Recommender systems for learning /

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 learn...

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Bibliographic Details
Corporate Authors: SpringerLink (Online service)
Group Author: Manouselis, Nikos
Published: Springer,
Publisher Address: New York :
Publication Dates: 2013.
Literature type: eBook
Language: English
Series: SpringerBriefs in electrical and computer engineering,
Subjects:
Online Access: http://dx.doi.org/10.1007/978-1-4614-4361-2
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.
Carrier Form: 1 online resource (76 pages).
Bibliography: Includes bibliographical references.
ISBN: 9781461443612 (electronic bk.)
146144361X (electronic bk.)
Index Number: QA76
CLC: G40-057
Contents: Introduction and Background --
TEL as a Recommendation Context --
Survey and Analysis of TEL Recommender Systems --
Challenges and Outlook.