Personalized learning of future teachers through Artificial Intelligence technologies
Abstract. The article analyzes the theoretical foundations and describes the practice-oriented experience of future educators training through the usage of Artificial Intelligence (AI) technologies. Cutting edge approaches to personalized learning are examined, focusing on the application of intelligent systems to design individual educational trajectories, adapt the content and pace of learning to students’ needs, and organize effective feedback. Particular attention is paid to examples of the practical integration of AI into the system of pedagogical education: the use of chatbots and recommender systems, the generation of adaptive courses, the application of educational data analysis tools, and the creation of virtual simulators for modeling pedagogical situations. The study has used an analysis of actual scientific sources as well as a synthesis of empirical experience in implementing AI technologies in the educational process. Positive pedagogical effects have been identified, including increased student motivation and engagement, improved academic performance, and the development of research and digital competencies. Risks and limitations related to information reliability, academic integrity, and teacher’ innovation readiness are simultaneously outlined. Conclusions are drawn regarding the educational potential of AI-based personalized learning, and practical recommendations are offered for its integration into teacher training programs.