Generative AI and the Future of University Education in Africa: Does AI Undermine the Value of Traditional Learning

Faisal Iddris; Salami Abdul Mohammed; Juliet Acheampong

doi:10.51137/wrp.ijarbm.596

Authors

Faisal Iddris Faculty of Business Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana Author
Salami Abdul Mohammed College of Business, Westcliff University, Irvine, California, USA. Author
Juliet Acheampong Faculty of Business Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana Author

DOI:

https://doi.org/10.51137/wrp.ijarbm.596

Keywords:

Generative AI, Higher Education, Institutional Theory, Governance, Student Perceptions, Africa

Abstract

The rapid diffusion of generative artificial intelligence (AI) tools such as ChatGPT has intensified debates about their implications for learning, academic integrity, and institutional governance in higher education. While existing research has predominantly focused on Western university contexts, limited attention has been paid to how students in African higher education systems perceive the legitimacy and regulation of generative AI. Drawing on institutional theory, this study examines Ghanaian university students’ perceptions of generative AI, focusing on its perceived effectiveness relative to traditional learning, gender-based differences in attitudes, and preferences for regulation versus prohibition. Using a cross-sectional survey design, data were collected from 341 students enrolled in public universities in Ghana. Descriptive statistics and independent samples t-tests were employed to examine patterns of AI use and perception. The findings indicate that generative AI has become widely normalized in students’ academic practices, with most respondents reporting prior use. Students largely perceive AI as a complementary learning tool that enhances efficiency, feedback, and access, while continuing to value human instructors as central to meaningful learning. Female students report more favourable perceptions of AI’s academic utility than male students, although concerns about over-reliance, fairness, and the replacement of educators are shared across genders. Notably, the majority of students oppose banning generative AI and instead favour formal regulation and institutional integration. The study contributes to AI-in-education research by extending empirical evidence to a Global South context and by reframing student perceptions as signals of institutional legitimacy and governance expectations. The findings suggest that the central challenge for universities is no longer AI adoption but institutional adaptation, particularly the development of regulatory frameworks that align with established student practices while safeguarding academic integrity.

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