Relationship between Generative AI Usage and Academic Performance among Undergraduate and Graduate Students in Kenyan Universities
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Abstract
This study examined the relationship between Generative Artificial Intelligence (GenAI) usage and academic performance among undergraduate and graduate students in Kenyan universities, with particular emphasis on differences between the two groups. A quantitative cross-sectional survey design was employed, collecting data from 458 students across diverse academic disciplines. Data were analysed using descriptive statistics, exploratory and confirmatory factor analyses, and structural equation modelling (SEM). The findings revealed moderate-to-high levels of GenAI usage (mean scores: 3.55–4.07), while academic performance indicators recorded consistently high ratings (M = 3.98–4.17). SEM results showed that GenAI usage positively and significantly associated with academic performance among both undergraduate (β = 0.278, p < 0.05) and graduate students (β = 0.403, p < 0.001), with a stronger effect observed among graduate students. Multi-group SEM confirmed a significant difference in the relationship between GenAI usage and academic performance across the two groups (p = 0.036), indicating that academic level moderates this relationship. The findings suggest that graduate students derive greater academic benefits from GenAI, likely due to higher levels of research competence and self-regulated learning. The study concludes that GenAI can enhance academic performance when used as a cognitive support tool rather than a substitute for independent learning. These findings provide empirical evidence to inform institutional policies, pedagogical strategies, and responsible AI integration in higher education.
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References
Anyanwu, C. C., Ononiwu, P. N., & Isiozor, G. N. (2024). Comparative impact of WhatsApp chatbot technology and Glaser's teaching approaches on the academic performance of education economics students in tertiary institutions in Nigeria. Education and Information Technologies, 29, 23801–23816. https://doi.org/10.1007/s10639-024-12780-2 DOI: https://doi.org/10.1007/s10639-024-12780-2
Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52–62. https://doi.org/10.61969/jai.1337500 DOI: https://doi.org/10.61969/jai.1337500
Belhaj, S. (2025). The influence of student-generative AI interaction on self-regulated learning and academic achievement. Journal of Advanced Research in Social Sciences and Humanities, 10(4), 28–41. https://doi.org/10.26500/JARSSH-10-2025-0403 DOI: https://doi.org/10.26500/JARSSH-10-2025-0403
Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and academic integrity concerns. Computers and Education: Artificial Intelligence, 20(43), 100134. https://doi.org/10.1016/j.caeai.2023.100134 DOI: https://doi.org/10.1016/j.caeai.2023.100134
Chen, S., & Cheung, A. C. (2025). Effect of generative artificial intelligence on university students learning outcomes: A systematic review and meta-analysis. Educational Research Review, 49, 100737. https://doi.org/10.1016/j.edurev.2025.100737 DOI: https://doi.org/10.1016/j.edurev.2025.100737
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating? Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148 DOI: https://doi.org/10.1080/14703297.2023.2190148
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 DOI: https://doi.org/10.2307/249008
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Alalwan, A. A., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., ... Wright, R. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642 DOI: https://doi.org/10.1016/j.ijinfomgt.2023.102642
Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., Shen, Y., Li, X., & Gašević, D. (2025). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology, 56(2), 489–530. https://doi.org/10.1111/bjet.13544 DOI: https://doi.org/10.1111/bjet.13544
Gerlich, M. (2025). AI and critical thinking: Exploring the cognitive offloading hypothesis in higher education. Education Sciences, 15(3), 289. https://doi.org/10.3390/educsci15030289 DOI: https://doi.org/10.3390/educsci15030289
Kamau, J. N. (2025). Generative artificial intelligence and mental well-being of university students: A structural equation modeling (SEM) based-analysis. African Journal of Business and Development Studies, 1(2), 344–358. https://doi.org/10.70641/ajbds.v1i2.135 DOI: https://doi.org/10.70641/ajbds.v1i2.135
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdinger, F., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., ... Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274 DOI: https://doi.org/10.1016/j.lindif.2023.102274
Liu, X., Guo, B., He, W., & Hu, X. (2025). Effects of generative artificial intelligence on K-12 and higher education students' learning outcomes: A meta-analysis. Journal of Educational Computing Research, 63(5), 1249–1291. https://doi.org/10.1177/07356331251329185 DOI: https://doi.org/10.1177/07356331251329185
Mutisya, D. N., & Makokha, G. L. (2016). Challenges affecting adoption of e-learning in public universities in Kenya. E-learning and Digital Media, 13(3–4), 140–157. https://doi.org/10.1177/2042753016672902 DOI: https://doi.org/10.1177/2042753016672902
Nosta, J. (2025, January 19). Cognitive offloading with AI boosts performance but may hinder deeper learning. Psychology Today. https://www.psychologytoday.com/intl/blog/the-digital-self/202501/the-shadow-of-cognitive-laziness-in-the-brilliance-of-llms
Piaget, J. (1972). The psychology of the child. Basic Books.
Roy, B. K., & Jony, M. S. (2026). Generative AI and critical thinking in higher education: Students' narratives of cognitive offloading. Journal of Interdisciplinary Studies in Education, 15(3), 263–282. https://doi.org/10.32674/jey59q25 DOI: https://doi.org/10.32674/jey59q25
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Wainaina, P. K., & Sun, Y. (2025). Educators’ perceptions and willingness to integrate Generative Artificial Intelligence in teaching and research: Evidence from Kenyan higher education. Discover Education, 4(1), 347. https://doi.org/10.1007/s44217-025-00820-z DOI: https://doi.org/10.1007/s44217-025-00820-z