Research Article

Effects of Artificial Intelligence Enriched Inquiry-Based Strategy on Performance in Chemistry among Secondary School Students in Zaria Metropolis, Kaduna, Nigeria

1 Jigawa State College of Education
2 Ahmadu Bello University, Zaria
3 Department of Science Education, Ahmadu Bello University, Zaria
4 Institute of Education, Ahmadu Bello University, Zaria, Kaduna State, Nigeria
* Corresponding author: muazuahmad03@gmail.com
Published: Aug, 2026
Pages: 179–190
Views: 24
Downloads: 5

Abstract

This study investigated the effects of ChatGPT enriched inquiry-based strategy (IBS+ChatGPT) on secondary school students’ performance in Chemistry. A quasi-experimental pretest–posttest group design was adapted. A sample of 103 (63 in experimental and 40 in control groups) secondary students were randomly selected from a population of 7,116 students across 17 public schools in Zaria. The experimental group was taught using IBS+ChatGPT while the control was taught using the conventional method. Data were collected using the chemical reaction and equilibrium performance test (CREPT), which was validated and yielded a reliability coefficient of .85.  Two research questions and two hypotheses were formulated to guide the study. The research questions were answered using mean, standard deviation and bar charts. The hypotheses were tested at α=.05 level of significance using analysis of covariance (ANCOVA) with pretest performance scores as a covariate. The result showed no significant difference in students’ performance between the experimental (M= 51.08, SD= 11.716) and control (M= 39.20, SD= 10.493) groups, F(df) = 103, p= .068 That is, there was an improved performance of students taught using the IBS+ChatGPT as compared to those taught using the conventional method after accounting for the initial differences between the two groups. However, there was no sufficient evidence to claim this improved performance is not due to random errors. Further, the result showed no significant difference in the performance of male (M= 53.61, SD= 11.093) and female (M= 46.36, SD= 11. 623) students taught using IBS+ChatGPT, F(df) = 63, p= .385 indicating that the IBS+ChatGPT was gender friendly. It was recommended that future studies should use a longer treatment period to better determine the effectiveness of the strategy

