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Formación universitaria

versão On-line ISSN 0718-5006

Resumo

MIRANDA, Mauricio A  e  GUZMAN, Jheser. Analysis of Dropouts of University Students using Data Mining Techniques. Form. Univ. [online]. 2017, vol.10, n.3, pp.61-68. ISSN 0718-5006.  http://dx.doi.org/10.4067/S0718-50062017000300007.

The research discussed in this paper determines the reasons and variables that determine student’s decision to abandon their university studies. Student dropout becomes a major problem for educational institutions, as the loss of students can disrupt short and long-term academic and financial strategies. To evaluate these factors, data provided by the School of Engineering of the Catholic University of the North (UCN) in Antofagasta and Coquimbo (Chile) were used. The results are obtained using a decision tree to predict the retention of students within 78,3% of accuracy. The models built in this analysis show a statistical ROC Curve of 76%, 75%, and 83% success rate for the Bayesian network classifier, decision tree, and neural network respectively.

Palavras-chave : university student retention; student dropout; data mining; education; engineering.

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