Multi-rep: An e-Learning Reputation System Aggregating Information from Heterogeneous Sources

Reputation systems are used both as a motivational and an assessment tool in cooperative and classic e-Learning. They can prove useful in accompanying learners along the paths of their didactic activities, by fostering their involvement in the socio-cooperative didactic game. A problem arises, though, when learners (and teachers) participate in different web systems and possibly in different reputation systems, as it is the case when the learners are in proper e-learning systems, such as Moodle, and/or blogs, forums, or wikis. Then, the difficulties in computing reputation, across heterogeneous platforms, may overcome the teacher, and eventually force her towards the use of a single system. We present the initial work done and the design of Multi-Rep, a reputation aggregator, able to collect data from heterogeneous sources, by tracking the participation actions of learners across diverse e-learning tools, and compute the related reputation. Being able to deal with different reputation algorithms and to merge the results of students’ interaction in several arenas, appears to be a key factor in allowing more freedom for teacher and students (who can use a wider array of socio-collaborative tools). Moreover, we want to easily define different roles for the students depending on their reputation, so that we can empower some of them (e.g. letting them be co-tutors or peer teachers), rewarding their involvement with higher capabilities/responsibilities, and thus recognizing their important role in the cooperative didactic game.

[1]  Karl Aberer,et al.  Synergies of Different Reputation Systems: Challenges and Opportunities , 2009, 2009 World Congress on Privacy, Security, Trust and the Management of e-Business.

[2]  Wei Wei,et al.  Measuring credibility of users in an e-learning environment , 2007, WWW '07.

[3]  George Buchanan,et al.  Digital Libraries: Universal and Ubiquitous Access to Information, 11th International Conference on Asian Digital Libraries, ICADL 2008, Bali, Indonesia, December 2-5, 2008. Proceedings , 2008, ICADL.

[4]  Jianmin Zhao,et al.  Advances in Blended Learning , 2008, Lecture Notes in Computer Science.

[5]  Marco Temperini,et al.  SocialX: Reputation Based Support to Social Collaborative Learning Through Exercise Sharing and Project Teamwork , 2011, Int. J. Inf. Syst. Soc. Chang..

[6]  Martin Halvey,et al.  WWW '07: Proceedings of the 16th international conference on World Wide Web , 2007, WWW 2007.

[7]  Martin Weller,et al.  The distance from isolation: Why communities are the logical conclusion in e-learning , 2007, Comput. Educ..

[8]  Maria De Marsico,et al.  The Definition of a Tunneling Strategy between Adaptive Learning and Reputation-based Group Activities , 2011, 2011 IEEE 11th International Conference on Advanced Learning Technologies.

[9]  Zhendong Niu,et al.  A User Reputation Model for DLDE Learning 2.0 Community , 2008, ICADL.

[10]  Luca de Alfaro,et al.  A content-driven reputation system for the wikipedia , 2007, WWW '07.

[11]  Jianmin Zhao,et al.  Application of PageRank Technique in Collaborative Learning , 2008, WBL.