Literaturnachweis - Detailanzeige
| Autor/inn/en | Romero-Zaldivar, Vicente-Arturo; Pardo, Abelardo; Burgos, Daniel; Delgado Kloos, Carlos |
|---|---|
| Titel | Monitoring Student Progress Using Virtual Appliances: A Case Study |
| Quelle | In: Computers & Education, 58 (2012) 4, S.1058-1067 (10 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 0360-1315 |
| DOI | 10.1016/j.compedu.2011.12.003 |
| Schlagwörter | Academic Achievement; Prediction; Learning Experience; Data; Data Collection; Research Tools; Electronic Learning; Educational Technology; Computer Uses in Education; Use Studies; Models; Correlation; Case Studies; Observation; Computer Simulation; Computer System Design; Feasibility Studies |
| Abstract | 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. (Contains 5 tables and 2 figures.) (As Provided). |
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| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2017/4/10 |
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