Adaptive Artificial Intelligence and Cognitive Processing: The Impact of Immediate Feedback Systems on the Development of Students’ Critical Thinking

Abstract

The integration of adaptive artificial intelligence into educational environments has brought about a substantive reconfiguration of teaching and learning processes by transforming the ways in which students interact with content, regulate their cognitive processes, and receive feedback on their performance. Unlike traditional digital platforms, adaptive systems employ algorithms capable of interpreting cognitive and behavioural data in order to continuously adjust instructional sequencing, task complexity, and feedback mechanisms, thereby directly influencing the depth of learning. Within this context, immediate feedback emerges as a strategic component in the development of critical thinking, understood as a set of higher-order cognitive skills encompassing analysis, evaluation, inference, and self-regulation. However, the examination of scientific production reveals a persistent gap between the conceptual potential attributed to these technologies and their actual educational impact, as many systems continue to operate according to superficial corrective logics that prioritise answer validation over cognitive reflection. To address this issue, a descriptive–analytical documentary review was conducted, guided by the PRISMA 2020 protocol, with the aim of critically and systematically examining this field of study. The findings indicate that the impact of adaptive artificial intelligence on students’ critical thinking is neither automatic nor uniform, but rather contingent upon its coherent alignment with robust cognitive and pedagogical principles, as well as the design of feedback systems oriented towards metacognition and deep learning.