Enhancing Conceptual Understanding in Chemistry Education Through AI-Powered Tutoring Systems

This research explores the transformative role of AI-powered tutoring systems in enhancing students’ conceptual understanding in chemistry education. With the integration of intelligent tutoring systems (ITS), adaptive learning technologies, and natural language processing (NLP), AI provides personalized learning experiences tailored to individual student needs. The study employs a mixed-methods approach to assess the effectiveness of AI tools in improving comprehension, retention, and engagement among high school and undergraduate chemistry students. Data is gathered through experimental interventions, pre- and post-tests, and surveys. Results indicate that AI-tutored students outperform those in traditional settings, demonstrating improved problem-solving skills and deeper conceptual grasp. The findings support the integration of AI in chemistry curricula and offer practical recommendations for educators and policymakers.