Automatic Feature Selection for Desertion and Graduation Prediction: A Chilean Case

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Autor:
Peralta Márquez, Billy - Poblete, T. - Caro Saldivia, Luis - IEEE
URI:
http://repositoriodigital.uct.cl/handle/10925/2792
Datos de publicación:
PROCEEDINGS OF THE 2016 35TH INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY (SCCC),Vol.,,2016
Temas:
feature selection - decision trees - education
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Resumen:
The high rate of university dropout and low graduation rates are very relevant social problems today. Since there are many possible causes of desertion and university graduation, in this paper, we propose to find, analyze and weigh the factors that allow predicting if a student will drop out or graduate according to prior information available using data mining techniques and statistical models. We will focus in the case of Catholic University of Temuco, using real data from that institution. This study reveals relevant variables in opinion of human experts, which demonstrates the ability of automatic models to represent the dropout and graduation at the university.

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