Personalised Chemistry Learning with AI: Experience, Analysis and Recommendations
DOI:
https://doi.org/10.47526/3107-3123.411Keywords:
Artificial Intelligence, Chemistry Education, Digital Technologies, Personalized Learning, ChatGPT, Chemistry Teaching, Neural Networks.Abstract
Modern chemical education is confronted with the imperative to adapt to rapidly evolving digital technologies. One of the most promising avenues in this regard is the integration of artificial intelligence (AI) tools into the academic process. This article examines the opportunities and constraints associated with the use of AI in chemistry instruction at the tertiary level. It discusses applications of neural networks and intelligent platforms (including ChatGPT, Copilot, ChemAI, and others) for elucidating complex concepts, solving problems, modelling chemical processes, and constructing personalized learning trajectories. Drawing on a pedagogical experiment conducted with 63 chemistry students at M. Auezov South Kazakhstan Research University (experimental and control groups), the study identifies a statistically significant (p < 0.01) improvement in academic performance by 10.4 points following the use of AI tools (ChatGPT, ChemAI, WolframAlpha). Survey data collected from both students and faculty were analysed to ascertain key trends, barriers, and expectations surrounding AI in education. The findings indicate a high level of interest in digital tools, while simultaneously underscoring concerns regarding the potential erosion of critical thinking, technological dependency, and compromised academic integrity. The article offers recommendations for the effective and ethically grounded integration of AI into chemical education, and delineates directions for future research aimed at enhancing the quality and accessibility of chemistry instruction amid digital transformation.
References
1. Кушеккалиев А.Н., Искалиева А.У., Имангалиева Б.С. Білім және жасанды интеллект // Ясауи университетінің хабаршысы. – 2025. – №3(137). – Б. 299-316. https://doi.org/10.47526/2025-3/2664-0686.252
2. Roll I., Wylie R. Evolution and Revolution in Artificial Intelligence in Education // International Journal of Artificial Intelligence in Education. – 2016. – №26(2). – P. 582–599. https://doi.org/10.1007/s40593-016-0110-3
3. Hashim S., Omar K. Kh., Ab Jalil H, Mohd Sharef N. Trends on technologies and artificial intelligence in education for personalized learning: systematic literature // Journal of Academic Research in Progressive Education and Development. – 2022. – Vol. 12, №1. – P. 884-903. https://doi.org/10.6007/IJARPED/v11-i1/12230
4. Zawacki-Richter O., Marín V.I., Bond M., Gouverneur F. Systematic Review of Research on Artificial Intelligence in Education: Applications and Trends // International Journal of Educational Technology in Higher Education. – 2019. – №16(1). https://doi.org/10.1186/s41239-019-0171-0
5. Государственная программа развития образования и науки Республики Казахстан на 2020–2025 годы. – Астана, 2020. [Электронный ресурс]. URL: https://www.gov.kz/memleket/entities/edu (дата обращения 10.04.2025)
6. Heffernan N.T., Heffernan C.L. The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching // International Journal of Artificial Intelligence in Education. – 2014. – №24(4). – P. 470–497. https://doi.org/10.1007/s40593-014-0024-x
7. Woolf B.P. Building Intelligent Interactive Tutors. – Elsevier & Morgan Kaufmann, 2008.
8. Золотухин В.М., Золотухина Н.А. Философские вопросы химии: проблемы и методологические основания // Вестник Кузбасского государственного технического университета. – 2007. – №2 (60). – С. 115-118.
9. Matovu H., Kencana Ungu D.A., Won M., Tsai Ch.Ch., David F. Mocerino M., Roy Tasker Immersive virtual reality for science learning: Design, implementation and evaluation // Studies in Science Education. – 2023. – Vol. 59, Issue 2. – P. 205-244. https://doi.org/10.1080/03057267.2022.2082680
10. Huang R.H., Liu D.J., Tlili A., Yang J.F., Wang H.H. Handbook on facilitating flexible learning during educational disruption: The Chinese experience in maintaining undisrupted learning in COVID-19 outbreak. – Beijing: Smart Learning Institute of Beijing Normal University, 2020. – Т. 46.
