ARTIFICIAL INTELLIGENCE IN CHEMISTRY EDUCATION: OPPORTUNITIES, ETHICAL CHALLENGES, AND THE DEVELOPMENT OF CRITICAL THINKING IN SECONDARY AND VOCATIONAL SETTINGS
Keywords:
Keywords: artificial intelligence, chemistry education, critical thinking, virtual laboratories, generative AI, large language models, ethics in education, secondary education, vocational education, AI literacyAbstract
The rapid integration of artificial intelligence (AI) tools is transforming chemistry education at secondary and vocational levels. This review synthesizes recent empirical studies and systematic reviews (primarily 2023–2025) on AI applications in chemistry teaching, including large language model (LLM) chatbots, adaptive learning platforms, and virtual laboratory simulations. Using the UNESCO Recommendation on the Ethics of Artificial Intelligence (2021) as the primary normative framework, the article examines the demonstrated benefits of AI—personalized feedback, enhanced molecular visualization, improved student self-efficacy, and scalable differentiated instruction—alongside persistent limitations, including computational errors in stoichiometric and redox calculations (with reported mechanistic accuracy as low as 28% for early models), hallucinated citations, and algorithmic bias. Six concrete ethical dilemmas specific to chemistry education are analyzed through detailed scenarios: data privacy and learner profiling, academic integrity in AI-assisted laboratory reports, algorithmic bias in automated assessment, the virtual–real competency gap in vocational training, the opacity of AI-driven assessment decisions, and digital inequality. The article argues that AI’s pedagogical effectiveness is inseparable from its capacity to foster critical thinking in both students and educators. A practical four-pillar framework for responsible implementation is proposed, with implications for curriculum design, teacher professional development, and institutional policy. Directions for future empirical research in secondary and vocational contexts, particularly in resource-constrained settings, are identified.
References
(1) IUPAC. Top 10 Emerging Technologies in Chemistry 2023. Chem. Int. 2023, 45 (3), 14–21. DOI: 10.1515/ci-2023-0303.
(2) Jumper, J.; Evans, R.; Pritzel, A.; et al. Highly Accurate Protein Structure Prediction with AlphaFold. Nature 2021, 596 (7873), 583–589. DOI: 10.1038/s41586-021-03819-2.
(3) Erümit, A. K.; Sarıalioğlu, R. Ö. Artificial Intelligence in Science and Chemistry Education: A Systematic Review. Discover Education 2025, 4 (1), 178. DOI: 10.1007/s44217-025-00622-3.
(4) Iyamuremye, A.; Niyonzima, F. N.; Mukiza, J.; Twagilimana, I.; Nyirahabimana, P.; Nsengimana, T.; Habiyaremye, J. D.; Habimana, O.; Nsabayezu, E. Utilization of Artificial Intelligence and Machine Learning in Chemistry Education: A Critical Review. Discover Education 2024, 3 (1), 95. DOI: 10.1007/s44217-024-00197-5.
(5) Johnstone, A. H. Why Is Science Difficult to Learn? Things Are Seldom What They Seem. J. Comput. Assisted Learn. 1991, 7 (2), 75–83. DOI: 10.1111/j.1365-2729.1991.tb00230.x.
(6) Yik, B. J.; Dood, A. J. ChatGPT Convincingly Explains Organic Chemistry Reaction Mechanisms Slightly Inaccurately with High Levels of Explanation Sophistication. J. Chem. Educ. 2024, 101 (5), 1836–1846. DOI: 10.1021/acs.jchemed.4c00235.
(7) UNESCO. Recommendation on the Ethics of Artificial Intelligence; UNESCO: Paris, 2022. Adopted on 23 November 2021.
(8) Faulconer, E.; Poore, J.; Fernandez, C.; Griffith, J. C. Virtual Chemical Laboratories: A Systematic Literature Review of Research, Technologies and Instructional Design. Comput. Educ. Open 2022, 2, 100053. DOI: 10.1016/j.caeo.2021.100053.
(9) Teferi, M. Y.; Negash, M. Y.; Diribsa, A. B. The Effect of Virtual Laboratories on the Academic Achievement of Undergraduate Chemistry Students: Quasi-Experimental Study. JMIR Form. Res. 2024, 8, e64476. DOI: 10.2196/64476.
(10) Lizano-Sánchez, F.; Arias-Navarro, A. M.; Orduña, P.; Dziabenko, O.; de La Cruz-García, J. S. Students’ Interactions with an Artificial Intelligence Assistant in a Remote Chemistry Laboratory. Front. Educ. 2025, 10, 1712743. DOI: 10.3389/feduc.2025.1712743.
(11) Tyson, J. Shortcomings of ChatGPT. J. Chem. Educ. 2023, 100 (8), 3098–3101. DOI: 10.1021/acs.jchemed.3c00361.
(12) Leon, A. J.; Vidhani, D. ChatGPT Needs a Chemistry Tutor Too. J. Chem. Educ. 2023, 100 (10), 3859–3865. DOI: 10.1021/acs.jchemed.3c00288.
(13) Clark, T. M.; Anderson, E.; Dickson-Karn, N. M.; Soltanirad, C.; Tafini, N. Comparing the Performance of College Chemistry Students with ChatGPT for Calculations Involving Acids and Bases. J. Chem. Educ. 2023, 100 (10), 3934–3944. DOI: 10.1021/acs.jchemed.3c00500.
