Recommender systems for technology enhanced learning

research trends and applications

Recommender systems for technology enhanced l ...
Nikos Manouselis, Hendrik Drac ...
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Last edited by MARC Bot
December 7, 2022 | History

Recommender systems for technology enhanced learning

research trends and applications

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.

Publish Date
Publisher
Springer
Language
English
Pages
306

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Book Details


Edition Notes

Includes bibliographical references.

Published in
New York

Classifications

Dewey Decimal Class
371.33
Library of Congress
LB1028.3 .R418 2014, Q334-342L1-991QA75.5, Q334-342, TJ210.2-211.495

The Physical Object

Pagination
xiv, 306 pages
Number of pages
306

Edition Identifiers

Open Library
OL30388595M
ISBN 10
1493905295
ISBN 13
9781493905294
LCCN
2014935878
OCLC/WorldCat
867615360

Work Identifiers

Work ID
OL21712835W

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December 7, 2022 Edited by MARC Bot import existing book
February 27, 2022 Edited by ImportBot import existing book
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