Artificial Intelligence Adoption in Nigerian Secondary Education: Opportunities Constraints, and Implications for Teaching and Educational Management in Ondo State

Authors

  • Olurotimi David ADULOJU Science Education Department, Adekunle Ajasin University, Akungba -Akoko, Ondo State, Nigeria. Author
  • Lydia Oluwafunmilayo ADEDOTUN Science Education Department, Ekiti State University, Ado-Ekiti, Ekiti State, Nigeria. Author
  • Gbemisola Janet KUMUYI Science Education Department, Adekunle Ajasin University, Akungba -Akoko, Ondo State, Nigeria Author
  • Adewale Gabriel ADEKOLU Science Education Department, Adekunle Ajasin University, Akungba -Akoko, Ondo State, Nigeria Author
  • Ibironke Esther OLAJIDE Science Education Department, Adekunle Ajasin University, Akungba -Akoko, Ondo State, Nigeria Author
  • Olukayode Solomon ABODERIN Science Education Department, Adekunle Ajasin University, Akungba -Akoko, Ondo State, Nigeria Author
  • Adesoji Olubunmi OMONIYI Science Education Department, Adekunle Ajasin University, Akungba -Akoko, Ondo State, Nigeria Author

DOI:

https://doi.org/10.54536/ijmdt.v1i1.7045

Keywords:

Artificial Intelligence, Nigeria, School Management, Secondary Education, Teachers’ Perceptions

Abstract

Artificial Intelligence (AI) is increasingly transforming educational systems worldwide by enhancing instructional delivery, learning processes, and administrative efficiency. Despite its growing global relevance, the integration of AI in many developing countries, including Nigeria, remains limited due to infrastructural and institutional challenges. This study examined teachers’ and school administrators’ perceptions of the opportunities, challenges, readiness, and ethical concerns associated with the adoption of Artificial Intelligence in secondary school education in Ondo State, Nigeria. The study adopted a descriptive survey research design. The population consisted of teachers and school administrators in public secondary schools in the state. A sample of 360 respondents, comprising 240 teachers and 120 school administrators, was selected using a multi-stage sampling technique. Data were collected using a structured questionnaire titled Artificial Intelligence Integration in Secondary Schools Questionnaire (AIISSQ) with a Cronbach’s alpha reliability coefficient of 0.82. Data were analyzed using mean and standard deviation to answer research questions, while independent samples t-test was used to test hypotheses at the 0.05 level of significance.
The findings revealed that respondents generally perceived AI as having strong potential to enhance teaching effectiveness, personalized learning, assessment practices, and school management. However, major challenges identified included inadequate ICT infrastructure, unreliable electricity supply, limited technical expertise among teachers, poor internet connectivity, and insufficient funding. The results further indicated a moderate level of institutional readiness for AI integration in secondary schools. Hypothesis testing showed no significant difference between teachers’ and administrators’ perceptions of ethical and policy concerns regarding AI integration (t = 0.962, p = 0.337 > 0.05). The study concludes that although AI offers significant opportunities for improving educational quality, its successful implementation in Nigerian secondary schools requires strengthened ICT infrastructure, targeted teacher training, and clear policy frameworks to ensure responsible and sustainable adoption.

Downloads

Download data is not yet available.

Author Biography

  • Lydia Oluwafunmilayo ADEDOTUN, Science Education Department, Ekiti State University, Ado-Ekiti, Ekiti State, Nigeria.

    PhD Student, 

    Department of Science Education, Faculty of Education, Ekiti State University, Ado-Ekiti, Ekiti State, Nigeria 

References

Bali, A. U., Garba, S. A., Ahmadu, A., Takwate, K. T., & Malgwi, M. E. (2024). Artificial intelligence applications in school administration: Implications for secondary education management in Nigeria. International Journal of Educational Management, 38(2), 215–229.

Bryman, A. (2023). Social research methods (6th ed.). Oxford University Press.

Ching, S. M., & Jamaludin, A. (2025). Teachers’ acceptance of artificial intelligence tools in education: An extension of the Technology Acceptance Model. Education and Information Technologies, 30(1), 145–163.

Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications.

