Personalized Learning In The Age Of AI

Opportunities And Challenges For University Students

Abstract

Personalized learning has gained increasing attention in higher education, particularly with the rapid integration of Artificial Intelligence (AI). While traditional teaching methods often fail to address the diverse needs of university students of UM Buton, AI-powered personalized learning systems offer adaptive pathways that can enhance engagement, flexibility, and academic achievement.  Method of this study applies a literature-based analytical approach by reviewing recent empirical research, case studies, and conceptual frameworks on AI-driven personalized learning in higher education. The analysis focuses on adaptive algorithms, learning analytics, and student-centered design. The findings highlight that AI enables more dynamic and individualized learning experiences for university students by tailoring content, pace, and feedback. Evidence shows improved student motivation, self-directed learning, and performance outcomes. However, critical challenges remain, including concerns over data privacy, equity of access, digital literacy, and the ethical use of algorithms in educational settings.The conclusion is  AI-driven personalized learning presents significant opportunities for enhancing higher education but also poses challenges that require careful management. Universities should adopt balanced strategies that integrate technology with pedagogical goals, while ensuring inclusivity, transparency, and ethical standards.