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VOL. 10, ISSUE 3 (2025)
Real-time AI solutions for preventing academic cheating and malpractices in examinations
Authors
Sunita Ganesh Satpute, Thorat Shubham Babasaheb
Abstract
Academic integrity is a critical concern in modern education, with the
rise of digital tools enabling sophisticated cheating methods during
examinations. This paper explores real-time AI-driven solutions to prevent
academic dishonesty and ensure fair assessments. We propose a multi-layered
approach integrating AI-powered proctoring, facial recognition, behaviour
analysis, and machine learning algorithms to detect suspicious activities, such
as unauthorized device usage, impersonation, or abnormal eye movements. By
leveraging computer vision and natural language processing, the system can
analyse student behaviour, identify anomalies, and provide instant alerts to
exam supervisors. Additionally, blockchain-based verification mechanisms can
enhance data security and prevent result tampering. The proposed framework
prioritizes privacy and ethical considerations while maintaining efficiency and
scalability across online and offline examination environments. