Unveiling AI’s impact in Rwandan higher education: navigating trends, challenges, and imperatives at the University of Rwanda - Abbes Sebihi; Leonie Schoelen; Berthilde Uwamwezi (Discover Education)
Abstract In the wake of the Covid-19 pandemic, which hastened the digitalization of education, the imperative to harness Artificial Intelligence (AI)'s potential has never been more pressing. While studies abound on the broader impact of technology in education, there remains a conspicuous gap in understanding its specific implications for African countries. These nations, historically marginalized in the discourse of technological advancement, confront unique challenges and opportunities in leveraging AI to advance their educational agendas. The objective of this contribution is to assess, and identify AI readiness with a focus on accompanying policy by an exemplary survey of academic practice at a East African higher education institution, the University of Rwanda. It encompasses three pivotal sections: an in-depth analysis of prevailing technological trends in academia, differentiating between AI and e-learning methodologies; an empirical investigation based on 32 responses of a structured online survey, featuring insights from teaching and research staff at the University of Rwanda; and an examination of policy implications informed by its findings, coupled with actionable recommendations to propel e-learning initiatives across Rwanda. The research questions address AI readiness on both the individual and the institutional level. Of exploratory nature, the theoretical framework is informed by the Technology Acceptance Model and constructive learning and interpretive theory. The results show that there is a perceived potential of AI that is particularly relevant for the African higher education context. It can enhance education through targeted and personalized learning, improve access to information, and facilitate research and teaching. There is, however, the need for regulatory frameworks and ethics considerations, more so that two response items are likely AI-generated.