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dc.contributor.authorRomero Zaldivar, Vicente Arturo
dc.contributor.authorPardo, Abelardo
dc.contributor.authorBurgos, Daniel (UNIR)
dc.contributor.authorDelgado Kloos, Carlos
dc.date2012-05
dc.date.accessioned2017-08-10T14:49:23Z
dc.date.available2017-08-10T14:49:23Z
dc.identifier.issn1873-782X
dc.identifier.urihttp://reunir.unir.net/123456789/5408
dc.description.abstractThe interactions that students have with each other, with the instructors, and with educational resources are valuable indicators of the effectiveness of a learning experience. The increasing use of information and communication technology allows these interactions to be recorded so that analytic or mining techniques are used to gain a deeper understanding of the learning process and propose improvements. But with the increasing variety of tools being used, monitoring student progress is becoming a challenge. The paper answers two questions. The first one is how feasible is to monitor the learning activities occurring in a student personal workspace. The second is how to use the recorded data for the prediction of student achievement in a course. To address these research questions, the paper presents the use of virtual appliances, a fully functional computer simulated over a regular one and configured with all the required tools needed in a learning experience. Students carry out activities in this environment in which a monitoring scheme has been previously configured. A case study is presented in which a comprehensive set of observations were collected. The data is shown to have significant correlation with student academic achievement thus validating the approach to be used as a prediction mechanism. Finally a prediction model is presented based on those observations with the highest correlation.es_ES
dc.language.isoenges_ES
dc.publisherComputers and Educationes_ES
dc.relation.ispartofseries;vol. 58, nº 4
dc.relation.urihttp://www.sciencedirect.com/science/article/pii/S0360131511003198?via%3Dihubes_ES
dc.rightsrestrictedAccesses_ES
dc.subjecteducational data mininges_ES
dc.subjectlearning analyticses_ES
dc.subjectvirtual applianceses_ES
dc.subjecteducational systemses_ES
dc.subjectpredictive systemses_ES
dc.subjectJCRes_ES
dc.titleMonitoring student progress using virtual appliances: A case studyes_ES
dc.typeArticulo Revista Indexadaes_ES
reunir.tag~ARIes_ES
dc.identifier.doihttp://dx.doi.org/10.1016/j.compedu.2011.12.003


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