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dc.contributor.authorRodríguez Marín, Paula Andreaes_ES
dc.contributor.authorGiraldo, Mauricioes_ES
dc.contributor.authorTabares, Valentinaes_ES
dc.contributor.authorDuque, Néstores_ES
dc.contributor.authorOvalle, Demetrioes_ES
dc.date.accessioned2017-01-09T12:04:17Z
dc.date.available2017-01-09T12:04:17Z
dc.date.issued2016-11-15es_ES
dc.identifier.citationADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 5 (2016)es_ES
dc.identifier.issn2255-2863es_ES
dc.identifier.urihttp://hdl.handle.net/10366/132098
dc.description.abstractIn a face-class, where the student group is heterogeneous, it is necessary to select the most appropriate educational resources that support learning for all. In this sense, multi-agent system (MAS) can be used to simulate the features of the students in the group, including their learning style, in order to help the professor find the best resources for your class. In this paper, we present MAS to educational resources recommendation for group students, simulating their profiles and selecting resources that best fit. Obtained promising results show that proposed MAS is able to delivered educational resources for a student group.es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherEdiciones Universidad de Salamanca (EspaÑa)es_ES
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputaciónes_ES
dc.subjectInformóticaes_ES
dc.subjectComputinges_ES
dc.subjectInformation Technologyes_ES
dc.titleEducational Resources Recommendation System for a heterogeneous Student Groupes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivs 3.0 Unported
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