References

  1. Agu, N. N., & Okafor, C. C. (2021). Relationship between students’ grades in WAEC and NECO Chemistry examination in Anambra State. International Journal of Research and Innovation in Social Science, 5(7), 90–94.
  2. Akhtar, N., Yasmeen, M., & Dar, M. U. (2025). Investigates the impact of integrating artificial intelligence (AI) in teaching chemistry at higher secondary school level. Advances and Issues in Social Sciences (AISS), 1(1), 20. https://aiss.pk
  3. Aregbesola, B. G., Ojelade, I. A., & Samuel, S. B. (2025). Impact of artificial intelligence class point on the academic achievement of secondary school students in chemistry. Cognify: Journal of Artificial Intelligence and Cognitive Science, 2(1), 1–11.
  4. Awodun, A. O., Famuwagun, S. T., & Ayomide, A. J. (2024). Improving senior secondary school students’ performance in chemistry through laboratory-based teaching strategy. International Journal of Educational Research, 7(9).45–53. https://ijojournals.com/index.php/er/article/view/933
  5. Bruner, J. S. (1961). The act of discovery. Harvard Educational Review, 31(1), 21–32.
  6. Bybee, R. W., Taylor, J. A., Gardner, A., Van Scotter, P., Powell, J. C., Westbrook, A., & Landes, N. (2006). The BSCS 5E instructional model: Origins and effectiveness. BSCS.
  7. Chikendu, R. E., Obikezie, M.C., & Abumchukwu, A.A. (2021). Challenge of effective teaching of chemistry in the secondary schools in Enugu State. International Journal of Research, 8(10), 106- 117.
  8. Danjuma, J. P., & Mankilik, M. (2022). Effects of inquiry teaching strategy on senior secondary school students’ retention and achievement in chemistry in Jalingo. BW Academic Journal, 1(1), 10. https://www.bwjournal.org/index.php/bsjournal/article/view/623
  9. Dauda, K., & Shoge, M. O. (2024). Perception of students toward learning chemistry in senior secondary school: A case study of Kaduna South. International Journal of Research and Innovation in Social Science, 8(3), 1919–1923.
  10. Ejilibe, O. C., Nnamonu, E. I., Chukwuemeka, P. C., Ifeanyi, J. C., Onyishi, S. O., & Onyeidu, B. U. (2020). Evaluation of gender difference influence: Effects of games on acquisition of science process skills in junior secondary school, South East Nigeria. Journal of Education and Practice, 11(15), 49–56. https://doi.org/10.7176/JEP/11-15-06
  11. Erno, P. L., II, & Berry, E. B. (2025). Impact of an AI-driven teacher dashboard on student performance in inquiry-based science learning. International Journal of Science and Research Archive, 15(2), 135–138. https://doi.org/10.30574/ijsra.2025.15.2.1279
  12. Global Education Monitoring Report Team. (2022). Global education monitoring report 2022: Gender report, Deepening the debate on those still left behind. UNESCO. https://doi.org/10.54676/RCZB6329
  13. Hong, J., Zhang, Y., & Zheng, X. (2022). Generative AI and the future of learning: Exploring potentials and pitfalls. Computers in Human Behavior Reports, 7, 100234. https://doi.org/10.1016/j.chbr.2022.100234
  14. Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
  15. Kotsis, K. T. (2024). Integrating ChatGPT into the inquiry-based science curriculum for primary education. European Journal of Education and Pedagogy, 5(6), 235–240.
  16. Krishna, L. S., Prasad, J. C., & Anjali, S. (2024). The impact of artificial intelligence in reshaping education: An analysis based on learning theories. ITM Web of Conferences, 68, 01008.
  17. Lucci, A., Santoro, F., & Rossi, G. (2022). The expanding frontier of generative AI: Emerging technologies and their societal impact. AI & Society, 37(3), 1039–1055. https://doi.org/10.1007/s00146-021-01237-5
  18. Nneka, O. F., & Otarigho, M. D. (2024). Artificial intelligence and chemistry learning outcomes of senior secondary school students in Warri Metropolis. International Journal of Academic Pedagogical Research (IJAPR), 8(7), 7–14.
  19. Ntibi, J. E., & Neji, H. A. (2021). Effect of inquiry and concept mapping strategies on students’ academic achievement in chemistry in Cross River State, Nigeria. International Journal of Contemporary Social Science Education, 2(1), 45–53.
  20. Odukwe, O. C., & Nwafor, S. C. (2021). Effect of guided-inquiry method on senior secondary school chemistry students’ academic achievement in Anambra State, Nigeria. Unizik Journal of Educational Research and Policy Studies, 11(1). https://sjifactor.com/passport.php?id=21363
