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Using Collaboration Strategies to Support the Monitoring of Online Collaborative Learning Activity Thanasis Daradoumis1, Angel A. Juan1, Fernando Lera-López2, and Javier Faulin2 1

Computer Science, Multimedia and Telecommunication Studies, Open University of Catalonia 156 Rambla Poblenou, Barcelona, Spain [email protected], [email protected] 2 Dep. of Economics and Dep. of Statistics and OR, Public University of Navarre Campus Arrosadia, Pamplona, Spain [email protected], [email protected]

Abstract. This paper first discusses the importance of online education and highlights its main benefits and challenges. In this context, on the one hand, we argue the significance of monitoring students’ and groups’ activity in an online learning environment. On the other hand, we analyze the informational needs that should be covered by any monitoring information system. Finally, the paper goes a step further by proposing the use of collaboration strategies as a manner to improve monitoring and learning processes in computer-supported collaborative learning. Keywords: Monitoring Online Learning, Collaboration Strategies, ComputerSupported Collaborative Learning.

1 Introduction Online learning platforms provide useful possibilities in the new educational paradigm in which students are the active and the main responsible of their own learning process. Among other possibilities, students can use these learning platforms to obtain the course core materials, to carry out self-assessment tests or to perform individual and collaborative learning activities. Moreover, these online platforms offer further complementary educational resources and interactive ways of communication. Accordingly, teachers and instructors are responsible for designing the courses, guide and provide assistance to the students. Online education offers some significant advantages both to students and instructors. For instance, it allows students to freely fix the learning timetable according to their time limitations and requirements, have a flexible schedule and be also part-time students. They are encouraged to develop their autonomous work with all educational resources available in the platform [4]. It also favors a more interactive communication among students and between students and instructors. Consequently, collaborative and working-group activities are encouraged. Moreover, it promotes continuous evaluation processes through self-assessment tests, individual and group activities and projects, etc. [10]. Finally, e-learning technologies contribute to the M.D. Lytras et al. (Eds.): TECH-EDUCATION 2010, CCIS 73, pp. 271–277, 2010. © Springer-Verlag Berlin Heidelberg 2010

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development of technical skills and provide multiple representation of information, while technologies can help to significantly reduce the gap between theory and practice [13]. At the same time there are some important challenges and difficulties associated to the use of online learning platforms. On the one hand, there may be different levels of online and Internet skills among students of different age [6]. Consequently, students may have technical difficulties to properly follow the course [16]. The authorship veracity of the assignments and tasks developed by the online student is also a relevant problem [13]. On the other hand, online learning programs present higher dropout rates than face-to-face education programs [17]. Consequently, interactive communication needs to be facilitated and continuously encouraged by instructors. Moreover, instructors should provide just-in-time guidance and assistance to students' activities as well as frequent feedback and assessments on these activities [8]. This paper focuses on the latter issues.

2 Why Monitoring? As some authors have pointed out [14,15], in face-to-face learning environments instructors are able to obtain feedback on students’ learning experiences throughout face-to-face interactions with them, which facilitates a continuous evaluation of their teaching activities and programs. Thus, monitoring activities involve observing students’ behavior in the classroom and evaluating the effectiveness of pedagogical strategies throughout a continuous and visual feedback. However, in online environments this informal monitoring process is not possible and, therefore, instructors must look for other ways to obtain this information. To a great extend, this explains the growing interest in the analysis of the data collected by web servers in elearning environments. On the one hand, monitoring online students’ and groups’ activity can help anticipate problems such as students not participating in the proposed learning activities or even dropping out the course [8] as well as possible internal conflicts in groups with unbalanced distribution of tasks [7]. Also, this process provides clues to instructors about how to improve courses’ website, materials and even the communication process among all participants [1,2]. On the other hand, students can also benefit from this monitoring process, since they can have periodical feedback regarding their performance level as compared with the rest of the class [8]. These monitoring reports can have a significant and positive influence on student motivation as well as a positive impact on the final performance [7, 12]. Though the development of an information system for monitoring students’ and groups’ activity in an online environment is not a trivial task., it is a necessary endeavor, since it is otherwise very difficult and time consuming to have a clear vision of each student academic progression during the course.

