AWERProcedia Information Technology & Computer Science

AWERProcedia Information Technology & Computer Science 2 (2012) 241-249

2nd World Conference on Innovation and Computer Sciences 2012

The use of deliberates practices on a mobile learning environment Ilker Yengina, I.Furkan Inceb, Adem Karahocac, Dilek Karahocac, Huseyin Uzunboylud a

A*STAR, Institute of High Performance Computing Singapore b School of Engineering, The University of Tokyo, Japan c Software Engineering Department, Bahcesehir University, Ciragan 34353 Besiktas, Istanbul, Turkey d Department of Computer Education and Instructional Technologies, Near East University, Lefkosa 98010, Northern Cyprus

Abstract Mobile learning brings the opportunity to do practices and activities anywhere in our daily life. However learning for expertise requires more than daily activities, it requires deliberate practices. Different than daily activities and practices, deliberate practices are specific and well designed activities for gradually gaining and improving expertise with the help of teacher led feed-backs. This paper introduces the use of deliberates practices on a mobile learning environment. This paper describes the system design and applications including both teacher and student side of the mobile learning environment. The teacher side consists of a management module for the learning objects pool creation and student monitoring. Student side consists of a content pulling module for deliberate practices and a self and personalized learning monitoring system. This paper would be helpful for teachers and instructional designers and mobile learning platform designers to understand the mechanisms behind the design practices for the notion of deliberate practices. Keywords:Mobile Learning,Deliberate Practices,Expertise; Selection and/or peer review under responsibility of Prof. Dr. Dogan Ibrahim. ©2012 Academic World Education & Research Center. All rights reserved.

1. Introduction Latest trends indicate that people are willing to work and learn mobile anytime [25]. Mobile applications and mobile availability for internet access may create an enriched learning experience [12]. Use of mobile applications for education may give freedom to students to study anytime and give them different capabilities to improve their learning and productivity. Mobile phones are bringing a wide range of possibilities for learning because of easy mobile access to networked information and applications that students carry whenever they go. Anytime access to internet brings the opportunity to access the learning content and to do practices and activities anywhere and anytime in our daily

ADDRESS FOR CORRESPONDENCE: Ilker Yengin, A*STAR, Institute of High Performance Computing Singapore

E-mail address: [email protected] / Tel.: +65-6419-1538

242 Ilker Yengin. / AWERProcedia Information Technology & Computer Science (2012) 241-249

life. However learning for expertise requires more than daily activities and practices, it requires deliberate practices. Different than daily activities and practices, deliberate practices are specific and well designed activities for gradually gaining and improving expertise with the help of teacher led feed-backs. The first part of the paper describes the notion of deliberate practices and discusses how they are beneficial to improve expertise. Second part of the paper describes the design and implementation of the deliberate practices in mobile learning environment. 2. Deliberate Practices vs. Other Activities Ericsson et al. make a clear segmentation between deliberative practices, practices (on repetitive training), play and actual work[28]. This segmentation is needed to differentiate learning from purposefulness and inefficient training [21]. Unlike the practices that need an application of already gained skills set, deliberate practices are based on repeated efforts to attain further levels of performance of individuals [27]. These properties of deliberate practices make them somewhat different than regular practices which are based on repetition of task based on skills that students already have. Deliberate practices should be designed to improve the existing level of performance; also they are designed for repetition of tasks based on skills that students don't have or need a correction or need an improvement for further range of skills [28, 21]. It is a general conception that practice helps students to learn from their experiences aiming to improve their skills; however others suggest that using practices are not sufficient enough to improve skills [30]. The use of deliberate practices rather than mere practices is much more beneficial to create such an improvement. [18]. Also in some practices there is no immediate feedback. However deliberate practices are based on highly structured activities to improve students’ predominance with immediate feedbacks. Feedback in deliberate practices will allow to overcome problems in the predominance and monitor students and to provide cues and guidelines to students to create further improvement [28, 55]. In most cases, deliberate practices are challenging and sequenced which requires a mentor to work with for the improvement of individual performances [30, 39, 48]. Ericsson also differentiates work competition - play from deliberate practices[28]. According to Hysterics, in these situations learners have to execute the task for the efficiency of task/time performances rates rather than put effort for learning and improving a skill set or refining them. Additionally learners are under time, peer or social pressures in these kind of environments. This kind of pressure does occur because in these environments mistakes and failure is costly. In work and playcompetition areas individuals have to show their best effort. Hysterics underlines that the work activities could create learning opportunities but they are not structured and optimal as deliberate practices. Different than practices or the play, deliberate practices will not provide immediately achieved rewards, prizes or social applause. Work, play – competition activities are motivated by social monetary external rewards [19, 28]. Play – competition activities include motivation because of the activities structure itself or the social recognition and work activities are motivated because of payment [15, 44]. Similar to other activities, deliberate practices also require a concentration but unlike to other activities this concentration can be kept for a limited time. Experts such as athletes, musicians can only practice few hours [20, 28] and they set special times for practices [22-23]. Additionally without improvement of skills and without ability, hours of practice have no great affect on performance [27].


