Recommender systems for learning:
<p>Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching...
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
New York, NY [u.a.]
Springer
2013
|
| Schriftenreihe: | SpringerBriefs in electrical and computer engineering
|
| Schlagworte: | |
| Online-Zugang: | BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FWS01 UBY01 Volltext |
| Zusammenfassung: | <p>Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.</p> |
| Beschreibung: | Introduction and Background -- TEL as a recommendation context -- Survey and Analysis of TEL Recommender Systems -- Challenges and Outlook |
| Beschreibung: | 1 Online-Ressource (XI, 76 p. 4 illus) |
| ISBN: | 9781461443612 |
| DOI: | 10.1007/978-1-4614-4361-2 |
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| id | DE-604.BV040704705 |
| illustrated | Not Illustrated |
| indexdate | 2024-08-01T16:14:51Z |
| institution | BVB |
| isbn | 9781461443612 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-025685167 |
| oclc_num | 819809717 |
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| physical | 1 Online-Ressource (XI, 76 p. 4 illus) |
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| publishDate | 2013 |
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| publisher | Springer |
| record_format | marc |
| series2 | SpringerBriefs in electrical and computer engineering |
| spellingShingle | Recommender systems for learning Informatik Computer science Information systems |
| title | Recommender systems for learning |
| title_auth | Recommender systems for learning |
| title_exact_search | Recommender systems for learning |
| title_full | Recommender systems for learning Nikos Manouselis ... |
| title_fullStr | Recommender systems for learning Nikos Manouselis ... |
| title_full_unstemmed | Recommender systems for learning Nikos Manouselis ... |
| title_short | Recommender systems for learning |
| title_sort | recommender systems for learning |
| topic | Informatik Computer science Information systems |
| topic_facet | Informatik Computer science Information systems |
| url | https://doi.org/10.1007/978-1-4614-4361-2 |
| work_keys_str_mv | AT manouselisnikos recommendersystemsforlearning |