Recommender Systems for Learning: 0 (SpringerBriefs in Electrical and Computer Engineering) - Softcover

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

Softcover

ISBN 10: 1461443601 ISBN 13: 9781461443605

Publisher: Springer, 2012

Synopsis

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.

About this title

From the Back Cover

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.

Edition details

• Publisher: Springer
• Publication date: 2012
• ISBN 10: 1461443601
• ISBN 13: 9781461443605
• Binding: Paperback
• Language: English
• Number of pages: 87