Recommender systems for learning

著者

    • Manouselis, Nikos
    • Drachsler, Hendrik
    • Verbert, Katrien
    • Duval, Erik

書誌事項

Recommender systems for learning

Nikos Manouselis ... [et al.]

(Springerbriefs in electrical and computer engineering)

Springer, c2013

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注記

Includes bibliographical references

Other authors:Hendrik Drachsler, Katrien Verbert, Erik Duval

内容説明・目次

内容説明

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.

目次

Introduction and Background.- TEL as a recommendation context.- Survey and Analysis of TEL Recommender Systems.- Challenges and Outlook.

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