Artificial Intelligence and Personalized Learning in Higher Education: Transforming Student-Centred Pedagogy, Learning Outcomes and Educational Equity

Abstract

Artificial Intelligence (AI) is rapidly transforming higher education by enabling learning environments that can respond to the individual needs, abilities, preferences and learning progress of students. Personalized learning, traditionally associated with differentiated instruction and adaptive educational technologies, has acquired new possibilities through machine learning, natural language processing, intelligent tutoring systems, learning analytics and generative AI. This paper critically examines the emerging role of AI in developing student-centred personalized learning environments in higher education. It analyses how AI can support adaptive content delivery, individualized feedback, intelligent assessment, learning-path recommendations, student engagement and self-regulated learning. Recent international research indicates that AI-enabled personalized learning can enhance engagement, motivation and learning performance, although the evidence also highlights significant concerns related to data privacy, algorithmic bias, digital inequality, academic integrity, teacher readiness and excessive dependence on automated systems. A human-centred approach is therefore essential in which AI complements rather than replaces teachers. The paper argues that the future of personalized higher education depends not merely on technological sophistication but on pedagogically meaningful, ethical, inclusive and evidence-based implementation. The study concludes by proposing a human-AI collaborative framework for student-centred higher education.