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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1820/3086
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| Title: | Recommender Systems in Technology Enhanced Learning |
| Authors: | Manouselis, Nikos Drachsler, Hendrik Vuorikari, Riina Hummel, Hans Koper, Rob |
| Keywords: | state-of-the-art recommender systems recommender systems adaptive hypermedia Learning Networks personalization |
| Issue Date: | 21-Dec-2010 |
| Abstract: | Technology enhanced learning (TEL) aims to design, develop and test sociotechnical
innovations that will support and enhance learning practices of both individuals
and organizations. It is therefore an application domain that generally
covers technologies that support all forms of teaching and learning activities.
Since information retrieval (in terms of searching for relevant learning resources
to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This chapter attempts to provide
an introduction to recommender systems for TEL settings, as well as to highlight
their particularities compared to recommender systems for other application
domains. |
| Description: | Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H. G. K., & Koper, R. (2011). Recommender Systems in Technology Enhanced Learning. In P. B. Kantor, F. Ricci, L. Rokach, & B. Shapira (Eds.), Recommender Systems Handbook (pp. 387-415). Berlin: Springer. |
| URI: | http://hdl.handle.net/1820/3086 |
| Appears in Collections: | 1. LN: Publications and Preprints
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