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dc.contributor.authorCordero Zambrano, J.es_ES
dc.contributor.authorAguilar Castro, J.es_ES
dc.contributor.authorEncalada Encalada, A.es_ES
dc.contributor.authorValdiviezo Diaz, P.es_ES
dc.contributor.authorRiofrio Calderon, G.es_ES
dc.date.accessioned2017-06-16T22:02:17Z-
dc.date.available2016-07-22es_ES
dc.date.available2017-06-16T22:02:17Z-
dc.date.submitted01/10/2016es_ES
dc.identifier10.1007/978-3-319-48024-4_17es_ES
dc.identifier.isbn1929-7750es_ES
dc.identifier.other10.1007/978-3-319-48024-4_17es_ES
dc.identifier.urihttp://dspace.utpl.edu.ec/handle/123456789/18739-
dc.description.abstractn this paper we propose the utilization of the Learning Analytics paradigm in a Smart Classroom. Learning Analytics can extract knowledge from a Smart Classroom platform to better understand students and his/her learning processes. In this way, a Smart Classroom can understanding and optimizing the learning process and the teaching environments proposed. The smart classroom can adapt its components to improve students� performance, among others. Particularly, this paper proposes a framework about how Learning Analytics paradigm can be used in a Smart Classroom, in order to provide knowledge about the activities taking place within it. The framework is defined like a closed cycle of Learning Analytics tasks, which generate metrics used like feedback to optimize the pedagogical model proposed by the smart Classroom. The metrics evaluate the learning process and pedagogical practice provided by the smart Classroom.es_ES
dc.languageIngléses_ES
dc.subjectLearning Analyticses_ES
dc.subjectSmart Classroomes_ES
dc.titleA general framework for Learning Analytic in a Smart Classroomes_ES
dc.typeArticlees_ES
dc.publisherCommunications in Computer and Information Sciencees_ES
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