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- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Electrical and Computer Engineering (BRIEFSELECTRIC)
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About this book
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.
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Table of contents (4 chapters)
Authors and Affiliations
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Bibliographic Information
Book Title: Recommender Systems for Learning
Authors: Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Erik Duval
Series Title: SpringerBriefs in Electrical and Computer Engineering
DOI: https://doi.org/10.1007/978-1-4614-4361-2
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2013
Softcover ISBN: 978-1-4614-4360-5Published: 28 August 2012
eBook ISBN: 978-1-4614-4361-2Published: 28 August 2012
Series ISSN: 2191-8112
Series E-ISSN: 2191-8120
Edition Number: 1
Number of Pages: XI, 76
Number of Illustrations: 4 b/w illustrations
Topics: Information Systems and Communication Service, Education, general