As similar to doing other activities, individuals who have more commitment to their expertise will be more motivated to execute deliberate practices [16]. 3. Mobile Learning System Design This part explains the user groups, their roles and the system modules and learning objects pool. The complete overview of system design is visualized in Figure 1.

Fig 1.Overview of System Design

3.1. User Groups and Roles The mobile learning environment has two user groups such as the teachers and the students. The teacher side consists of a management module for the learning objects pool creation and student monitoring. Student side consists of a content pulling module for deliberate practices and a self and personalized learning monitoring system. Teachers’ roles are basically creating the deliberate practices in learning objects pool and monitoring students’ performance. Students’ roles are to do the deliberate practices and self-personalized monitoring of their learning. 3.2. Learning Objects Pool The learning objects pool consists of entities which can be used and referenced during mobile technology learning according to IEEE Learning Technology Standards Committee’s definition [24, 52]. This pool helps to combine chuck of closely related entities (which are also basis of deliberate practices) into single learning objectives. Blooms’ Taxonomy provides an initial basis for constructing learning objects which are helpful for gaining gradual deeper learning and expertise on any knowledge or skill [3, 53+. Using Blooms’ Taxonomy in e-learning applications has been advocated as a necessary implementation for successful pedagogy in the design [4–6]. Therefore it may be pedagogically beneficial to implement it in mobile learning applications, too. The learning objects in the system are assumed to be designed to support gradual knowledge building with an alignment to Bloom’s Taxonomy. Thus, each learning object should have one or multiple references to one or many cognitive domain level at Bloom’s taxonomy [32, 54+. Figure 2 presents the different levels of Bloom’s taxonomy.


Fig.2. Bloom's Taxonomy

In addition to taxonomy levels, each learning object meta-data should also have a definition for the difficulty level. This difficulty level shows the cognitive resources that the students may need to use for completing the objective. The difficulty levels also give clue about how much germane cognitive load may occur during the processing, construction and automation of schemas for the related learning object [7]. Item difficulties in the systems are classified as easy, medium and hard. More over the deliberate practice item also should have a description, an ID, a feedback item and attached multimedia entities. Thus, a learning object should convey the following information in metadata as in Table 1. Table 1.An Example of Learning Object A Sample Learning Object’ Attributes Cognitive domain level at Bloom’s taxonomy Item Difficulty Description ID Feedback Attached multimedia

Data Comprehension , Synthesis Medium Please watch the video attached to this activity first. Then explain what the main idea in the video was. 00001 To figure out the main idea, ask yourself this question: What is being said about the person, thing, or idea (the topic)? NTV-News-21.mov

4. How does the System Support Deliberate Practices: System Scenario The deliberate practices should be specific and well designed activities that should allow the learner to gain gradual improvement with repeated practices. When students are expert in a certain learning object there will be no new improvements in their skills and knowledge so their current performance will keep becoming strengthened rather than improving. Thus deliberate practices are designed to improve or refine the knowledge that is already well known by the learner. In order to keep gradual improvement the system should keep giving activities where students can practice the skills and knowledge that they still have room for improvement, or the system can increase the level of difficulty of the activities. In order to implement that scenario, the system may check the students profile and associate it with available learning objects. As long as the associated learning objects will have different levels in Bloom’s taxonomy and different difficulty, the system may keep giving deliberate practices by pushing new activities where there is a gap or refinement is present. Also by increasing the object type; such as a new level from the taxonomy, or the difficulty of


