IMPACT OF ARTIFICIAL INTELLIGENCE ON COGNITIVE LEARNING PROCESSES IN UNIVERSITY STUDENTS

Abstract

The use of artificial intelligence (AI) in higher education has intensified in the last five years, directly modifying the cognitive learning processes of university students. The aim of this article is to analyze, from a theoretical review of recent literature (2020–2025), how different types of AI-based tools —intelligent tutors, learning analytics, adaptive systems, and generative models such as ChatGPT— influence processes such as attention, memory, deep learning strategies, metacognition, critical thinking, and self-regulation of learning. Evidence shows that, when AI is integrated as pedagogical support (personalization, formative feedback, metacognitive scaffolding), it tends to enhance the use of deep learning strategies and the development of metacognitive and self-regulatory competencies. However, when used as a substitute for cognitive activity (automatic task generation, unelaborated responses), it is associated with risks to the student's critical thinking, creativity, and agency, as well as increasing the likelihood of academic dishonesty behaviors. It also highlights the mediating role of AI literacy and self-regulation strategies in the way students relate to these technologies. It is concluded that the cognitive impact of AI is not intrinsically positive or negative, but depends on the pedagogical design, AI literacy and the degree of agency that students maintain over their own learning.