AIED For Self-Learning in Nigeria: Implications for Curriculum and Instruction

Adamu Ibrahim Maishafi PhD

doi:10.56201/ijee.v12.no.3.2026

📄 Download Paper

AIED For Self-Learning in Nigeria: Implications for Curriculum and Instruction

Adamu Ibrahim Maishafi PhD

Abstract

The advent of Artificial Intelligence in Education has opened new pathways for self- directed learning, particularly in contexts where access to qualified and competent teachers remains uneven. This paper examines the implications of AIED-supported self-learning for curriculum design and instructional practice, making Nigeria as a case of study. Drawing on a structured review of AIED literature, self-directed learning theory, and empirical studies from Nigerian educational contexts, the paper identifies three core tensions: the promise of personalized adaptive systems versus infrastructural deficits; the demand for learner autonomy versus the preference for teacher-directed instruction; and the urgency of AI literacy versus the need for ethical governance frameworks. The analysis suggests that Nigeria's curriculum must shift from content-coverage models toward competency-based, AI- augmented frameworks, while instruction must move toward blended facilitation that positions the teacher as a learning architect rather than a sole knowledge source. The paper concludes with a research agenda addressing theoretical and empirical gaps in AIED- supported self-learning in Nigeria.

Keywords

AIEDself-directed learningself-regulated learningcurriculuminstructionNigeriaadaptive learning.

References

Abubakar Shehu Sadiq, A'isha Jibril Bello & Salisu Tukur (2024). Ethical Implications of Artificial Intelligence in the Nigerian Education System: A Philosophical Call for Policy Integration and Curriculum Reform Achuthan, K. (2025). Artificial intelligence and learner autonomy: A meta-analysis of self- regulated and self-directed learning. Frontiers in Education, 10, 1738751. https://doi.org/10.3389/feduc.2025.1738751 Akgun, S., and Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431-440. https://doi.org/10.1007/s43681-021-00096-7 Awofiranye, M. (2024). The challenges of using AI in education. Available from Bray, B., & McClaskey, K. (2015). Make learning personal: The what, who, wow, where, and why. Corwin. Buiu, C. (1999). Artificial intelligence in education. ZIFF-Papiere, 111. Dignum, V. (2021). The role and challenges of education for responsible AI. London Review of Education, 19(1), 1-11. https://doi.org/10.14324/LRE.19.1.01 Dignum, V. (2021). The role and challenges of education for responsible AI. London Review of Education, 19(1), 1-11. https://doi.org/10.14324/LRE.19.1.01https://www.afterschoolafrica.com/78994/the- challenges-of-using-ai-in-education/ Jenna, E. (2024). Nigeria's National AI Strategy (2024): Overlooked critical challenges and strategic paths forward. https://www.researchgate.net/publication/395 Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. Association Press. Long, D., and Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16). Nucamp. (2025, September). The complete guide to using AI in the education industry in Nigeria in 2025. https://www.nucamp.co/blog/coding-bootcamp-nigeria-nga- education-the-complete-guide-to-using-ai-in-theeducation-industry-in-nigeria-in-2025 Pane, J. F., Steiner, E. D., Baird, M. D., & Hamilton, L. S. (2014). Continued progress: Promising evidence on personalized learning. RAND Corporation. Peno, K. (2024). Self-directed adult learning: Then and now. New Directions for Adult & Continuing Education, 2024(184), 14–19. Russell, S., and Norvig, P. (1995). A modern, agent-oriented approach to introductory artificial intelligence. Acm Sigart Bulletin, 6(2), 24-26. https://doi.org/10.1145/201977.201989 Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity. UNESCO. (2022). Guidance for generative AI in education and research. UNESCO. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education—Where are the educators? International Journal of Educational Technology in Higher Education, 16, 39.

AIED For Self-Learning in Nigeria: Implications for Curriculum and Instruction

Abstract

Keywords

References

More Articles from INTERNATIONAL JOURNAL OF EDUCATION AND EVALUATION