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 in...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY ; s.l.
Springer New York
2014
Imprint: Springer |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (XIV, 306 p.) Ill. |
| ISBN: | 9781493905300 9781493905294 |
| DOI: | 10.1007/978-1-4939-0530-0 |
Internformat
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Datensatz im Suchindex
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| author | Manouselis, Nikos |
| author_GND | (DE-588)134084659 (DE-588)1122669089 |
| author_facet | Manouselis, Nikos |
| author_role | aut |
| author_sort | Manouselis, Nikos |
| author_variant | n m nm |
| building | Verbundindex |
| bvnumber | BV041882028 |
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| ctrlnum | (OCoLC)879508600 (DE-599)BVBBV041882028 |
| dewey-full | 370 |
| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 370 - Education |
| dewey-raw | 370 |
| dewey-search | 370 |
| dewey-sort | 3370 |
| dewey-tens | 370 - Education |
| discipline | Pädagogik Informatik |
| doi_str_mv | 10.1007/978-1-4939-0530-0 |
| format | Electronic eBook |
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| id | DE-604.BV041882028 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T01:07:21Z |
| institution | BVB |
| isbn | 9781493905300 9781493905294 |
| language | English |
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| spelling | Manouselis, Nikos Verfasser (DE-588)134084659 aut Recommender Systems for Technology Enhanced Learning Research Trends and Applications edited by Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos New York, NY ; s.l. Springer New York 2014 Imprint: Springer 1 Online-Ressource (XIV, 306 p.) Ill. txt rdacontent c rdamedia cr rdacarrier 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 Online-Ausgabe Springer eBook Collection / Computer Science Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Informationssystem (DE-588)4072806-7 gnd rswk-swf Informatik (DE-588)4026894-9 gnd rswk-swf Informatik (DE-588)4026894-9 s Informationssystem (DE-588)4072806-7 s Künstliche Intelligenz (DE-588)4033447-8 s DE-604 Drachsler, Hendrik Sonstige oth Verbert, Katrien 1981- Sonstige (DE-588)1122669089 oth Santos, Olga C. Sonstige oth Reproduktion von Manouselis, Nikos Recommender Systems for Technology Enhanced Learning 2014 https://doi.org/10.1007/978-1-4939-0530-0 Verlag Volltext |
| spellingShingle | Manouselis, Nikos Recommender Systems for Technology Enhanced Learning Research Trends and Applications Künstliche Intelligenz (DE-588)4033447-8 gnd Informationssystem (DE-588)4072806-7 gnd Informatik (DE-588)4026894-9 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4072806-7 (DE-588)4026894-9 |
| title | Recommender Systems for Technology Enhanced Learning Research Trends and Applications |
| title_auth | Recommender Systems for Technology Enhanced Learning Research Trends and Applications |
| title_exact_search | Recommender Systems for Technology Enhanced Learning Research Trends and Applications |
| title_full | Recommender Systems for Technology Enhanced Learning Research Trends and Applications edited by Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos |
| title_fullStr | Recommender Systems for Technology Enhanced Learning Research Trends and Applications edited by Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos |
| title_full_unstemmed | Recommender Systems for Technology Enhanced Learning Research Trends and Applications edited by Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos |
| title_short | Recommender Systems for Technology Enhanced Learning |
| title_sort | recommender systems for technology enhanced learning research trends and applications |
| title_sub | Research Trends and Applications |
| topic | Künstliche Intelligenz (DE-588)4033447-8 gnd Informationssystem (DE-588)4072806-7 gnd Informatik (DE-588)4026894-9 gnd |
| topic_facet | Künstliche Intelligenz Informationssystem Informatik |
| url | https://doi.org/10.1007/978-1-4939-0530-0 |
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