Implementing an early warning system for dropout prevention in higher education: a case study

Abstract

Student dropout is a multifactorial problem affecting higher education, linked to academic, socioeconomic, and institutional factors. This study analyzes the impact of institutional support on student retention through an early warning system. The objective is to evaluate data-driven intervention strategies to reduce university dropout. An analytical methodology with document review and an integrated panel model was used to identify at-risk students. The results show that continuous monitoring and academic support reduce dropout rates. It is concluded that the implementation of technological tools and preventive strategies favors student retention, and their application is recommended in various educational contexts to improve retention and academic quality.