abstract
- This study uses advanced data science techniques to explore the variables that influence university dropout rates. Through predictive models and the integration of demographic, socioeconomic, and academic data, key factors are identified and risk estimates are provided, with the goal of guiding interventions to improve student retention. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.