Personalized learning, powered by artificial intelligence (AI), is revolutionizing education by tailoring instruction to individual students' needs, abilities, and learning styles. This paper explores the current state and future potential of AI-driven personalized learning systems. It examines how AI techniques such as machine learning, natural language processing, and knowledge representation can be leveraged to create adaptive learning experiences that optimize educational outcomes. The paper reviews existing research on AI in education, discusses key technologies and architectures for personalized learning systems, and presents case studies of successful implementations. Challenges and ethical considerations around AI in education are also explored. The paper argues that AI-driven personalized learning, combined with human instruction, has immense potential to enhance educational effectiveness, engagement, and equity. However, careful design and responsible deployment of these systems will be essential. The paper concludes with recommendations for future research and development in this field.
Katiyar et al. (Thu,) studied this question.