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

Authors

DOI:

https://doi.org/10.70232/jrese.v3i2.65

Keywords:

AI-Enhanced Training, Green Chemistry, Teacher Professional Development, Secondary Education, Sustainability Education

Abstract

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.

References

Abdulayeva, A., Zhanatbekova, N., Andasbayev, Y., & Boribekova, F. (2025). Fostering AI literacy in pre-service physics teachers: Inputs from training and co-variables. Frontiers in Education, 10, Article 1505420. https://doi.org/10.3389/feduc.2025.1505420

Almasri, F. (2024). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education, 54, 977-997. https://doi.org/10.1007/s11165-024-10176-3

Alwakid, W. N., Dahri, N. A., Humayun, M., & Alwakid, G. N. (2025). Exploring the role of AI and teacher competencies on instructional planning and student performance in an outcome-based education system. Systems, 13(7), Article 517. https://doi.org/10.3390/systems13070517

Amdan, M. A. B., Janius, N., Saidin, M. S. B., & Kasdiah, M. A. H. B. (2025). Impact of artificial intelligence in TVET and STEM education among higher learning students in Malaysia. Journal of Research in Mathematics, Science, and Technology Education, 2(1), 1-14. https://doi.org/10.70232/jrmste.v2i1.15

Basheer, A., Gulacar, O., Sindiani, A., & Eilks, I. (2025). The impact of an intervention on plastics and bioplastics on pre-service science teachers’ green chemistry and sustainability awareness and their attitudes toward environmental education. Education Sciences, 15(3), Article 322. https://doi.org/10.3390/educsci15030322

Cannon, A., Anderson, K., Enright, M., Kleinsasser, D., Klotz, A., O’Neil, N., & Tucker, L. (2023). Green chemistry teacher professional development in New York state high schools: A model for advancing green chemistry. Journal of Chemical Education, 100, 2224-2232. https://doi.org/10.1021/acs.jchemed.2c01173

Carangue, D., Geverola, I., Jovero, M., Lopez, E., Pizaña, A., Salmo, J., Silvosa, J., & Picardal, J. (2021). Green chemistry education among senior high school chemistry teachers: Knowledge, perceptions, and level of integration. Recoletos Multidisciplinary Research Journal, 9(2), 15–33. https://doi.org/10.32871/rmrj2109.02.04

Cohen, J. (1988). Statistical power analysis for the behavioural sciences (2nd ed.). Lawrence Erlbaum Associates.

Ding, A. E., Shi, L., Yang, H., & Choi, I. (2024). Enhancing teacher AI literacy and integration through different types of cases in teacher professional development. Computers and Education Open, 6, Article 100178. https://doi.org/10.1016/j.caeo.2024.100178

Dogan, S., Nalbantoglu, U. Y., Celik, I., & Dogan, N. A. (2025). Artificial intelligence professional development: a systematic review of TPACK, designs, and effects for teacher learning. Professional Development in Education, 51(3), 519–546. https://doi.org/10.1080/19415257.2025.2454457

Feldman-Maggor, Y., Blonder, R., & Alexandron, G. (2024). Perspectives of generative AI in chemistry education within the TPACK framework. Journal of Science Education and Technology, 34, 1-12. https://doi.org/10.1007/s10956-024-10147-3

Gibson, D., Kovanović, V., Ifenthaler, D., Dexter, S., & Feng, S. (2023). Learning theories for artificial intelligence promoting learning processes. British Journal of Educational Technology, 54(5), 1125-1146. https://doi.org/10.1111/bjet.13341

Ibrahim, M., Abas, A., Yahaya, A., Taha, H., Ahmad, C., & Yahaya, R. (2025). Exploring environmental sustainability awareness: perspectives of rural and urban school students and teachers on green chemistry and strategies for achieving sustainable development goals. Journal of Lifestyle and SDGs Review, 5(3), Article e04946. https://doi.org/10.47172/2965-730X.SDGsReview.v5.n03.pe04946

Kim, J. (2023). Leading teachers’ perspective on teacher-AI collaboration in education. Education and Information Technologies, 29, 8693-8724. https://doi.org/10.1007/s10639-023-12109-5

Koulougliotis, D., Paschalidou, K., & Salta, K. (2023). Secondary school students’ engagement with environmental issues via teaching approaches inspired by green chemistry. Sustainability, 16(16), Article 7052. https://doi.org/10.3390/su16167052

Laurensia , L. (2024). Global trends research and application of green chemistry and education: A bibliometric analysis (1994–2023). Journal of Education for Sustainable Development Studies, 1(1), 28-40. https://doi.org/10.70232/nveahh04

Lee, H., & Bryan, L. (2025). Integrating AI in teacher education: Exploring the impact on preservice teacher competencies. Professional Development in Education, 51, 478-494. https://doi.org/10.1080/19415257.2025.2490000

Lee, I., & Perret, B. (2022). Preparing high school teachers to integrate AI methods into STEM classrooms. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12783-12791. https://doi.org/10.1609/aaai.v36i11.21557

Meylani, R. (2024). Artificial intelligence in the education of teachers: A qualitative synthesis of the cutting-edge research literature. Journal of Computer and Education Research, 12(24), 600-637. https://doi.org/10.18009/jcer.1477709

Naseri, R., & Abdullah, M. (2024). Understanding AI technology adoption in educational settings: A review of theoretical frameworks and their applications. Information Management and Business Review, 16(3), 174-181. https://doi.org/10.22610/imbr.v16i3(I).3963