11. Dede C. The Role of Digital Technologies in Deeper Learning. – Harvard university, 2014. [Electronic resource]. URL: https://files.eric.ed.gov/fulltext/ED561254.pdf (date of access 11.04.2025)
12. OECD, Artificial Intelligence in Education and skills: Challenges and Opportunities. – OECD Publishing, 2021. [Electronic resource]. URL: https://www.oecd.org/en/topics/artificial-intelligence-and-education-and-skills.html (date of access 11.04.2025)
13. Tuomi I. The Impact of Artificial Intelligence on Learning, Teaching, and Education. – Luxembourg, 2018. – 46 p. https://doi.org/10.2760/12297
14. Holmes W., Tuomi, I. State of the art and practice in Al in education // European Journal of Education. – 2022. Vol. 57, Issue 4. – P. 542-570. https://doi.org/10.1111/ejed.12533
15. Baker R.S. Stupid Tutoring Systems, Intelligent Humans // International Journal of Artificial Intelligence in Education. – 2016. – №26(2). – P. 600–614. https://doi.org/10.1007/s40593-016-0105-0
16. Edwards B.I., Bielawski K.S., Prada R., Cheok A.D. Haptic Virtual reality and immersive learning for enchanced organic chemistry instruction // Virtual Reality. – 2019. – №23. – P. 363-373. https://doi.org/10.1007/s10055-018-0345-4
17. Buckingham Shum S., Ferguson R. Social Learning Analytics // Educational Technology & Society. – 2012. – №15(3). – P. 3–26 https://doi.org/10.1145/2330601.2330616
18. Berland M., Wilensky U. Comparing Virtual and Physical Robotics Environments for Supporting Complex Systems and Computational Thinking // Journal of Science Education and Technology. – 2015. – №24(5). – P. 628–647. https://doi.org/10.1007/s10956-015-9552-x
19. Greller W., Drachsler H. Translating Learning into Numbers: A Generic Framework for Learning Analytics // Educational Technology & Society. – 2012. – №15(42). – P. 42–57.
20. Ifenthaler D., Yau J.Y.K. Utilising Learning Analytics to Study success in higher education: a systematic review // Educational Technology Researches and Development. – 2020. – Vol. 68. – P. 1961-1990. https://doi.org/10.1007/s11423-020-09788-z
21. Ferguson R. Learning Analytics: Drivers, Developments and Challenges // International Journal of Technology Enhanced Learning. – 2012. – №4(5-6). – P. 304–317. https://doi.org/10.1504/IJTEL.2012.051816
22. Slade S., Prinsloo P. Learning Analytics: Ethical Issues and Dilemmas // American Behavioral Scientist. – 2013. – №57(10). – P. 1510–1529.
23. Molenaar I. Computational Psychometrics for Learning Analytics // British Journal of Educational Psychology. – 2021. – №91(1). – P. 87–101.
24. Chen L., Chen P., Lin Z. Artificial intelligence in education: A review // 9th International Scientific Conference Technics and Informatics in Education. – 2022. – P. 223-228. https://doi.org/10.46793/TIE22.223K
25. Holmes W., Bialik M., Fadel C. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. – Boston: Center for Curriculum Redesign, 2019. [Electronic resource]. URL: https://curriculumredesign.org/wp-content/uploads/AI-in-Education_Promises-and-Implications_CCR.pdf (date of access 11.04.2025)
26. Zawacki-Richter O., Bai J.Y.H., Lee K., Slagter van Tryon P.J., Prinsloo P. New advances in artificial intelligence applications in higher education? // International Journal of educational technology in higher education. – 2024. – №21. https://doi.org/10.1186/s41239-024-00464-3
27. Luckin R., Holmes W., Griffiths M., Forcier L.B. Intelligence Unleashed: An Argument for AI in Education. – London: Pearson, 2016. [Electronic resource]. URL: file:///C:/Users/User/Downloads/PearsonIntelligenceUnleashedFINAL.pdf (date of access 11.04.2025)
28. Siemens G. Learning Analytics: The Emergence of a Discipline // American Behavioral Scientist. – 2013. – Vol. 57, Issue 10. – P. 1380-1400. https://doi.org/10.1177/0002764213498851
29. Baker R.S., Inventado P.S. Educational Data Mining and Learning Analytics // In: Learning Analytics. – 2014. – P. 61-75. https://doi.org/10.1007/978-1-4614-3305-7_4
30. European Commission. DigComp 2.1: The Digital Competence Framework for Citizens. – 2018. https://dx.doi.org/10.2760/38842
31. Van Dijk J. The Digital Divide // Polity Press. – 2021. – Vol. 72, Issue 1. – P. 136-138. https://dx.doi.org/10.1002/asi.24355
32. Mishra P., Koehler M.J. Technological Pedagogical Content Knowledge // Teachers College Record. – 2006. – Vol. 108, Issue 6. – P. 1017-1054. http://dx.doi.org/10.1111/j.1467-9620.2006.00684.x
33. Сotton D.R.E., Cotton P.A., Shipway R.B. Chatting and cheating: Ensuring academic integrity in the era of ChatGPT // Innovations in Education and Teaching International. – 2024. – Vol. 61, Issue 2. – P. 228–239. https://doi.org/10.1080/14703297.2023.2190148
