USING HYBRID SEMANTIC INFORMATION FILTERING APPROACH IN COMMUNITIES OF PRACTICE OF E-LEARNING
Keywords:
Communities of Practice of e-learning, recommendation system, information filtering, ontologies, , semantic filtering, learning resource, profileAbstract
The paper discusses the application of the Information Filtering (IF) approach in Communities of Practice of E-learning (CoPEs). We identify the main characteristics of CoPEs and show how the integration of the IF techniques can be useful in this context as a technology support for members of CoPEs. A personalized recommendation approach is proposed for CoPEs based on the hybrid semantic IF, integrating the contentbased filtering, the collaborative filtering and the ontology-based filtering approaches. Three strategies of recommendation have been proposed: (1) a semantic recommendation by specialty; (2) a semantic contentbased recommendation by domains of interests; and (3) a semantic collaborative recommendation by domains of interests. We have developed a prototype of a recommendation system called ReCoPESyst, based on the recommendation approach. In order to evaluate our system, we considered a community of teachers from a higher education context. A preliminary tests and experimentation of ReCoPESyst conducted within this community show its advantage and benefit for members.
Downloads
References
Wenger, E., McDermott, R., Snyder, W.M., Cultivating Communities of Practice: A guide in
Managing Knowledge. Harvard Business School Press, 2002.
Berkani, L., Communities of Practice of E-learning – « CoPE »: Definition of Concepts and
Proposition of a Learning Scenario Specification Language. Master Thesis, Higher National
School of Computer Science (ESI), Algiers, Algeria, 2007.
Chikh, A., Berkani, L., Sarirete, A., Modeling the communities of practice of e learning (CoPEs).
In 4th Annual Conference proceedings of Learning International Networks Consortium, Jordan
, 428-441
Lave, J., Wenger, E., Situated learning: legitimate peripheral participation, Cambridge: Cambridge
University Press, 1991
Daele, A. & al., Managing Knowledge within Communities of Practice: Analysing Needs and
Developing Services. eLearning Papers, No. 5, 2007
Preece, J., Online communities: Designing usability, supporting sociability, New York: John
Wiley & Sons, 2000.
PALETTE IST project, Pedagogically sustained Adaptive Learning through the Exploitation of
Tacit and Explicit Knowledge, http://www.ecrim.palette.org
Hoadley, C., Kilner, P.G., Using technology to transform communities of practice into knowledgebuilding communities, SIGGROUP Bulletin, 25(1), 31-40, 2005.
Hoadley, C.,What is a Community of Practice and How Can We Support it?, in D. H. Jonassen &
S. M. Land (Eds.), Theoretical foundations of learning environments, 287-300. New York:
Routledge, 2010.
Lopez M.: Information Access through a controlled collaborative filtering system, PhD Thesis,
Joseph Fourier University, 2005.
Peis E., Morales-del-Castillo J. M., Delgado-López J. A., Semantic Recommender Systems, in
Analysis of the state of the topic, Hipertext.net, N 6, 2008.
Terveen, L., and Hill, W., Beyond Recommender Systems: Helping People Help Each Other, in J.
M. Carroll, Human-Computer Interaction in the New Millennium, 487-509, New York: AddisonWesley, 2001.
Shafer, J.B., Frankowski, D., Herlocker, J., Sen, S., Collaborative filtering recommender systems,
in Brusilovsky, P., Kobsa, A., Neidl, W. (eds.) The Adaptive Web: Methods and strategies of Web
Personalization. LNCS, Vol. 4321, 291-324, 2007.
Adomavicius, G., & Tuzhilin, A., Toward the Next Generation of Recommender Systems: A
Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and
Data Engineering, 17 (6), 734-749, 2005.
Balabanovic, M., & Shoham, Y., Fab: Content-Based Collaborative Recommendation.
Communications of the ACM archive, 40 (3), 66-72, 1997.
Burke, R., Hybrid Recommender Systems: Survey and Experiments. User Modeling and UserAdapted Interaction, 12 (4), 331-370, 2002.
Oufaida H., Nouali O., The Collaborative Filtering and the web 2.0. Literature Review, Document
numérique, Vol. 11, 13-35, 2008.
Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H., and Koper, R., Recommender Systems
in Technology Enhanced Learning, in RecSysBook_TEL, 2009.
