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Is Algorithmic Proctoring Compatible with Equity in Canadian Universities?

Automated surveillance technologies in higher education rely on real-time behavioural tracking and biometric pattern analysis to enforce assessment integrity remotely. While intended to standardise exam security, automated proctoring software disproportionately disadvantages marginalised student cohorts through algorithmic bias, neurodivergent behavioural misclassification, and unequal technological access. Reconciling digital evaluation with equity mandates across Canadian post-secondary institutions requires shifting away from intrusive surveillance toward human-centred, inclusive assessment frameworks.

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Is Algorithmic Proctoring Compatible with Equity in Canadian Universities?

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First M. Last

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Dr. First Last

City, 2026

Contents

Introduction
Analysis: Technological Determinism and Integrity Surveillance
Analysis: Algorithmic Bias and Accessibility Barriers
Analysis: Institutional Governance and Pedagogical Alternatives
Conclusion
Bibliography

Introduction

Remote examination systems have become foundational to contemporary university assessment regimes, driven by institutional commitments to uphold academic integrity across digital learning environments [2]. Contemporary platforms incorporate automated computer vision, facial recognition, and audio monitoring algorithms to track student behaviour during live assessments [1].

However, the deployment of biometric surveillance frequently conflicts with equity and accessibility principles within Canadian higher education. Automated monitoring systems often misclassify atypical movements or environmental noises as academic misconduct, disproportionately penalising neurodivergent learners and individuals residing in shared or under-resourced living spaces [3].

This analysis examines the systemic tension between automated integrity enforcement and equity mandates in Canadian post-secondary institutions. Evaluating technological limitations and human-rights concerns reveals that algorithmic proctoring compromises institutional equity, requiring universities to adopt pedagogical assessment strategies that do not rely on punitive surveillance [1, 3].

Analysis: Institutional Governance and Pedagogical Alternatives

Advocates of automated assessment tools maintain that continuous surveillance is vital for preserving the credibility of post-secondary qualifications in remote environments. From this perspective, systems integrating deep learning and computer vision to flag suspicious eye blinking patterns, head movements, mouth adjustments, and background audio ensure uniform testing conditions and prevent academic misconduct (AI-Enhanced Multimodal Online Exam Proctoring System with Real-Time Detection and Automated Reporting, 2026). Proponents therefore contend that algorithmic tracking provides an objective, scalable deterrent against dishonesty that safeguards institutional standards across distance education. However, this reliance on automated oversight overlooks how continuous behavioural policing conflicts directly with institutional commitments to equity and accessibility. Algorithmic integrity mechanisms impose rigid normative assumptions regarding physiological composure and focus, which systematically disadvantage neurodivergent students and examinees in non-standard physical environments. Rather than establishing objective fairness, automated monitoring converts ordinary domestic sounds and diverse physical movements into presumptive evidence of academic dishonesty. Addressing these structural harms requires higher education institutions to balance technological capabilities against ethical considerations under existing academic integrity frameworks (Mapping the Contours, 2024). While educational technologies offer genuine potential for accessibility and personalized feedback, their adoption must not compromise student equity through intrusive surveillance (Mapping the Contours, 2024). Consequently, Canadian universities must move beyond punitive biometric surveillance by establishing comprehensive institutional guidelines and transparent pedagogical frameworks that protect academic integrity responsibly while guaranteeing equitable treatment for all learners.

References

  1. AI-Enhanced Multimodal Online Exam Proctoring System with Real-Time Detection and Automated Reporting
    Erri Suvarna, Dr. K. Santhi Sree
    Lien DOI
  2. Ensuring academic integrity through automated online exam proctoring a decade long systematic review
    Manit Malhotra, Indu Chhabra
    Lien DOI
  3. Mapping the Contours
    Samita Sarkar, Rahul Kumar
    Lien DOI

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