Predicting Student Retention in a Medical Sciences discipline

Abstract

This research analyzed the factors that influence student retention in a medical science discipline, using the Hierarchical Analysis Process as the main methodological tool. This approach allowed for the hierarchical and weighting of multiple relevant criteria, identified from an exhaustive review of the literature and consultations with experts in the educational field. The data were collected through surveys applied to students and teachers, complemented by institutional statistics related to academic permanence. The objective of the study was to develop a predictive model that would identify the key factors for student retention, providing tools for strategic decision-making in the design of educational policies. Among the main findings, it was highlighted that academic and psychological support, together with curricular flexibility, were the factors with the greatest weight in student retention. Likewise, significant barriers were identified, such as excessive academic workload and lack of social integration in the university environment. The conclusions pointed out the importance of implementing personalized support and guidance programs, as well as adjusting the curricular load to improve the student experience. Furthermore, the application of the developed model in other disciplines was recommended to validate its usefulness and replicability. This study provides an innovative approach by combining multi-criteria decision-making techniques with the analysis of educational factors, offering a systematic and objective perspective to address the problem of student dropout in medical sciences.