AI Integration and Cognitive De-Skilling in Rivers State University

Ichenwo Glory PhD Ellah; Charlie Chukwudi PhD

doi:10.56201/wjimt.v10.no6.2026.pg52.58

📄 Download Paper

AI Integration and Cognitive De-Skilling in Rivers State University

Ichenwo Glory PhD Ellah, Charlie Chukwudi PhD

Abstract

The rapid integration of Artificial Intelligence (AI) in higher education has sparked significant concerns regarding "cognitive de-skilling", the erosion of critical thinking and analytical abilities due to over-reliance on automated tools. This study investigated the impact of AI adoption on the intellectual development of students at Rivers State University , Nigeria. Using a descriptive survey design, data were collected from a stratified sample of 400 respondents, including 350 students and 50 academic staff across various faculties. Findings revealed a high prevalence of AI usage (82%), primarily for summarizing and drafting assignments. However, results indicated a significant correlation between AI reliance and a decline in core academic skills, such as argumentative writing and complex problem-solving. The study identified a "shortcut culture" where students prioritize output over the cognitive process of learning. Faculty observations confirmed a homogenization of student work and a weakening of original synthesis. The study concludes that while AI enhances efficiency, it poses a threat to intellectual autonomy if unregulated. It recommends that RSU implement an institutional AI policy, redesign assessments to include oral defenses and in-class tasks, and integrate critical AI literacy into the curriculum to ensure that technological progress scaffolds rather than replaces human cognitive capacity.

Keywords

Artificial IntelligenceCognitive De-skillingRivers State UniversityHigher EducationCritical ThinkingNigeria.

References

Adebayo, O. S., & Okon, E. E. (2023). Artificial intelligence in Nigerian higher education: Benefits and the risk of intellectual atrophy. Journal of African Educational Technology, 12(3), 88–104. Anyanwu, C. U., & Nwosu, K. I. (2024). The impact of generative AI on student research capabilities in South-South Nigeria. Nigerian Journal of Educational Research and Evaluation, 19(1), 12–25. Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922 Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7–19. https://doi.org/10.1093/analys/58.1.7 Fabunmi, B. A. (2023). The ghost in the machine: Cognitive offloading and the future of Nigerian undergraduates. West African Journal of Applied Psychology, 21(1), 45–59. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. UCL Press. Oyelere, S. S., Agbo, F. J., & Sanusi, I. T. (2023). AI in the African classroom: A double-edged sword for sustainable development goal 4. International Journal of Educational Technology in Higher Education, 20(14), 1–22. https://doi.org/10.1186/s41239-023- 00391-w Prensky, M. (2001). Digital natives, digital immigrants part 1. On the Horizon, 9(5), 1–6. https://doi.org/10.1108/10748120110424816 Rivers State University. (2023). Academic brief and strategic plan for digital integration (2023- 2028). RSU Press. Selwyn, N. (2022). Education and technology: Key issues and debates (3rd ed.). Bloomsbury Academic. Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3–10. UNESCO. (2023). Guidance for generative AI in education and research. United Nations Educational, Scientific and Cultural Organization. https://unesdoc.unesco.org/ark:/48223/pf0000386693 Victor, A. T., & Tamuno, S. (2024). Digital transformation at Rivers State University: Assessing student engagement with automated tools. RSU Journal of Science and Technology Education, 7(2), 112–125. Williamson, B., & Eynon, R. (2020). Historical threads, current lines, and future directions in contemporary critical studies of edtech. Learning, Media and Technology, 45(3), 223–235. https://doi.org/10.1080/17439884.2020.1772979

AI Integration and Cognitive De-Skilling in Rivers State University

Abstract

Keywords

References

More Articles from WORLD JOURNAL OF INNOVATION AND MODERN TECHNOLOGY