Análisis de deserción-permanencia de estudiantes universitarios utilizando técnica de clasificación en minería de datos

Abstract

Academic information is analyzed to identify the factors that have more impact on desertion of students of Computer Science Engineering of the University Gastón Dachary in Argentina, by applying data mining techniques. The data source comes from the information provided by the student when they entered the university (personal and educational background) and information generated during the studies. Data are selected and analyzed using different criteria for the representation and application of classification algorithms such as decision trees, bayesian networks and rules. Influential variables on desertion are identified: passed courses, number and grades of courses, origin and age of student when he/she entered the university. Through this process it was possible to identify several variables that characterize the cases of desertion and its relation with academic achievement, especially during the first year of study.