3 Critical Information A first critical step in developing a monitoring information system is to determine which information should be available for each potential user. According to [14], it is possible to distinguish different actors as well as different information requirements:

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Information oriented towards instructors. Instructors should get more objective feedback in order to evaluate both the structure of their online course and its effectiveness on the learning process. Doing so, they can achieve better learning outcomes [1,2], such as find both the most effective and ineffective tasks; classify students into groups based on their guidance needs and their performance; personalize and customize courses as well as establish specific learning paths for each student or group of students; and, anticipate students with problems or even students at risk of dropping out the course. Information oriented towards students. Students receive recommendations about good learning experiences and specific suggestions based on their own previous activities and tasks or on the ones of their peers with a similar profile. Also, students should have access to reports regarding their performance as compared to the average group or class level [8]. Some empirical evidence has shown a positive influence of periodical feedback in student motivation and their final performance [10] as well as in the rate of dropouts [7]. Information oriented towards academic managers. The purpose here is to have parameters for improving courses’ quality in the mid- and long-term. This information should help educational institutions to gain a better organization of human and material resources, and to improve the overall quality of their academic offer.

After identifying the different agents and their informational needs, the information that should be provided through monitoring is classified according to three general criteria: background data, academic activity (access data and use of learning resources) and academic performance: •





Background data offer personal information about each student profile. Part of this information can be known previously such as gender, age or academy background, while other can be obtained through a short survey when the course starts (internet and computer skills, time availability, etc.). Academic activity collects all the information about the access data and the use of different learning resources. Online platforms usually record data about students’ actions and interactions into log files and databases [14]. Students’ usage statistics are often the starting point for evaluation and monitoring in an online e-learning environment [18]. During the online course, students carry out different activities: they post or read notes in forums, send or read e-mails, upload or download documents, send reports, complete self-assessments, etc. Each of these activities can be considered as an event of a certain type which has been carried out by a particular student at a certain time and web space. Academic performance is closely related to the web-base assessment. [11] suggested that assessment in online learning environments should integrated to instruction, be continuous and maximize feedback. Also, online assessment might help students in taking ownership of their learning and offer immediate and effective feedback to them. Then, online assessment systems could have more potential than paper-based assessment systems in terms of access and flexibility for students as well as for instructors. On the other hand, many online learning processes include team assessment task such as presentation,

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projects, case studies, reports, debates, etc. An issue in collaborative learning is to improve fairness of team assessment, which is essential to improve students’ learning from team tasks [5]. Consequently, if group leaders and group non-participant members could be identified, it could be possible to offer different rewards for different contributions in the team assessment. Regarding the characteristics and requirements that this information should meet, we consider the following basic principles: •

• •





Information should be relevant and easy-to-understand for instructors and students. Use of visual graphs and figures could provide immediate and easy interpretation of the desired information. In some cases, however, a more deep statistical analysis using data mining techniques may be needed. Information should be generated and transmitted personally and automatically by the system without any additional efforts from instructors. Information should be obtained just-in-time (e.g., weekly reports or after each assignment) and it should be directly sent to instructors and students by the system (email, RSS, etc.). Otherwise, it will not be possible to react on time and to find solutions to problems in advance. Information should be personalized according to individual profiles (e.g., students may receive a personalized feedback regarding academic activity and performance), link aggregated and individual information and easily contact an individual student or group with similar characteristics. Information must be useful for both instructors and students, e.g., for making decisions. As for instructors, information should allow them to look for students at risk, with low activity levels and underperformance results, and for groups with unbalanced distribution of activities and tasks, and provide them just-in-time and personalized guidance. A course analysis could provide a quick detection of possible problems. As for students, information should let them know their performance level as compared to the average class level and possibly to the other groups that participate in the same online course.

4 Monitoring CSCL An effective monitoring and evaluation approach of Computer-Supported Collaborative Learning (CSCL) should include both the collaborative learning process and its individual and collective outcomes. The first one is considered as the most laborious and demanding task, since participants (both the instructor and the students) should take several elements and factors into account. In our opinion, the monitoring and evaluation of the collaborative learning process should be done by structuring it through the use of well-defined collaboration strategies. These strategies can be proposed and described by either the instructor or the learning group itself and they aim at clearly specifying the tasks that the group has to carry out following specific steps and actions. The result of this approach is that participants know at any moment in which point of their process they are, what kind of actions they have taken, are taking and need to take further in order to accomplish their tasks, so it becomes easier for any participant to control and intervene accordingly when it is necessary.

