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...
| Main Authors: | , , , |
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| Corporate Author: | |
| Format: | Electronic |
| Language: | English |
| Published: |
New York, NY :
Springer New York : Imprint: Springer,
2013.
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| Series: | SpringerBriefs in Electrical and Computer Engineering,
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| Subjects: | |
| Online Access: | https://ezaccess.library.uitm.edu.my/login?url=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. |
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| Physical Description: | XI, 76 p. 4 illus. online resource. |
| ISBN: | 9781461443612 |
| ISSN: | 2191-8112 |