Integrating Artificial Intelligence and Green Chemistry into Innovative Chemistry Education
DOI:
https://doi.org/10.15575/jtk.v11i2.52514Keywords:
artificial intelligence, chemical pedagogy, green chemistry, innovationAbstract
This study aims to identify the challenges and potential applications of Artificial Intelligence (AI) and Green Chemistry in chemistry education and laboratory practices as innovative approaches to chemistry teaching. The research method uses a Systematic Literature Review (SLR) conducted by referring to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Fifteen peer-reviewed articles published in the last four years and indexed in Scopus were selected from several databases, including the Education Resources Information Center (ERIC) and the Multidisciplinary Digital Publishing Institute (MDPI). The review results show that an effective integration strategy needs to position AI as a pedagogical tool for cognitive scaffolding, an object of scientific evaluation, and a medium for academic reflection, while Green Chemistry needs to be positioned as a framework for assessing the efficiency, safety, and environmental impact of chemical processes. This integration requires strengthening lecturer capacity, utilizing AI as a cognitive laboratory, implementing hybrid assessments, and integrating AI ethics into the curriculum. Thus, the integration of AI and Green Chemistry not only contributes to learning innovation but also has the potential to transform Indonesian chemistry education to be more critical, reflective, ethical, and sustainable. It is suggested that these findings serve as a pedagogical framework for educators and policymakers in navigating the digital era.
References
Akaygun, S., & Kilic, I. (2025). Generative Artificial Intelligence (GenAI) as the Artist of Chemistry Visuals: Chemistry Preservice Teachers’ Reflections on Visuals Created by GenAI. Journal of Chemical Education, 102(7), 2549–2564. https://doi.org/10.1021/acs.jchemed.4c00775
Berber, S., Brückner, M., Maurer, N., & Huwer, J. (2025). Artificial Intelligence in Chemistry Research─Implications for Teaching and Learning. Journal of Chemical Education, 102(4), 1445–1456. https://doi.org/10.1021/acs.jchemed.4c01033
Cannon, A. S., Anderson, K. R., Enright, M. C., Kleinsasser, D. G., Klotz, A. R., O’Neil, N. J., & Tucker, L. J. (2023). Green Chemistry Teacher Professional Development in New York State High Schools: A Model for Advancing Green Chemistry. Journal of Chemical Education, 100(6), 2224–2232. https://doi.org/10.1021/acs.jchemed.2c01173
Etzkorn, F. A., & Ferguson, J. L. (2023). Integrating Green Chemistry into Chemistry Education. Angewandte Chemie - International Edition, 62(2). https://doi.org/10.1002/anie.202209768
Feldman-Maggor, Y., Blonder, R., & Alexandron, G. (2025). Perspectives of Generative AI in Chemistry Education Within the TPACK Framework. Journal of Science Education and Technology, 34(1), 1–12. https://doi.org/10.1007/s10956-024-10147-3
Hussain, C. M., Hussain, G., & Keçili, R. (2025). Smart analytical chemistry: Integrating green, sustainable, white and AI-driven approaches in modern analysis. In TrAC - Trends in Analytical Chemistry (Vol. 191). Elsevier B.V. https://doi.org/10.1016/j.trac.2025.118295
Huwer, J., Maurer, N., Mundt, P., & Belova, N. (2025). AI in chemistry and chemical education. International Journal of Physics and Chemistry Education, 17(1), 1–4. https://doi.org/10.51724/ijpce.v17i1.403