David, O. D., Adeyemi, B. A., & Ogunleye, A. J. (2025). Teachers’ perceptions of artificial intelligence for instructional support in Nigerian secondary schools. Journal of Educational Technology Systems, 53(1), 67–84.

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

Federal Ministry of Education. (2023). National digital learning policy for basic and secondary education in Nigeria. Federal Government of Nigeria.

Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2022). How to design and evaluate research in education (10th ed.). McGraw-Hill Education.

Ghimire, S., & Edwards, J. S. (2024). Organizational readiness and digital innovation adoption in education systems. Computers & Education, 196, 104705. https://doi.org/10.1016/j.compedu.2023.104705

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

Holmes, W., Bialik, M., & Fadel, C. (2021). Artificial intelligence in education: Global perspectives. Center for Curriculum Redesign.

Holmes, W., & Tuomi, I. (2022). State of the art and practice of artificial intelligence in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12512

Igbokwe, I. C. (2024). Ethical concerns and teacher preparedness for artificial intelligence adoption in Nigerian schools. African Journal of Teacher Education, 13(1), 1–17.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

Msafiri, A., Mbwette, T., & Komba, S. (2023). Artificial intelligence and digital transformation in African education systems: Opportunities and challenges. International Journal of Educational Development, 98, 102745.

Naseri, A., & Abdullah, M. Y. (2024). Technology–organization–environment factors influencing artificial intelligence adoption in education. Education and Information Technologies, 29(2), 1345–1364.

Nguyen, T. T., Ho, A. D., & Lee, J. (2023). Ethics and governance of artificial intelligence in education. AI & Society, 38(4), 1521–1534. https://doi.org/10.1007/s00146-022-01523-4

Organisation for Economic Co-operation and Development. (2023). Artificial intelligence in education: Challenges and opportunities for sustainable development. OECD Publishing. https://doi.org/10.1787/edc1c9f7-en

Ogunode, N. J., Adah, S., & Musa, A. (2023). ICT readiness and digital capacity of public secondary schools in Nigeria. Journal of Education and Learning, 12(2), 45–56.

Olaiya, A. A., Ajala, O. O., Azeez, S. A., & Taiwo, M. O. (2025). Digital competence and readiness for artificial intelligence integration among secondary school teachers. Journal of Computing in Education, 12(1), 89–107.

Ondo State Ministry of Education. (2024). Statistical report on public secondary schools in Ondo State. Government of Ondo State.

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2

UNESCO. (2021). Artificial intelligence in education: Guidance for policy-makers. UNESCO Publishing.

UNESCO. (2022). AI and education: A guidance for sustainable digital transformation. UNESCO Publishing.

Unwin, T., Naseem, A., Pawluczuk, A., Shareef, M., & Spiesberger, P. (2020). Digital learning, education, and skills in Africa. World Bank Blogs.

World Bank. (2021). Realizing the future of learning: From learning poverty to learning for everyone, everywhere. World Bank Publications.

World Bank. (2022). Realizing the future of learning: From learning poverty to learning for everyone, everywhere. World Bank Publications.

Xue, W., Ghazali, M. A., & Mahat, M. (2025). Acceptance of artificial intelligence technologies among educators: A systematic review based on TAM. Computers & Education: Artificial Intelligence, 6, 100146.

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(39). https://doi.org/10.1186/s41239-019-0171-0

National Information Technology Development Agency. (2023). National artificial intelligence strategy for Nigeria. Federal Government of Nigeria.

National Information Technology Development Agency. (2024). National artificial intelligence strategy (Revised edition). Federal Government of Nigeria.

Downloads

Published

2026-03-24

How to Cite

ADULOJU, O. D. ., ADEDOTUN, L. O. ., KUMUYI, G. J. ., ADEKOLU, A. G. ., OLAJIDE, I. E. ., ABODERIN, O. S. ., & OMONIYI, A. O. . (2026). Artificial Intelligence Adoption in Nigerian Secondary Education: Opportunities Constraints, and Implications for Teaching and Educational Management in Ondo State. International Journal of Multimedia and Digital Technology, 1(1), 1-13. https://doi.org/10.54536/ijmdt.v1i1.7045