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    Monitoring student progress using virtual appliances: A case study

    Autor: 
    Romero Zaldivar, Vicente Arturo
    ;
    Pardo, Abelardo
    ;
    Burgos, Daniel (1)
    ;
    Delgado Kloos, Carlos
    Fecha: 
    05/2012
    Palabra clave: 
    educational data mining; learning analytics; virtual appliances; educational systems; predictive systems; JCR; Scopus
    Tipo de Ítem: 
    Articulo Revista Indexada
    URI: 
    https://reunir.unir.net/handle/123456789/5408
    DOI: 
    http://dx.doi.org/10.1016/j.compedu.2011.12.003
    Dirección web: 
    http://www.sciencedirect.com/science/article/pii/S0360131511003198?via%3Dihub
    Resumen:
    The 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.
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