E-Assessment Proctoring Using Artificial Intelligence Technologies: A Review of Practices and Challenges in the African Context

Abstract

The rapid expansion of e-learning across African higher education institutions has accelerated the adoption of electronic assessments (e-assessments), intensifying concerns regarding examination integrity. Artificial intelligence (AI)-based proctoring technologies have emerged as a promising approach to mitigating academic dishonesty through automated monitoring, biometric authentication, and behavioral analytics. However, the effectiveness, ethical implications, and contextual suitability of these technologies within the African educational landscape remain underexplored. This review synthesizes empirical and conceptual studies on AI-enabled e-assessment proctoring in Africa to examine prevailing practices, challenges, and research gaps. Guided by the PRISMA 2020 guidelines, a systematic search of major academic databases identified 250 relevant studies published between 2015 and 2024, of which 25 met the inclusion criteria for qualitative and quantitative synthesis. The findings reveal a growing adoption of AI techniques, including facial recognition, keystroke dynamics, gaze tracking, and anomaly detection, alongside persistent challenges related to internet instability, algorithmic bias, data privacy concerns, system scalability, and institutional readiness. Notably, there is limited empirical evaluation of mobile-first, low-resource AI proctoring frameworks tailored to African contexts. Future research should prioritize the development of lightweight, privacy-preserving AI models, incorporate participatory and inclusive design approaches, and align technological implementations with region-specific regulatory and policy frameworks to support sustainable and ethical e-assessment practices.