Nazaretsky, T., Ariely, M., Cukurova, M., & Alexandron, G. (2022). Teachers’ trust in AI-powered educational technology and a professional development program to improve it. British Journal of Educational Technology, 53, 914-931. https://doi.org/10.1111/bjet.13232

Okonkwo, C., Toromade, A., & Ajayi, O. (2024). STEM education for sustainability: Teaching high school students about renewable energy and green chemistry. International Journal of Applied Research in Social Sciences, 6(10), 2533-2545. https://doi.org/10.51594/ijarss.v6i10.1664

Owoyemi, T. E., & Akinde, A. A. (2026). Assessment of green chemistry competencies and training needs among secondary school chemistry teachers. Journal of Research in Environmental and Science Education, 3(1), 24–45. https://doi.org/10.70232/jrese.v3i1.41

Palencia, P. A. E., Arteaga, K. P. A., & Nisperuza, E. P. F. (2025). Artificial intelligence and inclusive education: A professional development model for chemistry teachers in secondary education. Educational Process International Journal, 17(1), Article e2025380. https://doi.org/10.22521/edupij.2025.17.380

Pellas, N. (2024). The impact of AI-generated instructional videos on problem-based learning in science teacher education. Education Sciences, 15(1), Article 102. https://doi.org/10.3390/educsci15010102

Quang, N., Kien, N., & Van Giang, C. (2025). Artificial intelligence applications to develop problem-solving competency in chemistry education in Vietnam: Current situation and solutions. International Journal of Social Science Exceptional Research, 4(3), 93-102. https://doi.org/10.54660/ijsser.2025.4.3.93-102

Rissi, A., Insantuan, B., Evelyn, M., Widiyastuti, E., Nenohai, M., & Nadeak, B. (2025). Enhancing the effectiveness of technology-based learning with AI training for teachers: A literature review. Formosa Journal of Multidisciplinary Research, 4(4), 1737-1748. https://doi.org/10.55927/fjmr.v4i4.157

Shezad, F., Goswami, R., Shaheen, A., & Khan, I. (2025). AI in teacher training and professional development: A tool for continuous learning and skill enhancement. Review of Education, Administration & Law, 8(1), 179-191. https://doi.org/10.47067/real.v8i1.416

Şimşek, A., Cengiz, G., & Bal, M. (2025). Extending the TAM framework: Exploring learning motivation and agility in educational adoption of generative AI. Education and Information Technologies, 30, 20913-20942. https://doi.org/10.1007/s10639-025-13591-9

Tan, X., Cheng, G., & Ling, M. H. (2024). Artificial intelligence in teaching and teacher professional development: A systematic review. Computers and Education Artificial Intelligence, 8, Article 100355. https://doi.org/10.1016/j.caeai.2024.100355

Thanh, H., Van, H., Viet, H., Tran, Q., Thanh, H., Duy, B., & Duc, M. (2025). Integrating AI and IoT into STEM teacher training: A case study of secondary education in Vietnam. Edelweiss Applied Science and Technology, 9(4), 2439–2458. https://doi.org/10.55214/25768484.v9i4.6583

Tütüniş, B., Ünal, K., & Köksal, Ö. (2025). AI-enhanced professional development: Effects on secondary EFL teachers’ digital competencies and affective dimensions in Turkey. Journal of Posthumanism, 5(3), 859–882. https://doi.org/10.63332/joph.v5i3.805

Vaz, C. R., Morais, C., Pastre, J. C., & Júnior, G. G. (2024). Teaching green chemistry in higher education: Contributions of a problem-based learning proposal for understanding the principles of green chemistry. Sustainability, 17(5), Article 2004. https://doi.org/10.3390/su17052004

Velander, J., Taiye, M., Otero, N., & Milrad, M. (2023). Artificial intelligence in K-12 education: Eliciting and reflecting on Swedish teachers’ understanding of AI and its implications for teaching & learning. Education and Information Technologies, 29, 4085-4105. https://doi.org/10.1007/s10639-023-11990-4

Vogelzang, J., Admiraal, W., & Van Driel, J. (2020). Effects of Scrum methodology on students’ critical scientific literacy: the case of green chemistry. Chemistry Education Research and Practice, 21(3), 940-952. https://doi.org/10.1039/d0rp00066c

Yau, K., Chai, C., Chiu, T., Meng, H., King, I., & Yam, Y. (2022). A phenomenographic approach to teacher conceptions of teaching Artificial Intelligence (AI) in K-12 schools. Education and Information Technologies, 28, 1041-1064. https://doi.org/10.1007/s10639-022-11161-x

Yıldırım, B., & Akcan, A. (2024). AI-professional development model for chemistry teacher: Artificial intelligence in chemistry education. Journal of Education in Science, Environment and Health, 10(4), 161-182. https://doi.org/10.55549/jeseh.741

Zhang, J., & Zhang, Z. (2024). AI in teacher education: Unlocking new dimensions in teaching support, inclusive learning, and digital literacy. Journal of Computer Assisted Learning, 40(4), 1871-1885. https://doi.org/10.1111/jcal.12988

Downloads

Published

2026-07-01

How to Cite

Akinde, A. A., & Owoyemi, T. E. (2026). Impact of AI-Enhanced Training on Green Chemistry Understanding of Secondary School Chemistry Teachers. Journal of Research in Environmental and Science Education, 3(2), 181–194. https://doi.org/10.70232/jrese.v3i2.65

Similar Articles

11-20 of 34

You may also start an advanced similarity search for this article.