Abstract

BACALLAO GALLESTEY, Jorge; PARAPAR DE LA RIESTRA, José M; ROQUE GIL, Mercedes  and  BACALLAO GUERRA, Jorge. Árboles de regresión y otras opciones metodológicas aplicadas a la predicción del rendimiento académico. Educ Med Super [online]. 2004, vol.18, n.3, pp. 1-1. ISSN 0864-2141.

This paper is aimed at constructing an algorithm to detect students at high risk for academic failure and at identifying the best preformance predictors. The students that were admitted in the first year at Victoria de Girón Institute of Preclinical Basic Sciences during the course 2001-2002 were characterized according to their preuniversity academic index, roster index, admission test, intelligence test and an indicator of their professional motivation. Classification trees were used to identify the relevant predictors and their optimal cut-off points. A model of ordinal regression was used to evaluate the relative importance of the predictors and to propose the prediction algorithm.Starting only from the roster index, it was obtained a classification procedure that allowed to identify students at the highest risk for academic failure. The cut-offs were 87 and 91 points, which define a trichotomy for the performance prognosis.

Keywords : Classification trees; ordinal regression; performance prediction; admission at higher medical education.