Chemistry Education and Artificial Intelligence (AI) In the 21st Century Nigeria: Prospects, Challenges, and the Way Forward. A Review Article

Abstract

Nigeria stands at a crossroad in modernizing science education. Chemistry, an essential gateway to Science, Technology, Engineering, and Mathematics (STEM) careers continues to show uneven student outcomes, while artificial intelligence (AI) technologies are rapidly changing how Science is taught and learned worldwide. Artificial intelligence (AI) is increasingly recognized as a transformative force in global science education. In Nigerian school chemistry, AI can support conceptual understanding, foster inclusive education, improve evaluation processes, enhance practical competencies, improve instructional efficiency, bridge regional disparities, and expand access to laboratory-like experiences despite infrastructural constraints, digital literacy gaps, data privacy, and security concerns, lack of regulatory framework for integrating AI in Nigerian educational system, and socio-cultural challenges. In addition, the contextualization of AI to align with Nigeria’s diverse linguistics, cultural, and pedagogical needs are challenges that need to be addressed. This paper adopts a conceptual and narrative review approach, synthesizing national educational policy, peer-reviewed research, and global Artificial Intelligence in Education (AIED) evidence to address the research problem. The article synthesizes contemporary evidence and policy documents to map the prospects of deploying AI to strengthen chemistry teaching and learning in Nigeria, identify systemic challenges (infrastructure, teacher capacity, assessment integrity, equity, and ethics), and propose a pragmatic, evidence-informed recommendations for implementation. The review covers conceptual foundations, pedagogical applications, National Digital Learning Policy (NDLP), advantages of AI in chemistry education, some AI tools in chemistry education, international systematic reviews of AI in education, challenges, country-specific analyses of AI readiness, and systemic recommendations, targeted at policymakers, teacher educators, school leaders, and donor/industry partners. The paper argues that while national interest in AI-enabled teaching is rising, sustained policy support, improved infrastructure, teacher professional development linked to curricular aims, scalable blended AI tools for simulations and formative assessment, governance for data privacy, assessment validity, and inclusion are paramount. Limitations and avenues for research are also identified.