27 enero, 2017 -
Peralta, B.(a), Poblete, T.(a), Caro, L.,(a)
(a)Escuela de Ingeniería Informática, Universidad Católica de Temuco, Temuco, Chile
PROCEEDINGS – INTERNATIONAL CONFERENCE OF THE CHILEAN COMPUTER SCIENCE SOCIETY, SCCC
Fecha de publicación: 27 de enero de 2017
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.