One of the primary challenges facing modern education systems is the creation of a more flexible and effective learning environment for learners with diverse educational characteristics. The rapid development of digital technologies, artificial intelligence (AI), and learning analytics has created favorable conditions for the widespread implementation of personalized education models. A personalized education model aims to optimize the teaching and learning process by considering learners’ individual characteristics, knowledge levels, interests, and learning pace. This article comprehensively analyzes the theoretical foundations, structural components, technological capabilities, and implementation mechanisms of personalized education. Particular attention is devoted to examining the role of artificial intelligence, adaptive learning systems, and learning analytics in the development of this model. Based on scientific studies conducted during the last decade, the article systematically presents the advantages, challenges, and future development directions of personalized education.
S. et al. (Fri,) studied this question.