(14) Ruff, E. F.; Franz, J. L.; West, J. K. Using ChatGPT for Method Development and Green Chemistry Education in Upper-Level Laboratory Courses. J. Chem. Educ. 2024, 101 (8), 3224–3232. DOI: 10.1021/acs.jchemed.4c00193.
(15) Exintaris, B.; Karunaratne, N.; Yuriev, E. Metacognition and Critical Thinking: Using ChatGPT-Generated Responses as Prompts for Critique in a Problem-Solving Workshop (SMARTCHEMPer). J. Chem. Educ. 2023, 100 (8), 2972–2980. DOI: 10.1021/acs.jchemed.3c00481.
(16) Guo, Y.; Lee, D. Leveraging ChatGPT for Enhancing Critical Thinking Skills. J. Chem. Educ. 2023, 100 (12), 4876–4883. DOI: 10.1021/acs.jchemed.3c00505.
(17) [Authors]. Using Exam Preparation and Reflection to Introduce Artificial Intelligence Tools in Honors General Chemistry. J. Chem. Educ. 2025, 102 (10), 4470–4478. DOI: 10.1021/acs.jchemed.5c00618.
(18) Alli, A. A. A Review of the Potential of Artificial Intelligence (AI) in Enhancing Chemistry Education. Int. J. Recent Innovations Acad. Res. 2025, 9, 31–43.
(19) Heller, S. Assessment of Students Use of Generative Artificial Intelligence: Prompting Strategies and Prompt Engineering in Chemistry Education. J. Chem. Educ. 2024, 101 (6), 2475–2482. DOI: 10.1021/acs.jchemed.4c00212.
(20) West, J. K.; Franz, J. L.; Hein, S. M.; Leverentz-Culp, H. R.; Mauser, J. F.; Ruff, E. F.; Zemke, J. M. An Analysis of AI-Generated Laboratory Reports across the Chemistry Curriculum and Student Perceptions of ChatGPT. J. Chem. Educ. 2023, 100 (11), 4351–4359. DOI: 10.1021/acs.jchemed.3c00581.
(21) Emenike, M. E.; Emenike, B. U. Was This Title Generated by ChatGPT? Considerations for Artificial Intelligence Text-Generation Software Programs for Chemists and Chemistry Educators. J. Chem. Educ. 2023, 100 (4), 1413–1418. DOI: 10.1021/acs.jchemed.3c00063.
(22) Cooper, M. M. A Preliminary Set of Principles to Support Learning in the Context of Generative AI. J. Chem. Educ. 2026, 103 (1), 36–42. DOI: 10.1021/acs.jchemed.5c01413.
(23) Estrada, L.; et al. Artificial Intelligence and Inclusive Education. Educ. Process: Int. J. 2025, 17 (380). DOI: 10.22521/edupij.2025.17.380.
(24) Blonder, R.; Feldman-Maggor, Y. AI for Chemistry Teaching: Responsible AI and Ethical Considerations. Chem. Teach. Int. 2024, 6, 385. DOI: 10.1515/cti-2024-0014.
(25) [Authors]. Chemistry Faculty Perspectives on Artificial Intelligence and Pedagogical Change in Higher Education. Discover Education 2026. DOI: 10.1007/s44217-026-01250-1.
(26) Alasadi, E. A.; Baiz, C. R. Generative AI in Education and Research: Opportunities, Concerns, and Solutions. J. Chem. Educ. 2023, 100 (8), 2965–2971. DOI: 10.1021/acs.jchemed.3c00323.
(27) Huwer, J.; et al. AI in Chemistry and Chemical Education. Int. J. Phys. Chem. Educ. 2025, 17 (1), 1–4. DOI: 10.51724/ijpce.v17i1.403.
(28) Kasneci, E.; Sessler, K.; Küchemann, S.; et al. ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education. Learn. Individ. Differ. 2023, 103, 102274. DOI: 10.1016/j.lindif.2023.102274.
(29) Farrokhnia, M.; Banihashem, S. K.; Noroozi, O.; Wals, A. A SWOT Analysis of ChatGPT: Implications for Educational Practice and Research. Innov. Educ. Teach. Int. 2024, 61, 460–474. DOI: 10.1080/14703297.2023.2195846.
(30) Mendez, J. D. Student Perceptions of Artificial Intelligence Utility in the Introductory Chemistry Classroom. J. Chem. Educ. 2024, 101 (8), 3547–3549. DOI: 10.1021/acs.jchemed.4c00075.
(31) Munawwarah, M.; Alqadri, Z.; Zubair, S. Exploring Students’ Perspectives on the Integration of AI in Chemistry Learning Processes: Opportunities and Challenges. Asian J. Sci. Educ. 2025, 7 (1), 76–83. DOI: 10.24815/ajse.v7i1.43492.
(32) Watts, F. M.; Dood, A. J.; Shultz, G. V.; Rodriguez, J.-M. G. Comparing Student and Generative Artificial Intelligence Chatbot Responses to Organic Chemistry Writing-to-Learn Assignments. J. Chem. Educ. 2023, 100 (10), 3806–3817. DOI: 10.1021/acs.jchemed.3c00664.
(33) Zhai, C.; Wibowo, S.; Li, L. D. The Effects of Over-Reliance on AI Dialogue Systems on Students’ Cognitive Abilities: A Systematic Review. Smart Learn. Environ. 2024, 11 (1), 28–64. DOI: 10.1186/s40561-024-00316-7.
