* Price may vary from time to time.
* GO = We're not able to fetch the price (please check manually visiting the website).
Recommender Systems for Learning is written by Nikos Manouselis and published by Springer Science & Business Media. It's available with International Standard Book Number or ISBN identification 146144361X (ISBN 10) and 9781461443612 (ISBN 13).
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.