activities system may keep going to provide deliberate practices. This type of an implementation in system scenario will help students to be able to extend the boundaries of their skills and knowledge. In addition there should be a mechanism for getting feedback and for repeating and correcting the mistakes before going forward in any activity. These feedbacks will be useful for providing cues and guidelines to students to create further improvement. As long as the deliberate practices ideas are different than play, the system does not keep scores for any kind of immediately achieved rewards, prizes or social applause. The only indications of the performance are given in a feedback format. Thus the system scenario requires a design where the system continuously delivers deliberate practices to students and profiles the students’ performances. The students in the system should check their profiles and monitor their actions with the help of feed-backs. Deliberate practices pulling module is designed to provide the content and self – monitoring module are designed to give the related feedback. The modules that allow monitoring students’ performance are designed to monitor students’ progress and give immediate feedback where teachers need to. All the content creation will be done by the teachers. Thus they will be the users that are creating the deliberate practices in learning objects pool. Also feedbacks are given by the teachers as predetermined feedbacks and/or immediate on demand feedbacks. Predetermined feedbacks are previously embedded into learning objects at the moment when the deliberate practice is created. The immediate feedbacks are given to students as a text message format when necessary. Teachers will monitor students’ progress to find out the need for feedback. 4.1. Example Scenario: Regarding to the example item in Table 1, an example step by step scenario introduced as in the Table 2. According to scenario, a teacher adds a deliberate practice into the pool. This practice will be the one that the students will see at his mobile device. This practice will be provided to student to refine his exiting skills where he has the skill automation and expertise. Thus, in our example, before providing this practice item to student, the system is assumed to profile the student and identified that he has an expertise in the related area that this learning object is covering and the student still needs to have refinement and improvement in this area as well. This profiling and monitoring act will be done by the monitoring module of the system.

246 Ilker Yengin. / AWERProcedia Information Technology & Computer Science (2012) 241-249 Table 2.An Example of step by step scenario for creating deliberate practices

Step 1: Teacher adds a description for the deliberate practice item.

Step 2: Teacher decides the type of cognitive domain level of this item by clicking relevant checkboxes in the Bloom’s Taxonomy pyramid.

Step 3: Teacher decides the item difficulty for the related item by sliding the bar.

Step 4: Teacher accordingly.

Step 5: Teacher adds an attachment to the item. Attachments can be an offline/online picture, video or document. Teacher may also skip this step if she doesn’t have anything to attach.

Step 6: Summary screen lets teacher to review the deliberate practice item. Teacher may edit the item if she needs to change it or continue. After this step a message windows ask teacher whether she decides to add or not to add this item to object pool.

adds

the

feedback

In table 3, an example scenario introduced where a student do the deliberate practice that is created in previous scenario. Here, profile matching and adaptation was done by system’s monitoring module.

247 Ilker Yengin. / AWERProcedia Information Technology & Computer Science (2012) 241-249 Table 3.An Example step by step scenario of receiving deliberate practices

Step 1: Student receives the deliberate practice item. This item asks student to review a video to be able to do the practice.

Step 2: In this step student review the video that is attached to deliberate practice. Video controllers allow student to navigate in the video.

Step 3: Student response to the item. When he is done writing the text this response will send to server.

5. Conclusion In this paper, authors introduced the use of deliberates practices on a mobile learning environment. First, reviewing the related literature, authors discussed the notion of deliberate practices and the differences of deliberate practices from other activities. Then, in order to show the use of deliberate practices notion for mobile learning environments, authors described the system design and possible scenario applications including both teacher and student side of the mobile learning environment. This system design can be implemented to a mobile learning platform. The literature review analysis, system design and example scenarios discussed in this paper would be helpful for teachers and instructional designers and mobile learning platform designers to understand the mechanisms behind the design practices for the notion of deliberate practices. References *1+ D. Laurillard, “Pedagogical forms of mobile learning: framing research questions,” 2007. *2+ C. H. Lai, J. C. Yang, F. C. Chen, C. W. Ho, and T. W. Chan, “Affordances of mobile technologies for experiential learning: the interplay of technology and pedagogical practices,” Journal of Computer Assisted Learning, vol. 23, no. 4, pp. 326-337, 2007. *3+ P. McGee, “Learning objects: Bloom’s taxonomy and deeper learning principles,” in 7th annual E-learn conference. Norfolk: Association for the Advancement of Computing in Education, 2003. *4+ T. Govindasamy, “Successful implementation of e-learning: Pedagogical considerations,” The Internet and Higher Education, vol. 4, no. 3, pp. 287-299, 2001. *5+ A. Zouaq, R. Nkambou, and C. Frasson, “An integrated approach for automatic aggregation of learning knowledge objects,” Interdisciplinary Journal of Knowledge and Learning Objects, vol. 3, pp. 135-162, 2007. *6+ S. Baldiris, O. C. Santos, C. Barrera, J. G. Boticario, J. Velez, and R. Fabregat, “Integration of educational specifications and standards to support adaptive learning scenarios in ADAPTAPlan,” International Journal of Computer Science and Applications (IJCSA). Special Issue on New Trends on AI techniques for Educational Technologies, vol. 5, no. 1, pp. 88-107, 2008. *7+ J. Sweller, J. van Merrienboer, and F. Paas, “Cognitive Architecture and Instructional Design,” Educational Psychology Review, vol. 10, no. 3, pp. 251-296, 1998. [8] Anderson, J. R. Acquisition of cognitive skill. Psychological Review, 89,369–406, 1982.


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