Artificial Intelligence in the Redesign of the Theory and Practice of Self-Directed Learning

The integration of artificial intelligence into self-directed learning has a major impact on educational practice by offering a personalized, adaptive, and contextual learning experience. Our study is devoted to the transformative potential of artificial intelligence in self-directed learning (self-education) and analyses the impact of artificial intelligence technologies on student engagement, knowledge retention, and independence as the autonomy of educational activity. The theoretical analysis of existing research on the problem is used to assess the effectiveness of these technologies. The results show that students who used artificial intelligence may demonstrate a higher level of self-directed learning than students using traditional learning methods. The similarity between educational models based on artificial intelligence and modern theories of self-directed learning highlights the potential of artificial intelligence technologies for developing learners’ self-control and motivation. However, some problems remain that act as barriers to using artificial intelligence in education. In this article, they include internet access issues, ethical concerns related to data privacy, and algorithmic bias, which underscores the need for equal access to artificial intelligence technologies and other digital technologies. These problems can be overcome through interdisciplinary cooperation among specialists involved in developing, implementing, and improving educational technologies based on artificial intelligence. By addressing these problems, education that uses artificial intelligence may become an important step toward the democratization of education by providing access to quality education for various population groups.