Academic Management System for the identification and tracking of academic talent in university settings

Abstract

Objective: To develop an Academic Management System for identifying and tracking academic talent at the University of Matanzas using an evidence-based approach. Methods: A web platform (React, Next.js, PostgreSQL) was implemented with a multidimensional data model enabling longitudinal tracking. It includes automated scoring algorithms to classify students into three levels (Potential, Talent, Exceptional Talent) and generate predictive alerts. Validation was conducted with university administrators (n=5) using a Likert scale questionnaire (1-5 points). Results: The overall evaluation was excellent (4.46/5.00), highlighting the relevance of indicators (4.8) and recommendation intent (4.8). Conclusions: The system facilitates objective and proactive management of academic talent, demonstrating high perceived utility and potential for institutional adoption.