Analysis of Student Desertion in a Systems and Computing Engineering Undergraduate Program

Abstract

Data mining techniques are mainly focused on supporting the decision makers in a specific organization. Student attrition is a common phenomenon that worries public and private universities, which are affected financially and socially. Several studies have addressed this issue. However, they have mainly focused on academic, social, demographic, and economic aspects. In this paper, we propose a method for analyzing academic desertion in the context of a Systems and Computing Engineering undergraduate program by providing a view of this issue from a KDD (knowledge discovery in databases) perspective and using techniques for identifying students’ behavioral patterns. Unlike other proposals, we also consider variables provided by the BADyG test. This proposal is important because it will support higher education institutions in decision-making and creating action plans to reduce the high rate of student attrition.

Análisis de características que influyen en la deserción estudiantil en el contexto de una universidad latinoamericana

“…Existe una variedad de trabajos relacionados con la aplicación de EDM para el análisis de la deserción estudiantil universitaria los cuales permiten a las instituciones educativas establecer planes de acción conducentes a reducir sus tasas de deserción, mejorar la calidad de la educación y favorecer sus indicadores de desempeño (Bakhshinategh et al, 2018;Castro et al, 2018;Castro et al, 2019;Munizaga et al, 2018). Algunas cifras sustentan la problemática analizada en este tipo de estudios.…”