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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor Corporativo: | |
| Otros Autores: | , , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2014.
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| Edición: | 1st ed. 2014. |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-1-4939-0530-0 | ||
| 003 | DE-He213 | ||
| 005 | 20220116091418.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 140412s2014 xxu| s |||| 0|eng d | ||
| 020 | |a 9781493905300 |9 978-1-4939-0530-0 | ||
| 024 | 7 | |a 10.1007/978-1-4939-0530-0 |2 doi | |
| 050 | 4 | |a Q334-342 | |
| 050 | 4 | |a TA347.A78 | |
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| 245 | 1 | 0 | |a Recommender Systems for Technology Enhanced Learning |h [electronic resource] : |b Research Trends and Applications / |c edited by Nikos Manouselis, Hendrik Drachsler, Katrien Verbert, Olga C. Santos. |
| 250 | |a 1st ed. 2014. | ||
| 264 | 1 | |a New York, NY : |b Springer New York : |b Imprint: Springer, |c 2014. | |
| 300 | |a XIV, 306 p. 67 illus. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 505 | 0 | |a Collaborative Filtering Recommendation of Educational Content in Social Environments utilizing Sentiment Analysis Techniques -- Towards automated evaluation of learning resources inside repositories -- Linked Data and the Social Web as facilitators for TEL recommender systems in research and practice -- The Learning Registry: Applying Social Metadata for Learning Resource Recommendations -- A Framework for Personalised Learning-Plan Recommendations in Game-Based Learning -- An approach for an Affective Educational Recommendation Model -- The Case for Preference-Inconsistent Recommendations -- Further Thoughts on Context-Aware Paper Recommendations for Education -- Towards a Social Trust-aware Recommender for Teachers -- ALEF: from Application to Platform for Adaptive Collaborative Learning -- Two Recommending Strategies to enhance Online Presence in Personal Learning Environments -- Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem -- COCOON CORE: CO-Author Recommendations based on Betweenness Centrality and Interest Similarity -- Scientific Recommendations to Enhance Scholarly Awareness and Foster Collaboration. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Education. | |
| 650 | 0 | |a Computer networks . | |
| 650 | 1 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Education. |
| 650 | 2 | 4 | |a Computer Communication Networks. |
| 700 | 1 | |a Manouselis, Nikos. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Drachsler, Hendrik. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Verbert, Katrien. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Santos, Olga C. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781493905317 |
| 776 | 0 | 8 | |i Printed edition: |z 9781493905294 |
| 776 | 0 | 8 | |i Printed edition: |z 9781493946563 |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-1-4939-0530-0 |z Texto Completo |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||