Technology-Driven Examination Malpractices: Empirical Evidence and Policy Implications from Ugandan HEIs

Abstract

The rapid digitisation of higher education has transformed assessment while amplifying integrity risks. This mixed-methods study examines technology-driven examination malpractice in Ugandan higher education institutions (HEIs), integrating a cross-sectional survey (N = 244) with key-informant interviews. Quantitative measures captured frequency/effectiveness of devices and platforms, policy/monitoring coverage, and awareness of advanced tools; qualitative data explored implementation gaps. Perceptions were high that mobile devices enable cheating (83.5% agree), yet device use showed no statistical association with malpractice indicators (χ²(16) = 6.77, p = 0.977). Messaging platforms were reported less frequently than a neutral benchmark (WhatsApp: t(119) = −4.04, p < 0.001; Telegram: t(115) = −18.31, p < 0.001). By contrast, internet-based tools differed markedly in use (means: search engines = 2.87; ghostwriting = 1.82; hacking = 1.88; χ²(2) = 28.61, p < 10⁻⁶), and advanced technologies posed recognized detection challenges (awareness: AI > calculators > AR; χ²(2) = 54.11, p < 10⁻⁶; detection difficulty mean = 2.33). Policies were rated only somewhat effective by 62.2% of respondents, and 67.5% reported some form of monitoring, highlighting uneven implementation. Correlations between prevention strategies and a composite reduction index were moderate–strong (r = 0.63–0.70) but reflect a construction artefact rather than causality. Qualitative themes converged on limited surveillance coverage, insufficient invigilation, infrastructure instability, and inconsistent enforcement, with prioritised reforms including expanded CCTV (20.6% of suggestions), stricter penalties (16.4%), and increased invigilators (15.2%). Interpreted through General Deterrence Theory, findings suggest that raising certainty and rapidity of detection—via comprehensive monitoring, trained staffing, and rapid adjudication—alongside assessment redesign and targeted use of AI-assisted proctoring, offers the most credible pathway to safeguarding integrity in low-resource HEIs.