Recommender Systems for Learning (Paperback, 2013 ed.)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	SpringerBriefs in Electrical and Computer Engineering
Release date:	August 2012
First published:	2013
Authors:	Nikos Manouselis • Hendrik Drachsler • Katrien Verbert • Erik Duval
Dimensions:	235 x 155 x 4mm (L x W x T)
Format:	Paperback
Pages:	76
Edition:	2013 ed.
ISBN-13:	978-1-4614-4360-5
Categories:	Books > Social sciences > Education > Educational resources & technology > General
LSN:	1-4614-4360-1
Barcode:	9781461443605

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