Artificial Intelligence and Personalized Learning in Science Classrooms: Rethinking Learning Styles for Adaptive Teaching

Chapter Highlights  The chapter examines how AI transforms science education through personalized learning and adaptive teaching based on learners’ cognitive needs and performance. It critically reviews learning styles theories, highlighting their limitations and emphasizing learner cognition, metacognition, cognitive load and self-regulated learning as stronger foundations for instruction. It explains how AI tools, including intelligent tutoring systems, virtual laboratories, adaptive platforms, and real-time feedback, improve conceptual understanding and student engagement. It discusses implementation challenges in Nigeria, including infrastructure deficits, limited digital literacy, curriculum constraints, inequality and ethical concerns. The chapter concludes that AI redefines personalization while teachers remain central to effective science learning. It recommends strengthening infrastructure, teacher capacity, curriculum reform, ethical AI governance, equitable access and continuous research.