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Gallego Vico, Daniel, Barra Arias, Enrique ORCID: https://orcid.org/0000-0001-9532-8962, Rodríguez Pérez, Pedro and Huecas Fernández-Toribio, Gabriel
ORCID: https://orcid.org/0000-0001-5673-9312
(2013).
Incorporating proactivity to context-aware recommender systems for e-learning.
In: "World Congress on Computer and Information Technology (WCCIT 2013)", 22/06/2013 - 24/06/2013, Sousse, Tunisia. pp. 1-6.
Title: | Incorporating proactivity to context-aware recommender systems for e-learning |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | World Congress on Computer and Information Technology (WCCIT 2013) |
Event Dates: | 22/06/2013 - 24/06/2013 |
Event Location: | Sousse, Tunisia |
Title of Book: | World Congress on Computer and Information Technology (WCCIT 2013) |
Date: | 2013 |
Subjects: | |
Freetext Keywords: | Proactivity, Context-awareness, E-learning, Recommender Systems |
Faculty: | E.T.S.I. Telecomunicación (UPM) |
Department: | Ingeniería de Sistemas Telemáticos |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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Recommender systems in e-learning have proved to be powerful tools to find suitable educational material during the learning experience. But traditional user request-response patterns are still being used to generate these recommendations. By including contextual information derived from the use of ubiquitous learning environments, the possibility of incorporating proactivity to the recommendation process has arisen. In this paper we describe methods to push proactive recommendations to e-learning systems users when the situation is appropriate without being needed their explicit request. As a result, interesting learning objects can be recommended attending to the user?s needs in every situation. The impact of this proactive recommendations generated have been evaluated among teachers and scientists in a real e-learning social network called Virtual Science Hub related to the GLOBAL excursion European project. Outcomes indicate that the methods proposed are valid to generate such kind of recommendations in e-learning scenarios. The results also show that the users' perceived appropriateness of having proactive recommendations is high.
Item ID: | 25840 |
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DC Identifier: | https://oa.upm.es/25840/ |
OAI Identifier: | oai:oa.upm.es:25840 |
Official URL: | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?... |
Deposited by: | Memoria Investigacion |
Deposited on: | 13 May 2014 18:22 |
Last Modified: | 01 Apr 2023 08:28 |