Abstract
Recommender systems support users in accessing information available on the Web. This process ensures personalization since recommendations are generated according to user’s characteristics. In the educational domain, in the most cases, recommendations refer to learning materials. Besides that, there is a potential for using recommendation techniques in order to personalize other aspects of e-learning context. This paper describes a recommendation model for providing personalization of a collaborative learning process. Well-known recommendation techniques are adapted for online learning environment that consists of an LMS and different Web 2.0 tools. The recommendations are used to support students before and during e-tivities and include four different types of items: optional e-tivities, collaborators, Web 2.0 tools and advice.
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Dlab, M.H., Hoic-Bozic, N., Mezak, J. (2014). Personalizing E-Learning 2.0 Using Recommendations. In: Mascio, T., Gennari, R., Vitorini, P., Vicari, R., de la Prieta, F. (eds) Methodologies and Intelligent Systems for Technology Enhanced Learning. Advances in Intelligent Systems and Computing, vol 292. Springer, Cham. https://doi.org/10.1007/978-3-319-07698-0_4
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DOI: https://doi.org/10.1007/978-3-319-07698-0_4
Publisher Name: Springer, Cham
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