The Trend in Studies on Decoloniality, Artificial Intelligence and University Classrooms: A Systematic Review of African Higher Education Scholarship

Abstract

The convergence of decoloniality, artificial intelligence (AI), and university classroom practice has emerged as a pressing concern in African higher education. While decolonial movements such as Rhodes Must Fall and #FeesMustFall have reignited debates regarding epistemic justice within African universities, the rapid mainstreaming of generative AI has introduced new inquiries concerning whose knowledge is valued, which languages are acknowledged, and whose pedagogies are perpetuated through machine learning systems. This systematic review maps the trends in studies that engage with decoloniality, AI, and university classrooms, focusing specifically on African universities and African scholarship from 2010 to 2025. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, the review examined Scopus, Web of Science, African Journals Online, Sabinet, ERIC, and Google Scholar, supplemented by citation chasing. A total of twenty-five studies of varying types and peer-review status met the inclusion criteria. The findings indicate a marked acceleration in scholarly output following 2020, the emergence of three dominant thematic clusters (epistemic injustice and curriculum, algorithmic coloniality and data extractivism, and pedagogical adaptation of generative AI), and a significant concentration of research in South Africa, alongside emerging Pan-African scholarship on African-language AI. The review concludes that African scholarship is formulating a coherent decolonial AI research agenda; however, the scarcity of empirical evidence from classroom settings, the marginalisation of African languages within AI corpora, and uneven regional representation hinder the advancement of the field. Implications are discussed for institutional policy, curriculum design, and future research directions.