Description
Recommender Systems for Learning, 2013
SpringerBriefs in Electrical and Computer Engineering Series
Authors: Manouselis Nikos, Drachsler Hendrik, Verbert Katrien, Duval Erik
Language: English63.29 €
In Print (Delivery period: 15 days).
Add to cart the book of Manouselis Nikos, Drachsler Hendrik, Verbert Katrien, Duval Erik
Publication date: 08-2012
76 p. · 15.5x23.5 cm · Paperback
76 p. · 15.5x23.5 cm · Paperback
Description
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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.
Introduction and Background.- TEL as a recommendation context.- Survey and Analysis of TEL Recommender Systems.- Challenges and Outlook.
Includes supplementary material: sn.pub/extras
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