34. Абил А.С., Капина Э.А., Сугралиева А. Роль информационных технологий в цифровой трансформации высшего образования // Ясауи университетінің хабаршысы. – 2023. – №3(129). – С. 345-359. https://doi.org/10.47526/2023-3/2664-0686.26
REFERENCES
1. Kushekkaliev A.N., Iskalieva A.U., Imangalieva B.S. Bіlіm zhane zhasandy intellekt [Education and artificial intelligence] // Iasaui universitetіnіn habarshysy. – 2025. – №3(137). – B. 299-316. https://doi.org/10.47526/2025-3/2664-0686.252 [in Kazakh]
2. Roll I., Wylie R. Evolution and Revolution in Artificial Intelligence in Education // International Journal of Artificial Intelligence in Education. – 2016. – №26(2). – P. 582–599. https://doi.org/10.1007/s40593-016-0110-3
3. Hashim S., Omar K. Kh., Ab Jalil H, Mohd Sharef N. Trends on technologies and artificial intelligence in education for personalized learning: systematic literature // Journal of Academic Research in Progressive Education and Development. – 2022. – Vol. 12, №1. – P. 884-903. https://doi.org/10.6007/IJARPED/v11-i1/12230
4. Zawacki-Richter O., Marín V.I., Bond M., Gouverneur F. Systematic Review of Research on Artificial Intelligence in Education: Applications and Trends // International Journal of Educational Technology in Higher Education. – 2019. – №16(1). https://doi.org/10.1186/s41239-019-0171-0
5. Gosudarstvennaia programma razvitia obrazovania i nauki Respubliki Kazahstan na 2020–2025 gody [The State Program for the development of Education and Science of the Republic of Kazakhstan for 2020-2025]. – Astana, 2020. [Electronic resource]. URL: https://www.gov.kz/memleket/entities/edu (date of access 10.04.2025) [in Russian]
6. Heffernan N.T., Heffernan C.L. The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching // International Journal of Artificial Intelligence in Education. – 2014. – №24(4). – P. 470–497. https://doi.org/10.1007/s40593-014-0024-x
7. Woolf B.P. Building Intelligent Interactive Tutors. – Elsevier & Morgan Kaufmann, 2008.
8. Zolotuhin V.M., Zolotuhina N.A. Filosofskie voprosy himii: problemy i metodologicheskie osnovania [Philosophical issues of chemistry: problems and methodological foundations] // Vestnik Kuzbasskogo gosudarstvennogo tehnicheskogo universiteta. – 2007. – №2 (60). – S. 115-118. [in Russian]
9. Matovu H., Kencana Ungu D.A., Won M., Tsai Ch.Ch., David F. Mocerino M., Roy Tasker Immersive virtual reality for science learning: Design, implementation and evaluation // Studies in Science Education. – 2023. – Vol. 59, Issue 2. – P. 205-244. https://doi.org/10.1080/03057267.2022.2082680
10. Huang R.H., Liu D.J., Tlili A., Yang J.F., Wang H.H. Handbook on facilitating flexible learning during educational disruption: The Chinese experience in maintaining undisrupted learning in COVID-19 outbreak. – Beijing: Smart Learning Institute of Beijing Normal University, 2020. – Т. 46.
11. Dede C. The Role of Digital Technologies in Deeper Learning. – Harvard university, 2014. [Electronic resource]. URL: https://files.eric.ed.gov/fulltext/ED561254.pdf (date of access 11.04.2025)
12. OECD, Artificial Intelligence in Education and skills: Challenges and Opportunities. – OECD Publishing, 2021. [Electronic resource]. URL: https://www.oecd.org/en/topics/artificial-intelligence-and-education-and-skills.html (date of access 11.04.2025)
13. Tuomi I. The Impact of Artificial Intelligence on Learning, Teaching, and Education. – Luxembourg, 2018. – 46 p. https://doi.org/10.2760/12297
14. Holmes W., Tuomi, I. State of the art and practice in Al in education // European Journal of Education. – 2022. Vol. 57, Issue 4. – P. 542-570. https://doi.org/10.1111/ejed.12533
15. Baker R.S. Stupid Tutoring Systems, Intelligent Humans // International Journal of Artificial Intelligence in Education. – 2016. – №26(2). – P. 600–614. https://doi.org/10.1007/s40593-016-0105-0
16. Edwards B.I., Bielawski K.S., Prada R., Cheok A.D. Haptic Virtual reality and immersive learning for enchanced organic chemistry instruction // Virtual Reality. – 2019. – №23. – P. 363-373. https://doi.org/10.1007/s10055-018-0345-4
17. Buckingham Shum S., Ferguson R. Social Learning Analytics // Educational Technology & Society. – 2012. – №15(3). – P. 3–26 https://doi.org/10.1145/2330601.2330616
18. Berland M., Wilensky U. Comparing Virtual and Physical Robotics Environments for Supporting Complex Systems and Computational Thinking // Journal of Science Education and Technology. – 2015. – №24(5). – P. 628–647. https://doi.org/10.1007/s10956-015-9552-x
19. Greller W., Drachsler H. Translating Learning into Numbers: A Generic Framework for Learning Analytics // Educational Technology & Society. – 2012. – №15(42). – P. 42–57.
