Research Article

Perceived influence of Artificial Intelligence tools on academic engagement of undergraduate Science Education Students in Rev. Fr. Orshio Moses Adasu University, Makurdi

1 Department of Science and Mathematics Education, Rev. Fr. Moses Orshio Adasu University, Makurdi, Benue State, Nigeria
* Corresponding author: jfatoki@bsum.edu.ng
Published: Aug, 2026
Pages: 332–339
Views: 2
Downloads: 0

Abstract

This study examined the perceived influence of Artificial Intelligence (AI) tools on the academic engagement of undergraduate Science Education students at Rev. Fr. Moses Orshio Adasu University, Makurdi. A descriptive survey research design was adopted for the study. Two research questions and two hypotheses guided the study. A sample of 120 undergraduate Science Education students selected from the target population of 240. Data were collected using a structured questionnaire and analyzed using mean, standard deviation, and Pearson Product-Moment Correlation. Findings showed that students perceived AI tools as having a moderate influence on academic engagement, with a grand mean of 2.89. Which revealed a significant positive relationship between AI tool usage and academic engagement (r = 0.58, p < .001), leading to the rejection of hypothesis one. Students also demonstrated positive perceptions of AI tools and willingness to adopt them for academic purposes, with a grand mean of 3.17. A significant positive relationship was found between students’ perceptions of AI tools and their willingness to adopt them (r = 0.64, p < .001), resulting in the rejection hypothesis two. The study concludes that AI tools can support students’ academic engagement and technology adoption when perceived as useful and easy to use. It recommends responsible AI integration alongside independent learning and critical thinking

References

  1. Anukaenyi, B. A., & Ozomadu, E. A. (2019). Nigeria National Policy on Education: A tool for national development. In Relevance of Higher Education to Human and National Development in Nigeria (pp. 1–16). Enugu: Jomap Press. https://eprints.gouni.edu.ng/2834/
  2. ¬¬¬¬Bybee, R. W. (2019). The Case for STEM Education: Challenges and Opportunities. NSTA Press.
  3. Chikendu, R.E. (2018). Effects of instructional computer animation on secondary school students’ achievement and interest in chemistry in Awka education zone [Unpublished PhD Dissertation]. Nnamdi Azikiwe University, Awka
  4. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
  5. Egbodo, B. A., Terna, G. A., & Oche, E. S. (2021). Machine-assisted learning and virtual science laboratories as predictors of knowledge retention among upper basic science students in Benue State. Benue Journal of Science and Technology Education, 6(1), 66–75.
  6. Federal Ministry of Education. (2019). National policy on science and technology education. Federal Republic of Nigeria. https://education.gov.ng/wp-content/uploads/2020/09/National-Policy-On-Science-and-Technology-Education.pdf?utm_source=chatgpt.com
  7. Itikpo, G., Friday, J., & Delmang, T. K. (2021). The use of model-lead test strategy in enhancing achievement of senior secondary two students in organic chemistry in Benue State, Nigeria. British Journal of Education, 9(4), 81–92.
  8. NERDC. (2020). Revised Basic Science and Technology Curriculum for Nigerian Junior Secondary Schools. Abuja: Nigerian Educational Research and Development Council.
  9. Organization for Economic Co-operation and Development OECD. (2018). The Future of Education and Skills: Education 2030. Organisation for Economic Co-operation and Development.
  10. Ozcan, H. (2020). Difficulties encountered by students in learning abstract science concepts and strategies for improvement. International Journal of Science Education, 42(9), 1445–1462.
  11. Piaget, J. (1970). Science of education and the psychology of the child (D. Coltman, Trans.). Orion Press.
  12. Singh, R., & Kapur, D. (2021). The Role of Artificial Intelligence in Enhancing Science Education. International Journal of Educational Research, 108, 101759. https://doi.org/10.1016/j.ijer.2021.101759
  13. UNESCO. (2018). Education for sustainable development and the SDGs: Learning to act, learning to achieve. United Nations Educational, Scientific and Cultural Organization.
  14. Yang, Y., Zhuang, Y., & Pan, Y. (2021). Multiple knowledge representation for big data artificial intelligence: framework, applications, and case studies. Frontiers of Information Technology & Electronic Engineering, 22(12), 1551–1558. https://doi.org/10.1631/FITEE.2100463
  15. Zheng, L., Niu, J., Zhong, L., Gyasi, J.F. (2023). The effectiveness of artificial intelligence on learning achievement and learning perception: A meta-analysis. Interactive Learning Environment, 31(1), 5650–5664. [https://doi.org/10.1080/10494820.2021.2015693
  16. Zudonu, P. A., Briggs, T. O., & Eke, S. N. (2024). Effects of artificial intelligence-based instruction on achievement and conceptual change in Chemistry and Physics among secondary school students in Rivers State. African Journal of Science Education, 12(2), 88–101.
How to Cite

Fatoki, J. O., Okanche, S., & Onah, B. O. (2026). Perceived influence of Artificial Intelligence tools on academic engagement of undergraduate Science Education Students in Rev. Fr. Orshio Moses Adasu University, Makurdi. Journal of Studies in Science and Mathematics Education, 6(1), 332–339. https://doi.org/10.67203/jossme.2026.lt8u7rui

J. O. Fatoki, S. Okanche, and B. O. Onah, "Perceived influence of Artificial Intelligence tools on academic engagement of undergraduate Science Education Students in Rev. Fr. Orshio Moses Adasu University, Makurdi," Journal of Studies in Science and Mathematics Education, vol. 6, no. 1, pp. 332–339, August 2026. doi: 10.67203/jossme.2026.lt8u7rui

Share this article:
Facebook X / Twitter LinkedIn