Recommender Systems for Learning

Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Duval, Erik

ISBN 10: 1461443601 / ISBN 13: 9781461443605

Editore: Springer-Verlag New York Inc., 2012

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that support and enhance learning practices of individuals and organisations. This brief offers an introduction to recommender systems for TEL settings. It highlights their particularities compared to recommender systems for other application domains. Series: SpringerBriefs in Electrical and Computer Engineering. Num Pages: 87 pages, 4 black & white illustrations, 10 black & white tables, biography. BIC Classification: JNV. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 4. Weight in Grams: 148. . 2012. Paperback. . . . . Codice articolo V9781461443605

Riassunto:

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. 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 brief 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.

Dalla quarta di copertina:

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. 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 brief 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.

Dati bibliografici

Titolo: Recommender Systems for Learning
Casa editrice: Springer-Verlag New York Inc.
Data di pubblicazione: 2012
Legatura: Brossura
Condizione: New