Recommender Systems for Technology Enhanced Learning: Research Trends and Applications
Manouselis Nikos
ISBN 10: 1493905295 ISBN 13: 9781493905294
Editore: Springer, 2014
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Recommender Systems for Technology Enhanced Learning Editor(s): Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Santos, Olga C. Num Pages: 320 pages, 67 black & white illustrations, 30 black & white tables, biography. BIC Classification: JNV; UYQ. Category: (P) Professional & Vocational. Dimension: 241 x 163 x 22. Weight in Grams: 620. . 2014. 2014th Edition. Hardcover. . . . . Codice articolo V9781493905294
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.
Recensione:
From the book reviews:
“Book represents a collection of state-of-the-art contributions devoted to RSs for TEL and explores contemporary research achievements in the area. ... This very interesting, well-timed volume will provide great opportunities for PhD students and newcomers to this field to continue with high-quality research efforts. The book is also interesting for master’s students who would like to acquire adequate knowledge and emergent research achievements in this field. Secondary school teachers and experienced researchers could also find this book useful and interesting.” (M. Ivanović, Computing Reviews, October, 2014)
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Titolo: Recommender Systems for Technology Enhanced ...
Casa editrice: Springer
Data di pubblicazione: 2014
Legatura: Rilegato
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Recommender Systems for Technology Enhanced Learning : Research Trends and Applications
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Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 320 | Sprache: Englisch | Produktart: Bücher | 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 24443017/12
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Recommender Systems for Technology Enhanced Learning: Research Trends and Applications (eng)
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Recommender Systems for Technology Enhanced Learning
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Gebunden. 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 4213825
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Recommender Systems for Technology Enhanced Learning | Research Trends and Applications
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Buch. Condizione: Neu. Recommender Systems for Technology Enhanced Learning | Research Trends and Applications | Nikos Manouselis (u. a.) | Buch | xiv | Englisch | 2014 | Springer US | EAN 9781493905294 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 105492827
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Recommender Systems for Technology Enhanced Learning: Research Trends and Applications : Research Trends and Applications
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Hardcover. Condizione: Neu. Neu Neuware, auf Lager - 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 INF1000763552
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Recommender Systems for Technology Enhanced Learning
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Buch. 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 9781493905294
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Recommender Systems for Technology Enhanced Learning
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Springer New York, Springer US Apr 2014, 2014
ISBN 10: 1493905295
ISBN 13: 9781493905294
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Buch. Condizione: Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch. Codice articolo 9781493905294
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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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Springer New York, Springer US, 2014
ISBN 10: 1493905295
ISBN 13: 9781493905294
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Buch. 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 9781493905294
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