Impact of AI-Enhanced Training on Green Chemistry Understanding of Secondary School Chemistry Teachers

Ayotomiwa Abel Akinde (Department of Science Education, University of Lagos, Lagos State, Nigeria)
Toyin Eunice Owoyemi (Department of Science Education, University of Lagos, Lagos State, Nigeria)

Journal of Research in Environmental and Science Education
Vol. 3 No. 2 (2026): Journal of Research in Environmental and Science Education

Green chemistry education is increasingly recognised as essential for aligning chemistry instruction with Education for Sustainable Development goals, yet secondary chemistry teachers often lack adequate conceptual understanding and pedagogical strategies to integrate green chemistry principles into classroom practice. While artificial intelligence offers promising avenues for personalised teacher professional development, AI-enhanced training specifically targeting green chemistry competencies remains underexplored in Sub-Saharan African contexts. This study examined the impact of an AI-enhanced training programme on secondary school chemistry teachers’ understanding of green chemistry principles and evaluated the effectiveness of a structured, need-based professional development intervention. A two-phase design was employed: Phase 1 used the ADDIE model to develop a training module delivered via an AI-powered Mini Course Generator platform, while Phase 2 implemented a single-group pre-test–post-test design with 43 chemistry teachers from Education District IV, Lagos State, Nigeria. Participants completed the Green Chemistry Understanding Test before and after a four-week self-paced intervention comprising three modules covering introduction to green chemistry, the twelve principles, and classroom integration strategies. The AI platform personalised learning pathways, generated contextualised materials, and provided automated feedback. Results showed statistically significant improvement from pre-test (M = 9.58, SD = 2.95) to post-test (M = 14.51, SD = 3.21), t(42) = -21.47, p <.001, representing a 51% gain in understanding with a very large effect size (Cohen’s d = 1.62). The findings demonstrate that structured, AI-enhanced professional development can effectively address teachers’ green chemistry knowledge gaps. Recommendations include scaling up AI-supported training across education districts, integrating green chemistry and AI literacy into pre-service and in-service teacher education curricula, and strengthening national curriculum frameworks to support sustainability-oriented chemistry instruction.