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Collaboration strategies are used to improve students collaborative work, overcome their limitations and problems due to false perceptions and lack of experience in such settings, combat their fears and negative attitudes, help them acquire specific skills/ knowledge to collaborate effectively, guide them to best use and exploit the different online tools that support their work, and finally orientate them to adapt themselves to the reality and the true conditions of their situation in the best possible way. To this end, it is necessary to allow the instructor to provide the students a set of representative context-free collaboration strategies and ask them to make the best use of these so that they build a full, flexible and effective collaborative context within their group which will lead them to a successful realization of their tasks. A detailed description of such strategies has been described by [9]. For the sake of example, some of these strategies, and the learning objectives they achieve, are the following: • • •

• • • • •



Brainstorming. It focuses on the generation of a large number of ideas for the solution of a problem. Student Teams Achievement Divisions (STAD). It motivates students to encourage and help each other, while at the same time accelerates their achievements. Jigsaw. It emphasizes interpersonal inter-dependence while allows groups to get to know a topic in depth, by making individuals become experts on a subtopic and teach each other until the whole topic becomes familiar to any member of the group. Group Investigation Method. It promotes the use of learning activities that can be explored and approached through different ways by students. Co-op Co-op. It enhances collaboration by means of discussion, open-ended problems and activities, problem decomposition into suitable individual tasks, and composition of the group solution through discussion. Guided Reciprocal Peer Questioning. It encourages discussion and critical thinking through open-ended questions. Three Steps Interview. It enhances team building and in-depth understanding of the topic that students deal with through their engagement into an interview and role-playing. Paired Annotations. It promotes cooperative learning through accountability and positive interdependence (students discuss key issues, exchange ideas and questions, look for differences, comment and prepare a common attitude and treatment of the subject matter. Double entry journal. It gives students the ability to unfold their thoughts regarding a topic which help them concentrate on important terms and develop critical thinking and knowledge.

Each group of students studies and analyzes the given collaborative strategies so that to understand their goals, functioning and use as clearly as possible. Students may also search for more information in literature, if necessary. The analysis of each collaborative strategy takes into account the students' ideas, preferences, goals, attitudes and perceptions, as well as their particular styles, skills and knowledge. Students should be fully aware of the benefits and limitations of applying a strategy in

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real collaborative settings. At the end of this process, students are able to choose a collaboration strategy that best fits the dynamics and idiosyncrasy of their group. Each group should then use the selected strategy to structure its interaction by specifying in detail the steps and actions which the group will follow during the whole process of collaborative work. More specifically, each step of the strategy will have to specify explicitly the goals it sets: which is each member’s role; what each group member will do, that is, the tasks that a member will undertake to fulfill; how he/she will carry them out (e.g., through which tools, methods, etc); how he/she will collaborate with the rest of group members; and, which is the role that the various discussions (in forums and chats) play when they are performed within the group. All this information can be captured and represented in the form of a script. In the field of computer-supported collaborative learning (CSCL), scripts are designed to support collaboration among distant learners or co-present learners whose interactions are (at least partially) mediated by a computer. The rationale of scripts is to structure collaborative learning processes in order to trigger group interactions that may not occur in free collaboration [3]. Scripting the details of a collaboration strategy, as described above, offers an effective way to structure group interaction, while allowing flexibility since it lets students make choices among the various options they have in each strategy step in order to accomplish a task/goal in the best possible way.

5 Conclusions and Future Work This paper addresses an important issue: the importance of on-line education and the adoption of a student-centered approach pointing to the significance of monitoring online students' and groups' activities, and proposing the use of collaborative strategies as a framework for improving computer-supported collaborative learning. This approach has been applied to a real online classroom using a distance learning platform and other auxiliary tools (such as the Cmaptool, a Wiki tool) to achieve these goals. Though the initial experience showed promising results (the students' satisfaction and performance were clearly higher than before), several questions need to be still addressed in the near future: application of the approach to relatively large numbers of students, with varying knowledge and motivations, and pressures on teachers' time; adequate preparation of students, a more complete integration of software supports and activities into the curriculum; and a participative follow-up of the outcomes of the activities. Further work is in progress which is expected to provide a more complete solution to this issue and the afore-mentioned questions.

Acknowledgments This work has been partially supported by HAROSA Knowledge Community (http://dpcs.uoc.edu) of the Internet Interdisciplinary Institute (IN3 - UOC).

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