20. Ifenthaler D., Yau J.Y.K. Utilising Learning Analytics to Study success in higher education: a systematic review // Educational Technology Researches and Development. – 2020. – Vol. 68. – P. 1961-1990. https://doi.org/10.1007/s11423-020-09788-z
21. Ferguson R. Learning Analytics: Drivers, Developments and Challenges // International Journal of Technology Enhanced Learning. – 2012. – №4(5-6). – P. 304–317. https://doi.org/10.1504/IJTEL.2012.051816
22. Slade S., Prinsloo P. Learning Analytics: Ethical Issues and Dilemmas // American Behavioral Scientist. – 2013. – №57(10). – P. 1510–1529.
23. Molenaar I. Computational Psychometrics for Learning Analytics // British Journal of Educational Psychology. – 2021. – №91(1). – P. 87–101.
24. Chen L., Chen P., Lin Z. Artificial intelligence in education: A review // 9th International Scientific Conference Technics and Informatics in Education. – 2022. – P. 223-228. https://doi.org/10.46793/TIE22.223K
25. Holmes W., Bialik M., Fadel C. Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. – Boston: Center for Curriculum Redesign, 2019. [Electronic resource]. URL: https://curriculumredesign.org/wp-content/uploads/AI-in-Education_Promises-and-Implications_CCR.pdf (date of access 11.04.2025)
26. Zawacki-Richter O., Bai J.Y.H., Lee K., Slagter van Tryon P.J., Prinsloo P. New advances in artificial intelligence applications in higher education? // International Journal of educational technology in higher education. – 2024. – №21. https://doi.org/10.1186/s41239-024-00464-3
27. Luckin R., Holmes W., Griffiths M., Forcier L.B. Intelligence Unleashed: An Argument for AI in Education. – London: Pearson, 2016. [Electronic resource]. URL: file:///C:/Users/User/Downloads/PearsonIntelligenceUnleashedFINAL.pdf (date of access 11.04.2025)
28. Siemens G. Learning Analytics: The Emergence of a Discipline // American Behavioral Scientist. – 2013. – Vol. 57, Issue 10. – P. 1380-1400. https://doi.org/10.1177/0002764213498851
29. Baker R.S., Inventado P.S. Educational Data Mining and Learning Analytics // In: Learning Analytics. – 2014. – P. 61-75. https://doi.org/10.1007/978-1-4614-3305-7_4
30. European Commission. DigComp 2.1: The Digital Competence Framework for Citizens. – 2018. https://dx.doi.org/10.2760/38842
31. Van Dijk J. The Digital Divide // Polity Press. – 2021. – Vol. 72, Issue 1. – P. 136-138. https://dx.doi.org/10.1002/asi.24355
32. Mishra P., Koehler M.J. Technological Pedagogical Content Knowledge // Teachers College Record. – 2006. – Vol. 108, Issue 6. – P. 1017-1054. http://dx.doi.org/10.1111/j.1467-9620.2006.00684.x
33. Сotton D.R.E., Cotton P.A., Shipway R.B. Chatting and cheating: Ensuring academic integrity in the era of ChatGPT // Innovations in Education and Teaching International. – 2024. – Vol. 61, Issue 2. – P. 228–239. https://doi.org/10.1080/14703297.2023.2190148
34. Abil A.S., Kapina E.A., Sugralieva A. Rol informacionnyh tehnologi v cifrovoi transformacii vysshego obrazovania [The role of information technology in the digital transformation of higher education] // Iasaui universitetіnіn habarshysy. – 2023. – №3(129). – S. 345-359. https://doi.org/10.47526/2023-3/2664-0686.26 [in Russian]
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Yassawi Journal of Education Studies
This work is licensed under a Creative Commons Attribution 4.0 International License.
