Leveraging Pedagogical Innovation in Nigerian System of Education: An Application of Artificial Intelligence for Personal Learning and Research Writing

Authors

  • Blessing Beke Macauley Ph.D, Department of Curriculum Studies, Faculty of Education, Ignatius Ajuru University of Education, Rumuolumeni, Port Harcourt, Rivers State, Nigeria Author

Keywords:

Pedagogy, Innovation, Pedagogical Innovation, Artificial Intelligence, Personal Learning, Research Writing

Abstract

Pedagogical landscapes are quickly changing worldwide due to the use of digital technology in the delivery of educational instructions. Digital technology has enormous potential for change in our Nigerian educational system which continues to struggle with issues including overcrowding in classrooms, a lack of resources for instruction, and teacher shortage. This paper discourse analyzes how artificial intelligence (AI) could inspire educational innovation with an emphasis on research writing and tailored learning. This contextual literature-based study critically examines the multifaceted implications of Adaptive Learning Algorithms, Intelligent Tutoring System (ITS), Learning Analytics/Predictive Modeling, Natural Language Processing (NLP), Recommendation Systems, Automated Assessment/Personalized Feedback, and Behavioral/Cognitive Modeling tools that can be used to improve students' academic writing skills, customize instruction, and enable self-paced learning. These include improved access to quality instruction, personalized and student-centered learning, enhanced teacher effectiveness, and the bridging of urban-rural educational divides. However, the paper also identifies a number of contextual obstacles that hinder the successful integration of AI in Nigerian schools and universities and thus suggested that government and other parties involved in education should prioritize them, including collaborations, infrastructure investment, established AI laboratories, digital innovation centers, and smart classrooms.

References

[1] UNESCO, Education in a Post-COVID World: Nine Ideas for Public Action. Paris: UNESCO Publishing, 2020.

[2] G. Siemens, “The changing landscape of education: Digital transformation and the future of learning,” Journal of Learning Analytics, vol. 8, no. 4, pp. 1–14, 2021.

[3] W. Holmes, M. Bialik, and C. Fadel, Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston, MA: Center for Curriculum Redesign, 2019.

[4] A. I. Akwitti, “Leveraging emerging technologies to improve access to education,” Mar. 14, 2025. [Online]. Available: www.miva.blog

[5] P. Okebukola, Reinventing the Nigerian Education System for Global Competitiveness. Lagos: Coalition for Education Reform, 2021.

[6] O. Adebayo and T. Adeyanju, “Pedagogical challenges in Nigerian higher education: Implications for quality learning,” Journal of Educational Development, vol. 15, no. 2, pp. 45–58, 2020.

[7] J. Ogunlade and F. Olaleye, “ICT integration and teacher readiness in Nigerian schools,” Nigerian Journal of Educational Management, vol. 20, no. 1, pp. 75–92, 2022.

[8] J. Babalola and A. Ejidike, “AI-driven personalized learning: Opportunities and challenges in African universities,” International Review of Education Technology, vol. 9, no. 3, pp. 110–128, 2022.

[9] O. Akindele, “Artificial intelligence tools and the enhancement of research writing among university students in Nigeria,” African Journal of Educational Technology, vol. 8, no. 1, pp. 55–70, 2023.

[10] O. Verdenhofa, R. Kinderis, and G. Berjozkina, “AI as a creative partner: How artificial intelligence impacts student creativity and innovation: Case study of students from Latvia, Ukraine and Spain,” Baltic Journal of Economic Studies, vol. 10, no. 5, pp. 111–119, 2024.

[11] UNESCO, AI and Education: Guidance for Policy-Makers. Paris: UNESCO Publishing, 2021.

[12] T. Adebayo, Digital Transformation in Nigerian Education: Opportunities and Barriers to E-Learning Adoption. Lagos: University of Lagos Press, 2024.

[13] OECD, Innovating Education and Educating for Innovation. Paris: OECD Publishing, 2018.

[14] M. Cochran-Smith and S. L. Lytle, Inquiry as Stance: Practitioner Research for the Next Generation. New York, NY: Teachers College Press, 2020.

[15] J. Pane, E. Steiner, M. Baird, and L. Hamilton, Continued Progress: Promising Evidence on Personalized Learning. Santa Monica, CA: RAND Corporation, 2015.

[16] L. W. Anderson and D. Krathwohl, A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives. New York, NY: Longman, 2020.

[17] R. S. Baker and P. S. Inventado, “Educational data mining and learning analytics,” in The Cambridge Handbook of the Learning Sciences, 2nd ed., R. K. Sawyer, Ed. Cambridge: Cambridge Univ. Press, 2018.

