From Regurgitation to Critical Knowledge Production: A Scoping Review Protocol of Developmental AI Research Frameworks in African Higher Education

Background: The increasing use of generative artificial intelligence (AI) in higher education has raised concerns about uncritical AI-assisted content reproduction, often described as AI regurgitation, and its implications for postgraduate research development, epistemic agency, and academic integrity. These concerns are particularly salient in African higher education contexts, where longstanding epistemic inequalities intersect with rapidly expanding algorithmic technologies. Objective: This scoping review aims to map developmental AI research frameworks that support progression from AI-assisted content reproduction to critical knowledge production in higher education, with particular attention to African contexts and Indigenous Knowledge Systems. Methods: Guided by the Arksey and O’Malley framework and reported in accordance with PRISMA-ScR guidelines. The review will synthesise English-language literature published between 2010 and 2025 from Scopus, Web of Science, ERIC, and Google Scholar. Data will be charted and analysed using descriptive mapping and interpretive synthesis to examine how existing AI research frameworks conceptualise learner progression, epistemic responsibility, ethical AI use, and contextual relevance. Discussion: The review is expected to identify a predominance of instrumental AI literacy approaches, limited explicit engagement with Indigenous epistemologies, and significant gaps in developmental AI research frameworks tailored to African postgraduate research contexts. By systematically mapping conceptual trends and gaps, the scoping review will provide a rigorous foundation for the development of an Indigenised Novice-to-Expert AI research framework aimed at fostering ethical, critical, and contextually grounded AI-supported research in African higher education.