Abstract
ABSTRACT University dropout is a major problem in Latin America and the Caribbean; in Colombia, around 50% of students who enter university complete their studies. This phenomenon is multi-causal; therefore, it is necessary to perform an analysis in different scenarios, in order to create strategies that help permanence and graduation. This paper presents an alternative to identify some factors that lead a student to drop out of the Universidad del Cauca, based on data science methodologies. It was found that desertion is influenced by academic factors, such as areas of knowledge, semester and average, social context such as stratum and place of origin, and individual factors such as age and gender.
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