[18] R. Luckin, W. Holmes, M. Griffiths, and L. B. Forcier, Intelligence Unleashed: An Argument for AI in Education. London: Pearson, 2016.

[19] M. L. Bernacki, M. J. Greene, and N. G. Lobczowski, “A systematic review of research on personalized learning: Personalized by whom, to what, how, and for what purpose(s)?,” Educational Psychology Review, vol. 33, no. 4, pp. 1675–1715, 2021.

[20] E. Brynjolfsson and A. McAfee, Machine, Platform, Crowd: Harnessing Our Digital Future. New York, NY: W.W. Norton, 2017.

[21] L. Floridi and J. Cowls, “A unified framework of five principles for AI in society,” Harvard Data Science Review, vol. 1, no. 1, 2019, doi: 10.1162/99608f92.8cd550d1.

[22] OpenAI, Technical Report on GPT Models and Multimodal Generative AI. OpenAI Publications, 2023.

[23] O. Zawacki-Richter, V. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence in higher education,” International Journal of Educational Technology in Higher Education, vol. 16, no. 1, pp. 1–27, 2019.

[24] K. VanLehn, “The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems,” Educational Psychologist, vol. 46, no. 4, pp. 197–221, 2011.

[25] H. Drachsler, K. Verbert, O. Santos, and N. Manouselis, “Panorama of recommender systems to support learning,” in Recommender Systems Handbook, F. Ricci et al., Eds. New York, NY: Springer, 2015.

[26] J. Lu and M. Cutumisu, “Artificial intelligence-enabled assessments in education,” Computers & Education, vol. 165, 2021.

[27] K. R. Koedinger, J. L. Booth, and D. Klahr, “Instructional complexity and the science of learning,” Current Directions in Psychological Science, vol. 23, no. 5, pp. 374–380, 2015.

[28] T. G. Olatunde-Aiyedun, “Artificial intelligence (AI) in education: Integration of AI into science education curriculum in Nigerian universities,” Int. J. Artif. Intell. Digit., vol. 1, no. 1, pp. 14–24, 2024.

[29] P. O. Emesiobi and B. B. Macauley, “Innovative approaches to curriculum development: An implication for quality curriculum design,” International Journal of Research Publication and Reviews, vol. 6, no. 10, pp. 574–580, 2025.

[30] E. J. Andorshiye and L. N. Orlu, “Educational curriculum and artificial intelligence in today’s world,” International Journal of Research Publication and Reviews, vol. 6, no. 8, pp. 4542–4549, 2025.

[31] U. Aja-Okorie, “Teachers personal management as a determinant of teachers productivity in secondary school,” vol. 4, no. 8, 2016.

[32] B. Bali, E. J. Garba, A. S. Ahmadu, K. T. Takwate, and Y. M. Malgwi, “Analysis of emerging trends in artificial intelligence for education in Nigeria,” Discover Artificial Intelligence, vol. 4, no. 110, 2024, doi: 10.1007/s44163-024-00163-y.

[33] M. Campbell, A. J. Hoane, and F. Hsu, “Deep Blue,” Artificial Intelligence, vol. 134, no. 1–2, pp. 57–83, 2002.

[34] Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” Nature, vol. 521, no. 7553, pp. 436–444, 2015.

[35] G. A. Mahuta and H. Abubakar, “Artificial intelligence in higher education in Nigeria: Challenges and way forward,” Journal of Contemporary Research in Educational Administration & Management, vol. 2, no. 3, pp. 62–71, 2025.

[36] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed. Hoboken, NJ: Pearson, 2021.

[37] E. I. Silas, M. O. Ekong, and I. M. Akpan, “Exploring AI-driven adaptive learning systems for personalized education in Nigerian TVET institutions to enhance student engagement and skill acquisition outcomes,” World Journal of Innovation and Modern Technology, vol. 8, no. 5, pp. 186–196, 2024.

[38] N. P. Ughenu, C. J. Ukandu, U. N. Okeke, C. E. Akpulue, and U. Uju, “Leveraging artificial intelligence in educational planning and management of secondary schools in Nigeria,” World Journal of Innovation and Modern Technology, vol. 9, no. 4, pp. 62–73, 2025.

[39] K. I. Vorobyeva et al., “Personalized learning through AI: Pedagogical approaches and critical insights,” Contemporary Educational Technology, vol. 17, no. 2, 2025, doi: 10.30935/cedtech/16108.

Downloads

Published

2026-02-21

How to Cite

Macauley, B. B. (2026). Leveraging Pedagogical Innovation in Nigerian System of Education: An Application of Artificial Intelligence for Personal Learning and Research Writing. Excellencia: International Multi-Disciplinary Journal of Education (2994-9521), 4(2), 298-309. https://multijournals.org/index.php/excellencia-imje/article/view/3786