Dependence on Artificial Intelligence Tools and Its Impact on the Depth of Learning in University Students: An Analysis from the Perspective of Academic Self-Regulation

Abstract

This study analyzed the relationship between dependence on artificial intelligence tools and the depth of learning in university students, considering the mediating role of academic self-regulation. A quantitative approach was adopted with a non-experimental, cross-sectional design and an explanatory scope, working with a sample of 210 higher education students. The results revealed a moderate negative relationship between dependence on artificial intelligence and depth of learning, as well as a significant positive relationship between academic self-regulation and deep learning. Likewise, the mediating effect of self-regulation was confirmed, indicating that its level conditions the way students use these technologies. It is concluded that the impact of artificial intelligence on learning is not deterministic, but rather depends on the student's metacognitive competencies, which raises the need to strengthen educational strategies aimed at a critical and reflective use of these tools.