Mapping the landscape of artificial intelligence in teaching and learning across African higher education
Year: 2025
Type: article
Abstract: Artificial Intelligence (AI) is rapidly transforming global teaching and learning (T&L) processes in higher education. As the integration of AI in African higher education continues to accelerate, the body of research examining its implementation remains relatively limited. This study presents a bibliometric analysis of AI applications for T&L within higher education institutions on the African continent, utilising Scopus-indexed publications from 2008 to 2025. The analysis employs VOSviewer software to visualise publication trends, co-occurring keywords, and country-specific contributions. One hundred and five relevant documents were extracted and analysed, encompassing peer-reviewed journal articles, conference papers, book chapters, and books. The results reveal a sharp increase in AI-related publications since 2023, with South Africa, Nigeria, and Morocco emerging as key contributors. The University of South Africa and the University of Johannesburg are identified as the most active institutions in this domain. The co-occurrence analysis identified three main thematic clusters: AI-driven Knowledge Networks, Resilient Learning Technologies, and AI and Education Computing. Emerging keywords include generative AI, personalised learning, contrastive learning, and ChatGPT, while ethical considerations remain notably absent. The study highlights the growing academic interest and substantial research gaps, particularly concerning ethical and policy frameworks for AI integration in African universities. It concludes by recommending a deeper engagement with AI ethics and an expansion of research to underrepresented regions on the continent. The insights provided contribute to global discourse and offer a foundation for evidence-based policy and pedagogical innovation within the African higher education sector.
Institution: Walter Sisulu University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4415483515