Impact of using AI systems on students' learning motivation: risk of reduced autonomy

Abstract

This article examines the impact of artificial intelligence on student motivation and autonomy in the educational process. It demonstrates that excessive reliance on AI tools can undermine students' intrinsic motivation, weakening their sense of competence and autonomy. Key risks include decreased cognitive load, the development of passive information consumption, and weakened critical thinking and independent knowledge-seeking skills. At the same time, the article identifies conditions under which the use of AI can contribute to increased learning motivation: personalization of learning tailored to individual needs, the development of new forms of assessment, and the targeted development of metacognitive skills. Particular attention is paid to the ethical aspects of integrating AI into education, emphasizing the need to develop students' understanding of their responsibility for using technology, the ability to recognize algorithmic bias, and adhere to principles of privacy and data protection. The conclusion is that the successful implementation of AI in educational practice requires a balanced combination of automation and active student participation, the development of pedagogical strategies that stimulate critical understanding of information, and the establishment of an interdisciplinary dialogue between educators, AI system developers, and educational experts.