Assessment of Teachers’ Perception of Artificial Intelligence Technology on Academic Achievement in Physics among Secondary Schools in Plateau State, Nigeria

Authors

  • FWANGLE, Ishaya Istifanus Author
  • MANKILIK, Mangut Author
  • USMAN, Isa Shehu Author

DOI:

https://doi.org/10.64348/zije.202566

Keywords:

Physics teachers AI perception, Plateau State, Academic achievement.

Abstract

This study investigated the teachers’ perception of artificial intelligence technology on academic achievement in physics among secondary schools in Plateau State, Nigeria. Guided by two objectives and two hypotheses respectively, grounded in Bento’s AI Literacy Framework of 2020, the study explored teachers’ perceptions of AI and examined whether gender differences influenced their effectiveness in utilizing AI to enhance learning outcomes. Using an ex post facto research design, a sample of 36 Physics teachers and 393 SS3 students were selected across 36 secondary schools during the 2024/2025 academic session in Plateau State. Data were collected using the Physics Teachers’ AI Literacy Assessment Questionnaire (PTAILAQ) and a Physics Students’ Academic Achievement Proforma (PSAAP). Descriptive statistics of mean and standard deviation was used to answer the research questions and inferential analyses of ANOVA & ANCOVA were used to test the two hypotheses at a 0.05 level of significance. Results revealed that teachers exhibited a high level of perception of AI as a useful tool for improving students learning. However, no significant effect was found between teachers’ AI perception and students’ academic achievement. The study concludes that while teacher’s perception of AI is high, it does not directly translate to improved academic outcomes. Recommendations included targeted AI training, infrastructural support, and policy reforms to bridge the gap between perception and classroom practice.

References

Bento, M. (2020). Artificial intelligence literacy: A framework for educators. Journal of Educational Computing Research, 58(4), 419-435.

Chen L, Chen P, & Lin Z (2020) Artificial intelligence in education: a review. Ieee Access 8:75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510 DOI: https://doi.org/10.1109/ACCESS.2020.2988510

Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., Suman, R. (2022) Artificial intelligence (AI) applications for marketing: a literature-based study. Int J Intell Netw 3:119–132. https://doi.org/10.1016/j.ijin.2022.08.005 DOI: https://doi.org/10.1016/j.ijin.2022.08.005

Kim, J., & Lee, Y. (2020). Artificial intelligence in education: A review of the literature. Journal of Educational Computing Research, 62(4), 419-437.

Kong, S.C, Cheung, W.M.Y, & Tsang O (2023a). Evaluating an artificial intelligence literacy programme for empowering and developing concepts, literacy and ethical awareness in senior secondary students. Educ Inf Technol 28:4703–4724. https://doi.org/10.1007/s10639-022-11408-7 DOI: https://doi.org/10.1007/s10639-022-11408-7

Lee, I., Ali, S., Zhang, H., DiPaola, D., & Breazeal, C. (2021). Developing middle school students’ AI literacy. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education: 191–197. https://doi.org/10.1145/3408877.3432513 DOI: https://doi.org/10.1145/3408877.3432513

Long, D., & Magerko B (2020). What is AI literacy? Competencies and design considerations. In: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems: 1–16. https://doi.org/10.1145/3313831.3376727 DOI: https://doi.org/10.1145/3313831.3376727

Mahligawati, F., Allanas, E., Butarbutar, M. H., & Nordin, N. A. N (2023). Artificial intelligence in Physics Education: A Comprehensive literature review Journal of Physics.: Conference. Series. 2596 012080. doi:10.1088/1742-6596/2596/1/012080 DOI: https://doi.org/10.1088/1742-6596/2596/1/012080

Mankilik, M., & Umaru, M. G. (2015). Effects of hybrid active learning strategy on secondary school students’ Understanding of Direct Current Electricity Concepts in Physics. International Journal of Learning Teaching and Educational Research, 13(2), 77-87.

Mertala P, Fagerlund J, Calderon O (2022). Finnish 5th and 6th grade students’ pre instructional conceptions of artificial intelligence (AI) and their implications for AI literacy education. Comput Educ Artif Intell 3:100095. https://doi.org/10.1016/j.caeai.2022.100095 DOI: https://doi.org/10.1016/j.caeai.2022.100095

Ng DTK, Lee M, Tan RJY, Hu X, Downie JS, Chu SKW (2023a). A review of AI teaching and learning from 2000 to 2020. Educ Inf Technol 28(7), 8445–8501. https://doi.org/10.1007/s10639-022-11491-w DOI: https://doi.org/10.1007/s10639-022-11491-w

Ng D.T.K, Leung J.K.L, Chu K.W.S. &Qiao M. S. (2021a). AI literacy: definition, teaching, evaluation and ethical issues. Proc Assoc Inf Sci Tech 58(1), 504–509. https://doi.org/10.1002/pra2.487 DOI: https://doi.org/10.1002/pra2.487

Sahu A, Mishra J, Kushwaha N (2022). Artificial intelligence (AI) in drugs and pharmaceuticals. Comb Chem High Throughput Screen 25(11), 1818–1837. https://doi.org/10.2174/1386207325666211207153943 DOI: https://doi.org/10.2174/1386207325666211207153943

Spector, J. M. (2016). Foundations of educational technology: Integrative approaches and interdisciplinary perspectives. Routledge.

Su J, Ng DTK. & Chu SKW (2023). Artificial intelligence (AI) literacy in early childhood education: The challenges and opportunities. Comput Educ Artif Intell 4:100124. https://doi.org/10.1016/j.caeai.2023.100124 DOI: https://doi.org/10.1016/j.caeai.2023.100124

Su J, Yang W (2022). Artificial intelligence in early childhood education: a scoping review. Comput Educ Artif Intell 3:100049. https://doi.org/10.1016/j.caeai.2022.100049 DOI: https://doi.org/10.1016/j.caeai.2022.100049

Van Esch P, Black JS (2021). Artificial intelligence (AI): revolutionizing digital marketing. Australas Mark J 29(3), 199–203. https://doi.org/10.1177/18393349211037684 DOI: https://doi.org/10.1177/18393349211037684

Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4), Article 100179 DOI: https://doi.org/10.1016/j.xinn.2021.100179

Zhai, X., Chu, X. Chai, C.S., Jong, M.S.Y., Istenic. A., Spector, M., Liu, J.B., Yuan, J., & Li, Y. (2021). A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity 2021:8812542. https://doi.org/10.1155/2021/8812542

Zhao, L., Wu, X, Luo, H. (2022). Developing AI literacy for primary and middle school teachers in China: based on a structural equation modeling analysis. Sustainability 14(21):14549. https://doi.org/10.3390/su142114549 DOI: https://doi.org/10.3390/su142114549

Downloads

Published

2025-08-07

How to Cite

Assessment of Teachers’ Perception of Artificial Intelligence Technology on Academic Achievement in Physics among Secondary Schools in Plateau State, Nigeria. (2025). Federal University Gusau Faculty of Education Journal, 5(3), 266-272. https://doi.org/10.64348/zije.202566