AI as a teaching augmentor : a review of the integration of AI in science education

Abstract

The integration of Artificial Intelligence (AI) in science education has witnessed significant advancements, transforming traditional teaching and learning practices. This narrative review examines the roles of AI in science education over a decade (2013–2022), focusing on three key areas, namely, AI-based instructional tools that offer personalized and adaptive learning experiences; AI-enabled learning environments that facilitate immersive and interactive exploration of scientific concepts; and AI-supported assessment tools that enhance feedback and evaluation processes. The study highlights the potential of synergistically integrating these roles to create dynamic and adaptive educational systems. It also addresses challenges such as ethical considerations, teacher preparedness, and resource disparities, which influence AI adoption and efficacy in science education. By exploring current trends, practices, and outcomes, this review underscores AI's capacity to augment traditional teaching methods, fostering student engagement, critical thinking, and personalized learning pathways. Recommendations for teacher training and curriculum development are provided to ensure effective integration and sustainable implementation of AI technologies in science education.