Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem

A Technology Enhanced Learning (TEL) ecosystem is a kind of Digital Ecosystem formed by independent platforms combined and used by learners to support their learning. Related work shows that recommendations in TEL can support learners and that in TEL ecosystems, learners do use different platforms. We therefore pursue the goal to enable recommendations across different platforms by exploiting the synergies between them to benefit learners. However, building such cross-platform recommender systems poses new and unique technological challenges for developers. In this paper, we discuss the challenges faced and present a framework, with a running example, for the development of cross-platform recommender systems for TEL ecosystems. The framework decouples the development of the recommender system from the evolution of the specific platforms and allows the integration of different recommendation algorithms by combining graph-based algorithms. As proof of concept, the framework was effectively applied and evaluated to develop a cross-platform recommender system in a TEL ecosystem comprising Moodle as the Learning Management System, and MediaWiki customized as Learning Object Repository. For future work, the integration of different recommendation algorithms and a user study on the benefits of recommendations from different sources in a learning scenario is planned.

[1]  Cliff Lampe,et al.  The Benefits of Facebook "Friends: " Social Capital and College Students' Use of Online Social Network Sites , 2007, J. Comput. Mediat. Commun..

[2]  Khe Foon Hew,et al.  Students' and teachers' use of Facebook , 2011, Comput. Hum. Behav..

[3]  Jürgen Buder,et al.  Learning with personalized recommender systems: A psychological view , 2012, Comput. Hum. Behav..

[4]  H. Boley,et al.  Digital Ecosystems: Principles and Semantics , 2007, 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference.

[5]  Hans Hummel,et al.  Recommendations for learners are different: Applying memory-based recommender system techniques to lifelong learning , 2007 .

[6]  D. Perkins,et al.  Chapter 1: Individual and Social Aspects of Learning , 1998 .

[7]  Padhraic Smyth,et al.  Analysis and Visualization of Network Data using JUNG , 2005 .

[8]  Renato Domínguez García,et al.  Exploiting Semantic Information for Graph-Based Recommendations of Learning Resources , 2012, EC-TEL.

[9]  Renato Domínguez García,et al.  CROKODIL - A Platform for Collaborative Resource-Based Learning , 2011, EC-TEL.

[10]  Erik Duval,et al.  The Ariadne Infrastructure for Managing and Storing Metadata , 2009, IEEE Internet Computing.

[11]  Carlos Delgado Kloos,et al.  Automatic Discovery of Complementary Learning Resources , 2011, EC-TEL.

[12]  George Karypis,et al.  A Comprehensive Survey of Neighborhood-based Recommendation Methods , 2011, Recommender Systems Handbook.

[13]  Olga C. Santos,et al.  Requirements for Semantic Educational Recommender Systems in Formal E-Learning Scenarios , 2011, Algorithms.

[14]  D. Perkins,et al.  Individual and Social Aspects of Learning , 1998 .

[15]  Peter Brusilovsky,et al.  Adaptation "in the Wild": Ontology-Based Personalization of Open-Corpus Learning Material , 2012, EC-TEL.

[16]  Stefanie N. Lindstaedt,et al.  Recommending knowledgeable people in a work-integrated learning system , 2010, RecSysTEL@RecSys.

[17]  Etienne Wenger,et al.  Communities of Practice: Learning, Meaning, and Identity , 1998 .

[18]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[19]  Rosa Alarcón,et al.  Recommending Learning Objects According to a Teachers' Contex Model , 2010, EC-TEL.

[20]  Christoph Rensing,et al.  A Framework for Cross-Platform Graph-based Recommendations for TEL , 2012, RecSysTEL@EC-TEL.

[21]  Bracha Shapira,et al.  Recommender Systems Handbook , 2015, Springer US.

[22]  Pithamber R. Polsani,et al.  Use and Abuse of Reusable Learning Objects , 2006, J. Digit. Inf..

[23]  Lloyd Rutledge,et al.  ReMashed - Recommendations for Mash-Up Personal Learning Environments , 2009, EC-TEL.

[24]  Hendrik Drachsler,et al.  Recommender Systems in Technology Enhanced Learning , 2011, Recommender Systems Handbook.

[25]  Umberto Straccia,et al.  User recommendation for collaborative and personalised digital archives , 2005, Int. J. Web Based Communities.

[26]  Ralf Steinmetz,et al.  Cross-Lingual Recommendations in a Resource-Based Learning Scenario , 2011, EC-TEL.

[27]  David Elliott,et al.  In the Wild , 2010 .

[28]  Alicia Díaz,et al.  Thinking Semantic Wikis as Learning Object Repositories , 2012, LiLe@WWW.