Análise exploratória e preditiva de dados acadêmicos sobre evasão escolar em Cursos de Graduação do Instituto Federal da Bahia

Abstract

School dropout is a global socio-educational and economic problem affecting public and private institutions at all educational levels, with impacts ranging from the individual to the collective sphere. In Brazil, student retention measures span from national basic education programs, like Pe-de-Meia ´ , to specific higher education policies, such as those implemented by the Federal Institute of Bahia (IFBA). However, undergraduate dropout rates remain high, demanding continuous analyses to support new strategies and outline profiles of students prone to leaving. Thus, this descriptive and quantitative study conducted an exploratory and predictive analysis of academic data, developing and training machine learning models to identify school dropout patterns.