Enhancing Personalized Learning through Artificial Intelligence in Modern Education Systems

Abstract

AI is transforming current education systems by providing personalized learning experiences and adjusting the pace of instruction, content delivery, and learning pace according to a student’s needs. This study investigates the personalization of education through AI in the context of current educational settings, primarily higher education. A systematic search of 41 academic databases identified 17,899 records, and after strict inclusion criteria, we included 45 studies. We followed the PRISMA approach to guarantee methodological transparency in selection, data extraction, and synthesis. The studies included were assessed using a standard bias instrument. The results suggest that the impact of AI-enabled solutions on adaptive learning, student engagement, and administrative efficiency is substantial. Helping to personalize learning, AI fosters better learning outcomes and increased student satisfaction. Yet, there are challenges to AI integration, including ethical issues, data privacy concerns, and the need for robust teacher training and institutional support. This review discusses the transformative potential of AI for education and makes calls for standards to evaluate the efficacy of AI methods, greater collaboration across disciplines, and long-term studies to ensure the fairness and effectiveness of AI implementations. These findings are crucial for educators, policymakers, and institutional leaders seeking to transform and sustain future-ready education systems in an era of AI.