Verbert, K., Manouselis, N., Ochoa, X., Wolpers, M., Drachsler, H. Bosnic, I., Duval, E.,
“Context-Aware Recommender Systems for Learning: A Survey and Future Challenges”. IEEE
Transactions on Learning Technologies, 5(4), 318–335, 2012.
Ziovas, S., Grigoriadou, M., Samarakou, M., Supporting learning in online communities with
social software: An overview of community driven technologies. Advanced Technologies, in
InTech, 245-258, 2010.
Rafaeli, S., Barak, M., Dan-Gur, Y., and Toch, E., QSIA: a web-based environment for learning,
assessing and knowledge sharing in communities. Computers & Education, 43(3), 273-289, 2004.
Drachsler, H., Pecceu, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H.G.K.,
Koper, R., ReMashed - Recommendations for Mash-Up Personal Learning Environments, in
Cress, U., Dimitrova, V., Specht, M. (eds.): Learning in the Synergy of Multiple Disciplines, ECTEL 2009, LNCS 5794, Berlin; Heidelberg; New York: Springer, 788-793, 2009
Drachsler, H., Pecceu, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H.G.K.,
Koper, R.: ReMashed - An Usability Study of a Recommender System for Mash-Ups for
Learning. 1st Workshop on Mashups for Learning at the International Conference on Interactive
Computer Aided Learning, Villach, Austria, 2009
Brut, M., Sèdes, F., Modélisation basée sur des ontologies pour développer des recommandations
personnalisées dans les systèmes hypermédia adaptatifs, in Actes du XXVIII° congrès INFORSID,
Marseille, 2010.
Cantador, I., Bellogín, A., Castells, P., A Multilayer Ontology-based Hybrid Recommendation
Model, in AIC’08, 2008.
Berkani, L., Nouali, O., Chikh, A, A Recommendation-based Approach for Communities of
Practice of E-learning. Malki, M, Benbernou, S., Benslimane, S.M., Lehireche A., (Eds.): ICWIT
, Sidi Bel Abbes, Algeria, 2012.
Berkani, L., Nouali, O., Chikh, A, Recommandation personnalisée des ressources dans une
communauté de pratique de e-learning - Une approche à base de filtrage hybride. To appear in the
th proceedings of INFORSID, Paris, 2013.
Berkani, L., Chikh, A., Towards an Ontology for Supporting Communities of Practice of Elearning "CoPEs": A Conceptual Model. In: Cress, U., Dimitrova, V., and Specht, M. (eds.) ECTEL 2009. LNCS 5794, p664-669. Springer, Heidelberg, 2009.
Berkani, L. and Chikh, A., A Process for Knowledge Reuse in Communities of Practice of Elearning. In Social & Behavioural Sciences Journal (Elsevier) – WCES2010, 4-8 February,
Istanbul, Turkey, 2010
PAPI (2000). Draft Standard for Learning Technology —Public and Private Information (PAPI)
for Learners (PAPI Learner). IEEE P1484.2/D7, 2000-11-28. Available on-line:
IMS LIP (2001). IMS Learner Information Package Specification. The Global Learning
Consortium. Available on line at: http://www.imsglobal.org/profiles/index.html
Evangelou, C-E., Karousos, N., Tzagarakis, M., Gkotsis, G., Nousia, D., Personalization Services
in Argumentation Tools: a Catalyst for Learning. In TEL-CoPs’06, 1st International Workshop on
Building Technology Enhanced Learning solutions for CoPs, 89-99, Greece, 2006.
Drachsler, H., Bogers, T., Vuorikari, R., Verbert, K., Duval, E., Manouselis, N., Beham, G.,
Lindstaedt, S., Stern, H., Friedrich, M., Wolpers, M. Issues and Considerations regarding Sharable
Data Sets for Recommender Systems in Technology Enhanced Learning. In Procedia Computer
Science, Vol.1, 2010, 2849–2858.
Verbert, K., Manouselis, N., Drachsler, H., & Duval, E., Dataset-Driven Research to Support
Learning and Knowledge Analytics. Educational Technology & Society, 15 (3), 133–148, 2012.
Cechinel, C., Sicilia, M.A., Sánchez-Alonso, S., García-Barriocanal, E. Evaluating collaborative
filtering recommendations inside large learning object repositories. In Information Processing &
Management, Elsevier, 49(1), 2013, 34–50.
