Identifying the most relevant causes of student dropout as basis of an Educational Management Systems

Abstract

This paper presents an approach to select the most representative variables in student dropout studies as a basis for designing dropout management systems in engineering programs. The approach is based on a literature review that includes diverse concepts of student dropout, its classifications, analysis models, and factors and variables. Likewise, the approach uses the Pareto principle to identify and prioritize the dropout variables. The information is organized and analyzed to be used as a reference for Universities or Institutions that want to design their analysis model or management system of the student dropout. The study shows that the analysis models have changed over the years; firstly, authors use the psychological models, later, economic models and organizational models; finally, the integration models, and their combinations. Among the variables that were prioritized are gender and family structure, academic performance, satisfaction with the program (expectations), program quality, university’s resources and financing supports.