The Role of Artificial Intelligence in Transforming Research Methods in Science Education in Nigeria
Authors
Integrated Science Department, School of Sciences, Fct College of Education Zuba, Abuja (Nigeria)
Integrated Science & Environmental Education Department Federal University of Education, Pankshin Plateau State (Nigeria)
Article Information
DOI: 10.47772/IJRISS.2026.10100135
Subject Category: Artificial Intelligence
Volume/Issue: 10/1 | Page No: 1677-1684
Publication Timeline
Submitted: 2026-01-07
Accepted: 2026-01-12
Published: 2026-01-27
Abstract
The rapid advancement of Artificial Intelligence (AI) has significantly transformed research methodologies across educational disciplines including science education in Nigeria. This paper examines the role of artificial intelligence in transforming research methods in science education in Nigeria. Thus, AI enhances the collection, analysis and interpretation of educational data with a focus on quantitative, qualitative and mixed methods research approaches. Using a qualitative review of existing literature and case studies in Nigerian educational contexts, the paper identifies key applications of AI including learning analytics, virtual laboratories, automated assessment and natural language processing tools for qualitative analysis. Indeed, AI provides opportunities for improving instructional strategies, supporting evidence-based decision-making, and strengthening teacher professional development. However, challenges such as poor digital infrastructure, limited AI awareness among educators, high costs, ethical concerns and curriculum gaps constrain its full adoption. The paper concludes that deliberate investment in digital infrastructure, capacity-building programmes, ethical guidelines, affordable AI tools and curriculum reform are critical for maximizing AI’s potential in transforming science education research in Nigeria. The paper recommends that government and private sector stakeholders should improve internet connectivity, provide stable electricity and equip schools and research institutions with modern ICT facilities and that educational authorities must establish clear policies on data privacy, consent and algorithmic fairness to ensure responsible and ethical AI usage among.
Keywords
Artificial Intelligence, Science Education, Research Methods, Nigeria, Quantitative, Qualitative, Mixed-Methods
Downloads
References
1. Adebayo, A. S., & Abdulrahman, M. O. (2023). Learning analytics and student performance prediction in Nigerian tertiary institutions. Journal of Educational Technology and Data Science, 4(1), 55–70. [Google Scholar] [Crossref]
2. Aderemi, T. (2023). Digital infrastructure and the future of educational technology in Nigeria. Journal of ICT Development, 11(2), 44–58. [Google Scholar] [Crossref]
3. Adewumi, M., & Ajayi, O. (2021). ICT gaps and challenges in Nigeria’s digital transformation agenda. African Journal of Educational Technology, 9(1), 22–35. [Google Scholar] [Crossref]
4. Bamidele, T. J., & Ibrahim, Y. M. (2024). Artificial intelligence for educational research productivity in Africa: Implications for science education. African Journal of Digital Learning, 2(2), 88–103. [Google Scholar] [Crossref]
5. Bello, R., & Yusuf, A. (2022). Public-private partnerships in advancing educational technology in Africa. International Journal of Innovation in Education, 6(3), 101–115. [Google Scholar] [Crossref]
6. Chiemeke, S., & Adeoye, I. (2021). Capacity building for AI adoption among educators in Sub-Saharan Africa. Education and Information Technologies, 26(4), 5123–5140. [Google Scholar] [Crossref]
7. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. [Google Scholar] [Crossref]
8. Eneh, P. U., & Ugochukwu, C. A. (2023). Artificial intelligence and equitable access to STEM education in Nigeria. International Journal of Science Education and Innovation, 15(3), 112–128. [Google Scholar] [Crossref]
9. Eze, U., & Nwosu, C. (2022). Curriculum reform and digital competence development in teacher education. Nigerian Journal of Curriculum Studies, 29(1), 89–104. [Google Scholar] [Crossref]
10. Ezeani, I. S., & Nwankwo, O. U. (2021). Artificial intelligence and the future of virtual laboratory experiences in Nigerian secondary schools. Journal of Science Education and Technology, 30(4), 512– 525. [Google Scholar] [Crossref]
11. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to design and evaluate research in education (10th ed.). McGraw-Hill. < [Google Scholar] [Crossref]
12. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. [Google Scholar] [Crossref]
13. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson. [Google Scholar] [Crossref]
14. Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation (4th ed.). Jossey-Bass. [Google Scholar] [Crossref]
15. Mohammed, K., & Abdullahi, R. (2021). Cost implications of adopting emerging technologies in higher education. Journal of African Educational Research, 3(2), 77–88. [Google Scholar] [Crossref]
16. Nnamani, J., & Uzochukwu, P. (2023). Integrating AI literacy into science education programmes in Nigeria. Journal of Science Teacher Education in Africa, 4(1), 15–28. [Google Scholar] [Crossref]
17. Nwosu, I. C., & Chiemeke, S. C. (2023). Natural language processing tools for qualitative research in Nigerian educational settings. Journal of Applied Computing in Education, 7(2), 43–59. [Google Scholar] [Crossref]
18. Okechukwu, P. O., & Fajemidagba, M. O. (2022). Virtual science laboratories and AI-driven simulations in Nigerian secondary schools. Nigerian Journal of Science Teaching and Learning, 18(1), 92–104. [Google Scholar] [Crossref]
19. Okonkwo, T., & Chukwu, L. (2022). Teachers’ readiness for digital transformation in Nigerian secondary schools. Education Today Review, 14(3), 33–47. [Google Scholar] [Crossref]
20. Olatunji, A. (2023). Ethical considerations in AI-driven educational research in Africa. African Journal of Ethics and Technology, 2(1), 55–70. [Google Scholar] [Crossref]
21. Olatunji, T. A., & Adegoke, B. A. (2022). Artificial intelligence and teacher professional development in Nigerian science classrooms. Journal of Innovative Pedagogy and Digital Learning, 6(4), 201–216. [Google Scholar] [Crossref]
22. Olayemi, S. (2023). Responsible AI governance for the education sector in Nigeria. Journal of Policy and Digital Society, 8(2), 141–159. [Google Scholar] [Crossref]
23. Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson. [Google Scholar] [Crossref]
24. Yusuf, M. O., & Adewale, O. S. (2022). Digital transformation and artificial intelligence in Nigerian higher education: Prospects and challenges. International Journal of Education and Development using ICT, 18(1), 45–60. [Google Scholar] [Crossref]
25. 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), 1–27. [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- The Role of Artificial Intelligence in Revolutionizing Library Services in Nairobi: Ethical Implications and Future Trends in User Interaction
- ESPYREAL: A Mobile Based Multi-Currency Identifier for Visually Impaired Individuals Using Convolutional Neural Network
- Comparative Analysis of AI-Driven IoT-Based Smart Agriculture Platforms with Blockchain-Enabled Marketplaces
- AI-Based Dish Recommender System for Reducing Fruit Waste through Spoilage Detection and Ripeness Assessment
- SEA-TALK: An AI-Powered Voice Translator and Southeast Asian Dialects Recognition