Recommender Systems for Learning

✍ Scribed by Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Erik Duval (auth.)

Publisher: Springer-Verlag New York
Year: 2013
Tongue: English
Leaves: 84
Series: SpringerBriefs in Electrical and Computer Engineering
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ 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.

✦ Table of Contents

Front Matter....Pages i-xi
Introduction and Background....Pages 1-20
TEL as a Recommendation Context....Pages 21-36
Survey and Analysis of TEL Recommender Systems....Pages 37-61
Challenges and Outlook....Pages 63-76

✦ Subjects

Information Systems and Communication Service; Education (general)

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