Automatic feature selection for desertion and graduation prediction: A chilean case

B. Peralta, T. Poblete, L. Caro

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferencia

1 Cita (Scopus)

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.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016
EditorialIEEE Computer Society
ISBN (versión digital)9781509033393
DOI
EstadoPublicada - 27 ene 2017
Evento35th International Conference of the Chilean Computer Science Society, SCCC 2016 - Valparaiso, Chile
Duración: 10 oct 201614 oct 2016

Conferencia

Conferencia35th International Conference of the Chilean Computer Science Society, SCCC 2016
PaísChile
CiudadValparaiso
Período10/10/1614/10/16

    Huella digital

Áreas temáticas de ASJC Scopus

  • Ingeniería (todo)
  • Informática (todo)

Citar esto

Peralta, B., Poblete, T., & Caro, L. (2017). Automatic feature selection for desertion and graduation prediction: A chilean case. En Proceedings of the 2016 35th International Conference of the Chilean Computer Science Society, SCCC 2016 [7836055] IEEE Computer Society. https://doi.org/10.1109/SCCC.2016.7836055