  21. Ojelade, I. A., Dajal, R. G., & Badamasi, M. F. (2024). Effect of inquiry teaching strategy on students’ achievement in chemistry in senior secondary schools in Federal Capital Territory, Abuja. Journal of Institutional Research, Big Data Analytics and Innovation, 1(1), 1–31.
  22. Oladejo, A. I. (2022). Concept difficulty in secondary school chemistry: An intra-play of gender, school location, and school type. Journal of Technology and Science Education, 12(2), 190–202. https://doi.org/10.3926/jotse.1902
  23. Oyiza, I. N., Justice, O. I., Oguguo, B. C. E., Hannah, D. C., Chikwado, O. A., Ibrahim, Y., Izuchukwu, O. D., & Ndubumma, C. J. (2025). The role of artificial intelligence in enhancing chemistry education: A pathway to improve students’ performance and academic achievement in Nsukka Education Zone. International Journal of Research and Innovation in Social Science (IJRISS), 9(6), 1-27 https://doi.org/10.47772/IJRISS.2025.906000384
  24. Raman, Y., Surif, J., & Ibrahim, N. H. (2024). The effect of problem-based learning approach in enhancing problem-solving skills in chemistry education: A systematic review. International Journal of Interactive Mobile Technologies (iJIM), 18(5), 126-143 https://doi.org/10.3991/ijim.v18i05.47929
  25. Russell, S. J., & Norvig, P. (2016). Artificial intelligence: A modern approach (3rd ed.). Pearson.
  26. Selvarasu, S. (2023). The excellence of chemical science in achieving a sustainable world. RSC Sustainability, 1(7), 1604- 1607
  27. Sweller, J. (2023). The development of cognitive load theory: Replication crises and incorporation of other theories can lead to theory expansion. Educational Psychology Review, 35(4), 95. https://doi.org/
  28. Sylvanus, T., & Eke, S. (2017). Effect of inquiry teaching strategy on academic achievement of senior secondary school chemistry students in Okrika Local Government Area. International Journal of Education and Evaluation, 3(12). Retrieved from www.iiardpub.org
  29. Taber, K. S. (2024). Educational constructivism. Encyclopedia, 4(4), 1534–1552.
  30. Tang, C., & Cooper, D. (2024). Generative artificial intelligence in education: A new paradigm for learning and assessment. Educational Technology Research and Development, 72(2), 445–462. https://doi.org/10.1007/s11423-024-10234-6
  31. Tijani, B. E. (2025). Impact of open inquiry instructional strategy on secondary school students’ academic achievement and conceptual knowledge in chemistry across genders in Osun State, Nigeria. A Journal of Spread Corporation, 14(1), 120–141. ISSN 1916-7822.
  32. Umahaba, E. R. (2016). Impact of 5E's Learning Model on Questioning Styles Preference and Academic Performance among Secondary School II Chemistry Students, Katisna Metropolis, Nigeria [Unpublished Master’s Dissertation]. Ahmadu Bello University, Zaria, Nigeria http://kubanni.abu.ng/handle/123456789/8514
  33. Yeboah, A., & Siaw, W. N. (2020). The impact of inquiry-based method of teaching on the academic performance of primary education students of Atebubu College of Education in general chemistry. European Journal of Basic and Applied Sciences, 7(1), 1–12.
  34. Zakariya, Y. F. (2025, January 21–28). Teaching Generation Z students for productive learning: Introducing inquiry-driven collaborative learning model. In Proceedings of the 9th International Conference on Global Practice of Multidisciplinary Scientific Studies, Havana, Cuba.
  35. Zhang, L., & Li, H. (2024). Integrating artificial intelligence into inquiry-based learning: Implications for student-centered education. Computers & Education, 205, 104962. https://doi.org/10.1016/j.compedu.2024.104962
  36. Zudonu, C., Eze, U., & Nwosu, P. (2024). Artificial intelligence in Chemistry education: Impacts on achievement and conceptual change. International Journal of STEM Education, 11(1), 88–101. https://doi.org/10.1186/s40594-024-00488-2
How to Cite

Ahmad, M. A., Umahaba, R. E., Zakariya, Y. F., & Saidu, M. U. (2026). Effects of Artificial Intelligence Enriched Inquiry-Based Strategy on Performance in Chemistry among Secondary School Students in Zaria Metropolis, Kaduna, Nigeria. Journal of Studies in Science and Mathematics Education, 6(1), 179–190. https://doi.org/10.67203/jossme.2026.blvwzwrn

M. A. Ahmad, R. E. Umahaba, Y. F. Zakariya, and M. U. Saidu, "Effects of Artificial Intelligence Enriched Inquiry-Based Strategy on Performance in Chemistry among Secondary School Students in Zaria Metropolis, Kaduna, Nigeria," Journal of Studies in Science and Mathematics Education, vol. 6, no. 1, pp. 179–190, August 2026. doi: 10.67203/jossme.2026.blvwzwrn

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