Measuring the Adoption and Efficacy of AI-Powered Tools in Academic Writing and Peer Review among Academics in Nigerian Universities

This study investigates the adoption, perceived efficacy, and ethical considerations surrounding the use of AI-powered tools in academic writing and peer review among academics in Nigerian Universities. Employing a descriptive survey design, data were collected from 425 respondents across disciplines using structured questionnaires. The findings reveal a moderate adoption rate of 62.12%, with generative AI tools being less frequently used compared to grammar and writing assistance tools. While 88% of respondents perceived AI tools as highly useful—particularly in enhancing writing quality—only 25% reported having the necessary facilitating conditions to use them effectively. Furthermore, the study identified significant ethical concerns, with 95% of respondents rejecting AI as a co-author and 90% lamenting the absence of institutional policies on AI use. Despite recognizing efficiency and time savings (92%), only 20% expressed confidence in AI's independent role in peer review, highlighting the need for human oversight. The study concludes that while AI tools hold great promise in academic work, their adoption and effectiveness are constrained by infrastructural, ethical, and policy-related challenges. It recommends targeted training, policy development, and institutional support to ensure ethical, responsible, and effective integration of AI tools in academic settings.

AI-powered tools, academic writing, peer review, adoption, efficacy, ethics, Nigerian academic integrity

1. Adebayo, M., & Johnson, T. (2023). AI tools and peer review in academia. Nigerian Journal of Educational Technology, 15(2), 66–82. [Google Scholar] [Crossref]

2. Adeleke, R. A. (2022). The unregulated rise of AI tools in Nigeria's education sector. African Journal of Educational Policy, 4(2), 32–45. [Google Scholar] [Crossref]

3. Bello, A. A., & Asogwa, B. E. (2022). Ethical challenges of artificial intelligence use in Nigerian universities. Nigerian Journal of Educational Research and Evaluation, 21(1), 85–97. [Google Scholar] [Crossref]

4. Bello, A., & Hassan, R. (2022). Awareness and use of AI tools in Nigerian university libraries. Library Trends in Africa, 10(1), 12–25. [Google Scholar] [Crossref]

5. Boden, M., Bryson, J., Caldwell, D., Dignum, V., & Dignum, F. (2021). Principles of AI ethics: Towards a global framework. AI & Society, 36(3), 431–437. https://doi.org/10.1007/s00146-020-00960-w [Google Scholar] [Crossref]

6. 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 [Google Scholar] [Crossref]

7. Eze, P. (2022). Generative AI and academic integrity: Implications for Nigerian universities. Journal of Academic Ethics, 20(1), 45–59. https://doi.org/10.1007/s10805-021-09410-9 [Google Scholar] [Crossref]

8. Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1 [Google Scholar] [Crossref]

9. Ibrahim, K. (2023). Academic writing in the age of AI: Opportunities and risks. African Journal of Language and Communication, 9(4), 101–115. [Google Scholar] [Crossref]

10. Ienca, M., & Vayena, E. (2020). On the responsible use of AI in biomedical research. Nature Medicine, 26(4), 463–464. https://doi.org/10.1038/s41591-020-0809-7 [Google Scholar] [Crossref]

11. Ige, O., & Shorunke, S. (2023). Policy gaps in AI adoption in Nigerian higher education. International Review of Information Ethics, 21(2), 56–70. [Google Scholar] [Crossref]

12. Kokol, P., Blažun Vošner, H., & Završnik, J. (2023). ChatGPT and scholarly publishing: Is the academic community prepared? Scientometrics, 128, 2069–2084. https://doi.org/10.1007/s11192-023-04660-0 [Google Scholar] [Crossref]

13. Lee, J., Kim, Y., & Kim, M. (2022). Generative AI for academic writing: Use cases and ethical dilemmas. Computers & Education, 180, 104470. https://doi.org/10.1016/j.compedu.2022.104470 [Google Scholar] [Crossref]

14. Nwosu, B., & Abubakar, M. (2022). ICT infrastructure and AI readiness in Nigerian universities. African Journal of ICT Development, 14(3), 77–93. [Google Scholar] [Crossref]

15. Obi, C., & Alade, K. (2021). Artificial intelligence and policy gaps in African education. Journal of Policy Studies in Africa, 10(1), 19–35. [Google Scholar] [Crossref]

16. Okoye, J., & Lawal, M. (2022). Adoption patterns of AI tools by Nigerian university students. Journal of Digital Pedagogy, 5(1), 29–41. [Google Scholar] [Crossref]

17. Okoye, M., & Nwachukwu, C. (2022). Digital divide and AI utilization in Nigerian higher education. Journal of African Educational Research, 18(2), 89–101. [Google Scholar] [Crossref]

18. Schwab, K. (2017). The fourth industrial revolution. World Economic Forum. [Google Scholar] [Crossref]

19. Tang, R., Ma, F., Zhang, L., & Zhao, H. (2023). Artificial intelligence-assisted peer review: Opportunities and challenges. Nature Machine Intelligence, 5(2), 98–106. https://doi.org/10.1038/s42256-023-00610-w [Google Scholar] [Crossref]

20. UNESCO. (2021). Recommendation on the ethics of artificial intelligence. Paris: United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000380455 [Google Scholar] [Crossref]

21. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926 [Google Scholar] [Crossref]

22. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org [Google Scholar] [Crossref]

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