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All Journal Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Indonesian Journal of Education and Mathematical Science
Mogoi, Bartholomew Oganda
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Aerospace Engineering Computer Science & IT Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics

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AI-Powered Mobile Proctoring Frameworks using Machine Learning Algorithms in Higher Education: Post-Covid Trends, Challenges, and Ethical Implications Mogoi, Bartholomew Oganda; Kamau, John; Ongus, Raymond
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3600

Abstract

The rapid transition to online learning during and after the COVID-19 (Corona Virus Disease) pandemic has heightened the need for secure, scalable, and ethical online exam systems. AI-powered mobile proctoring frameworks have emerged as viable alternatives to traditional invigilation methods, enabling automated anomaly detection and behavior analysis through machine learning algorithms. This systematic review examines post-COVID trends, technological developments, challenges, and ethical implications of mobile AI proctoring in higher education. Following PRISMA 2020 guidelines, 180 studies were retrieved and screened, with 20 peer-reviewed articles meeting the inclusion criteria. Findings reveal that while AI-powered proctoring enhances scalability, integrity, and real-time monitoring, it raises significant concerns about privacy, algorithmic bias, accessibility, and technical reliability. The review identifies gaps in relation to technical and methodological issues, ethical and social concerns, and institutional and infrastructural readiness. This review illustrates a lapse in the existing literature, which focus on resource intensive proctoring frameworks without considering mobile compatibility and light-weight frameworks, discusses technical challenges, and recommends future research directions to balance technological effectiveness with ethical standards.
E-Assessment Proctoring Using Artificial Intelligence Technologies: A Review of Practices and Challenges in the African Context Mogoi, Bartholomew Oganda; Kamau, John; Ongus, Raymond
Indonesian Journal of Education and Mathematical Science Vol 7, No 1 (2026)
Publisher : Universitas Muhammadiyah Sumatera Utara (UMSU)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ijems.v7i1.28922

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.
Co-Authors Kamau, John Ongus, Raymond