AI-POWERED INQUIRY-BASED LEARNING: TRANSFORMING SCIENCE TEACHING AND LEARNING

Abstract

Science education continues to experience persistent challenges in many developing contexts, particularly in relation to teacher-centred instruction, limited laboratory facilities, and weak student engagement with scientific processes. At the same time, Artificial Intelligence (AI) is reshaping educational practice by introducing tools that support personalization, simulation, automated feedback, and adaptive learning. This paper examined AI-powered inquiry-based learning as an emerging pedagogical approach for improving science education in the digital age. Grounded in constructivist learning theory, the paper synthesized recent literature from Nigeria and global contexts to explain how AI tools such as intelligent tutoring systems, virtual laboratories, generative AI applications, and learning analytics can support inquiry-based science instruction. The paper argued that AI, when aligned with inquiry pedagogy, strengthens students’ scientific reasoning, improves engagement, and expands access to learning resources. However, the effectiveness of this integration depends on teacher competence, infrastructural readiness, and ethical use of AI systems. The paper concludes that AI-powered inquiry-based learning represents a significant shift in science education practice, particularly in resource-constrained environments.