Iyamuremye, A., Niyonzima, F. N., Mukiza, J., Twagilimana, I., Nyirahabimana, P., Nsengimana, T., Habiyaremye, J. D., Habimana, O., & Nsabayezu, E. (2024). Utilization of artificial intelligence and machine learning in chemistry education: a critical review. In Discover Education (Vol. 3, Number 1). Discover. https://doi.org/10.1007/s44217-024-00197-5
Kim, J. (2025). Integrating Artificial Intelligence (AI) Chatbots and Green Chemistry Principles in the Synthesis of Cyclohexene. Journal of Chemical Education, 102(7), 3058–3064. https://doi.org/10.1021/acs.jchemed.5c00212
Lestari, N. A., Sulistyowati, D., Dellatiani, Y., Irawan, N. Z. P., Fadhilah, A., & Muyassaroh, A. (2024). Implementation of green chemistry approaches in chemistry labs instruction: A systematic literature review. Jurnal Pendidikan Kimia, 16(3), 263–277. https://doi.org/10.24114/jpkim.v16i3.63398
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Journal of Clinical Epidemiology, 62(10), 1006–1012. https://doi.org/10.1016/j.jclinepi.2009.06.005
O’Neil, N. J., Scott, S., Relph, R., & Ponnusamy, E. (2021). Approaches to Incorporating Green Chemistry and Safety into Laboratory Culture. Journal of Chemical Education, 98(1), 84–91. https://doi.org/10.1021/acs.jchemed.0c00134
Pont-Niclòs, I., Echegoyen-Sanz, Y., Orozco-Gómez, P., & Martín-Expeleta, A. (2024). Creativity and artificial intelligence: A study with prospective teachers. Digital Education Review, (45), 91–97. https://doi.org/10.1344/der.2024.45.91-97
Ruff, E. F., Franz, J. L., & West, J. K. (2024). Using ChatGPT for Method Development and Green Chemistry Education in Upper-Level Laboratory Courses. Journal of Chemical Education, 101(8), 3224–3232. https://doi.org/10.1021/acs.jchemed.4c00193
Ruff, E. F., & Zemke, J. M. O. (2025). Discussing the Ethics of Professional AI Use in Undergraduate Chemistry Courses. Journal of Chemical Education, 102(4), 1457–1464. https://doi.org/10.1021/acs.jchemed.4c01038
Schuessler, K., Striewe, M., Pueschner, D., Luetzen, A., Goedicke, M., Giese, M., & Walpuski, M. (2024). Developing and evaluating an e-learning and e-assessment tool for organic chemistry in higher education. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1355078
Singh, G., Rajasekhar, E. S. K., Mounika, K., Tulasi, K. R. S. K., Dondapati, T., Himasaila, M., & Pulipati, S. (2024). Artificial Intelligence in Green Organic Chemistry: Pathway to Sustainable and Eco-Friendly Chemistry. In Asian Journal of Chemistry (Vol. 36, Number 12, pp. 2731–2743). Asian Publication Corporation. https://doi.org/10.14233/ajchem.2024.32719
Tassoti, S. (2024). Assessment of Students Use of Generative Artificial Intelligence: Prompting Strategies and Prompt Engineering in Chemistry Education. Journal of Chemical Education, 101(6), 2475–2482. https://doi.org/10.1021/acs.jchemed.4c00212
Widyantoro, C., Han, J. Y., Ong, J. S. H., Goh, K. H., & Fung, F. M. (2025). Teaching Sustainability through Green Chemistry: An Experiential Learning Approach. Journal of Chemical Education, 102(7), 2743–2754. https://doi.org/10.1021/acs.jchemed.4c01476
Xiao, Y., & Watson, M. (2019). Guidance on Conducting a Systematic Literature Review. In Journal of Planning Education and Research (Vol. 39, Number 1, pp. 93–112). SAGE Publications Inc. https://doi.org/10.1177/0739456X17723971
Yamtinah, S., Wiyarsi, A., Widarti, H. R., Shidiq, A. S., & Ramadhani, D. G. (2025). Fine-tuning AI models for enhanced consistency and precision in chemistry educational assessments. Computers and Education: Artificial Intelligence, 8. https://doi.org/10.1016/j.caeai.2025.10039
Downloads
Published
How to Cite
Issue
Section
Citation Check
License
Copyright (c) 2026 Salis Maulida Arismika, Wawan Wahyu
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
