Dropout Rate Model Analysis at an Engineering School

The phenomenon of student dropout in higher education presents significant challenges for students, higher education institutions, governments, and society. The present study focuses on the dropout rates within the engineering programmes at one school of engineering in Mexico. This study uses a quantitative approach with a non-experimental cross-sectional design. Exploratory, descriptive, and correlational analyses of historical data from the University Information and Administration Integral System were performed. A logistic regression model was applied to assess the influence of various demographic, academic, and socioeconomic factors on the likelihood of student dropout. The results show some predictive variables, namely, Gender, Displaced students from home, High school GPA, and Mathematical skills. In conclusion, the group of students identified as the most likely to drop out comprised males who were studying very far away from home, who studied in a private high school in a general programme (not technological), and who presented lower grades in math. Since most dropouts were identified in the first two semesters, students who perform poorly in these semesters and have the former characteristics could benefit from special attention.