Recommender Systems for Learning (SpringerBriefs in Electrical and Computer Engineering)

Manouselis, Nikos

ISBN 10: 1461443601 / ISBN 13: 9781461443605

Edité par Springer, 2012

In. N° de réf. du vendeur ria9781461443605_new

Synopsis :

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.

Présentation de l'éditeur: 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.

Détails bibliographiques

Titre : Recommender Systems for Learning (...
Éditeur : Springer
Date d'édition : 2012
Reliure : Couverture souple
Etat : New