or another competency. This research demonstrates that it is possible to promote collective learning by adding new elements to the intra-class competition. A friendly competition between the first and last year was added, and one suggestion is that in future research, business managers could participate together and compete with the business school groups. This situation could extend collective learning to organisational learning. Very little has been discovered about what employers could learn by using business games, and this work suggests they can benefit from joint participation in this activity. From this research, it is possible to conclude students presented different perceptions about the use of the business games that are coherent with the timing in the course. It is remarkable the higher level of perception about acquisition of knowledge in the first-year students and higher order thinking skills in the last-year students. This result could be a starting point for understanding and designing future research about the timing and purpose of this educational tool within the course.

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