Recommender Systems for Technology Enhanced Learning

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106,99 

Research Trends and Applications

ISBN: 1493946560
ISBN 13: 9781493946563
Herausgeber: Nikos Manouselis/Hendrik Drachsler/Katrien Verbert et al
Verlag: Springer Verlag GmbH
Umfang: xiv, 306 S., 67 s/w Illustr., 306 p. 67 illus.
Erscheinungsdatum: 03.09.2016
Auflage: 1/2014
Produktform: Kartoniert
Einband: Kartoniert

Presents cutting edge research from leading experts in the growing field of Recommender Systems for Technology Enhanced Learning (RecSys TEL)International contributions are included to demonstrate the merging of various efforts and communitiesTopics include: Linked Data and the Social Web as Facilitators for TEL Recommender Systems in Research and Practice, Personalised Learning-Plan Recommendations in Game-Based Learning and Recommendations from Heterogeneous Sources in a Technology Enhanced Learning EcosystemIncludes supplementary material: sn.pub/extras

Artikelnummer: 9808428 Kategorie:

Beschreibung

As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted increased interest during the past years.Recommendation methods, techniques and systems open an interesting new approach to facilitate and support learning and teaching. The goal is to develop, deploy and evaluate systems that provide learners and teachers with meaningful guidance in order to help identify suitable learning resources from a potentially overwhelming variety of choices.Contributions address the following topics: i) user and item data that can be used to support learning recommendation systems and scenarios, ii) innovative methods and techniques for recommendation purposes in educational settings and iii) examples of educational platforms and tools where recommendations are incorporated.

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