Modeling higher education dropout on IFMS campuses through socioeconomic educational data (Revista Contexto & Educação, 2024)
Several studies highlight the different factors (economic, social, institutional, among others) that influence school dropout in Brazilian Higher Education Institutions (HEIs). With this in mid, we used data from the 8campuses of the Instituto Federal de Mato Grosso do Sul (IFMS) to ascertain, through logistic regression, whether the characteristics present in these data can influence student dropout. After preparing, transforming, and analyzing logistic regression models, variables were identified that determine the student's probability of dropping out or completing their course.  We conclude that the identification of variables related to dropout should be done in each institution, and preferably crossed with global economic indicators and information on factors related to the institution and the labor market.
Keywords: School dropout; Regression analysis; Socio-economic analysis; Technical education