DEVELOPING STUDENTS’ METACOGNITIVE STRATEGIES IN TEACHING MATHEMATICS WITH THE INTEGRATION OF ADAPTIVE ARTIFICIAL INTELLIGENCE TECHNOLOGIES

Abstract

The article presents a theoretical study of the didactic conditions for developing students’ metacognitive strategies in teaching mathematics with the integration of adaptive artificial intelligence (AI) technologies. The article examines the discrepancy between the potential of intelligent digital systems and the actual level of development of students’ planning, self-monitoring, and reflection skills. Based on an analysis of psychological and pedagogical literature and modern approaches to the digital transformation of education, the mechanisms of potential metacognitive support provided by AI environments are identified, and a model for their integration into mathematics learning is theoretically substantiated. A structural and functional model for developing metacognitive strategies is proposed, including diagnostic, operational, and reflective components. A typology of “metacognitive deficits” arising during interaction with AI has been developed, and ways to compensate for them through pedagogical design have been identified.