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Recommender Systems for Learning
Details
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.
Includes supplementary material: sn.pub/extras
Inhalt
Introduction and Background.- TEL as a recommendation context.- Survey and Analysis of TEL Recommender Systems.- Challenges and Outlook.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09781461443605
- Anzahl Seiten 88
- Lesemotiv Verstehen
- Genre Allgemein & Lexika
- Auflage 2013
- Herausgeber Springer New York
- Gewicht 149g
- Untertitel SpringerBriefs in Electrical and Computer Engineering
- Größe H235mm x B155mm x T6mm
- Jahr 2012
- EAN 9781461443605
- Format Kartonierter Einband
- ISBN 1461443601
- Veröffentlichung 28.08.2012
- Titel Recommender Systems for Learning
- Autor Nikos Manouselis , Erik Duval , Katrien Verbert , Hendrik Drachsler
- Sprache Englisch