project

1.

Exam cheating
using digital
tools.
Arseniy Kan dtnp-2604

2.

Problem + Research Purpose
Proliferation of digital cheating tools
Inefficiency of human invigilation in
remote and large
-scale environments
Research Purpose: Evaluate the
effectiveness, architectures, and
limitations of AI-driven Automated
Proctoring Systems (AIPS)

3.

Methodology
PRISMA systematic review methodology
10-year span: 2014–2024 ,pre- and post-pandemic evolution
Comparative evaluation of ML, DL,
and IoT detection frameworks
Synthesized 80 peer
-reviewed empirical
studies across 5 major databases

4.

Three Key Findings & Evidence
High Detection Accuracy in Visual Cues
Behavioral Biometrics for Digital Misconduct
Dataset and Generalization Bottlenecks

5.

Personal Reflection &
Recommendation
Psychological toll: invasive
surveillance vs. test anxiety
The algorithmic bias problem
in facial and gaze tracking
Recommendation: Adopt multimodal,
privacy-preserving hybrid models
with human-in-the-loop oversight

6.

References
Malhotra, M., & Chhabra, I. (2026).
Ensuring academic integrity through
automated online exam proctoring: A
decade long systematic review.
Discover Education, 5, Article 207.
https://link.springer.com/content/pdf/1
0.1007/s44217-026-01224-3.pdf
https://joiv.org/index.php/joiv/article/vi
ew/2894/1724