Integration Of Artificial Intelligence Into Nigerian Polytechnic Curricula: An Empirical Analysis Of Legal And Ethical Awareness
Aboderin, Lawrence Omotose
Directorate of General Studies, Osun State Polytechnic, Iree, Nigeria.
Keywords: Artificial Intelligence, Ethical Responsibility, Technical Education, Polytechnic, Legal Awareness, Digital Equity
Abstract
The use of Artificial Intelligence (AI) in Nigerian Polytechnic education has tremendous transformative potential and critical equity challenges. The aim of this study was to empirically explore the extent of digital equity in relation to student access to AI tools and explore the impact of legal awareness and institutional ethical responsibilities. The data were collected using the Quantitative, Cross-sectional survey design method with a sample size of 300 students from the population of 3500 students in the three categories of federal, state and private polytechnic of Osun State using stratified random sampling technique. Descriptive statistics and Multiple regression were used for the analyses. The results showed a moderate digital equity level (M=3.12 SD=0.86). Legal rights awareness (β=0.39, p< .001) and ethical responsibility (β=0.48, p< .001) significantly predicted digital equity, with ethical responsibility predicting digital equity more strongly (R²=0.61). Overall, the results point to the challenges faced by technical education institutions in Nigeria when it comes to equitable AI implementation, which go beyond mere technological availability and are rooted in legal understandings and ethical frameworks. We argue that adopting sustainable AI practices needs to be embedded in the policy, including the use of equity indicators, legal protection, and institutional ethical commitments, to avoid the exacerbation of current socio-digital inequalities.
References
Adeniji, S. M., Oladipo, A. J., & Yusuf, M. O. (2023). Artificial intelligence in Nigerian technical education: Opportunities and challenges for curriculum innovation. Journal of Vocational Education and Technology, 24(2), 112-129.
Akomolehin, A. O., & Aluko, R. B. (2025). Digital disparities in AI adoption across Nigerian polytechnics: A comparative analysis. African Journal of Educational Technology, 8(1), 45-62.
Brey, P. A. (2023). Ethical and legal dimensions of AI in education: A framework for policy development. International Journal of Artificial Intelligence in Education, 33(3), 567-589.
Chaudhry, M. A., & Kazim, E. (2022). Ethical AI in education: Addressing bias, fairness, and accountability in learning systems. AI & Society, 38(2), 345-362.
Green, S. B. (1991). How many subjects does it take to do a regression analysis? Multivariate Behavioral Research, 26(3), 499-510.
Luckin, R., Cukurova, M., Kent, C., & du Boulay, B. (2022). Empowering educators to be AI-ready. Computers & Education: Artificial Intelligence, 3, 100076.
Mittelstadt, B. (2023). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence, 5(4), 296-306.
Nwankwo, C. A., Eze, T. I., & Okoro, J. U. (2023). Legal frameworks for digital education in Nigeria: Bridging the policy-implementation gap. Nigerian Journal of Educational Law and Policy, 5(1), 88-104.
Nwosu, J. C., Adeyemo, A. B., & Bello, A. (2022). Digital divide and access to emerging technologies in Nigerian technical colleges. Journal of Science and Technology Education, 31(4), 501-517.
Okebukola, P. A. (2022). Education law and policy reforms in Nigeria's digital era. Journal of African Educational Policy, 14(1), 23-39.
Oni, T., Opara, U., & Ngongpah, D. (2025). Assessing AI readiness in Nigerian Polytechnics: Infrastructure, competency, and institutional support. Journal of Higher Education in Africa, 12(3), 78-95.
Williamson, B. (2023). The social life of AI in education. Learning, Media and Technology, 48(2), 159-174.