Recommender Systems for Technology Enhanced Learning | Research Trends and Applications
Nikos Manouselis (u. a.)
ISBN 10: 1493946560 ISBN 13: 9781493946563
Editore: Springer, 2016
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Recommender Systems for Technology Enhanced Learning | Research Trends and Applications | Nikos Manouselis (u. a.) | Taschenbuch | xiv | Englisch | 2016 | Springer | EAN 9781493946563 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Codice articolo 103425555
Riassunto:
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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Titolo: Recommender Systems for Technology Enhanced ...
Casa editrice: Springer
Data di pubblicazione: 2016
Legatura: Taschenbuch
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Recommender Systems for Technology Enhanced Learning. Research Trends and Applications.
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New York, NY ; s.l., Springer New York/Imprint: Springer., 2014
ISBN 10: 1493946560
ISBN 13: 9781493946563
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ed. 2014. XIV, 306 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stemped. Sprache: Englisch. Codice articolo 8222JB
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Recommender Systems for Technology Enhanced Learning: Research Trends and Applications [Paperback] Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien and Santos, Olga C. (eng)
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Recommender Systems for Technology Enhanced Learning
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 communities. Codice articolo 203124842
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Recommender Systems for Technology Enhanced Learning
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Springer, Springer Sep 2016, 2016
ISBN 10: 1493946560
ISBN 13: 9781493946563
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch. Codice articolo 9781493946563
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Recommender Systems for Technology Enhanced Learning
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Springer New York Sep 2016, 2016
ISBN 10: 1493946560
ISBN 13: 9781493946563
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 320 pp. Englisch. Codice articolo 9781493946563
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Recommender Systems for Technology Enhanced Learning : Research Trends and Applications
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9781493946563
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Recommender Systems for Technology Enhanced Learning: Research Trends and Applications
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Recommender Systems for Technology Enhanced Learning : Research Trends and Applications
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