Integration and competence in artificial intelligence: predictors of academic performance in university students.

Abstract

This study analyzes the relationship between the integration of Artificial Intelligence tools into study practices, proficiency in their use, and the academic performance perceived by university students. A questionnaire was administered to 331 university students, assessing three constructs via Likert scales. Factor analysis confirmed three factors explaining 75.4% of the total variance. Multiple regression analysis results reveal that AI integration and proficiency in its use significantly predict academic performance, explaining 65.3% of the variance. A synergistic relationship between the two variables was identified, suggesting a "virtuous circle" in which skill development facilitates greater integration and vice versa, with implications for educational policies and pedagogical practices.