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E-book

Title Recommender systems for learning / Nikos Manouselis [and others]
Published New York : Springer, [2013]
©2013
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Description 1 online resource (76 pages)
Series SpringerBriefs in electrical and computer engineering, 2191-8120
SpringerBriefs in electrical and computer engineering.
Contents Introduction and Background -- TEL as a Recommendation Context -- Survey and Analysis of TEL Recommender Systems -- Challenges and Outlook
Summary 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
Analysis Computer science
Information Systems and Communication Service
Education (general)
Bibliography Includes bibliographical references
Notes Print version record
Subject Recommender systems (Information filtering)
Educational technology.
Form Electronic book
Author Manouselis, Nikos.
LC no. 2012940235
ISBN 146144361X (electronic bk.)
9781461443612 (electronic bk.)
(paper)
(paper)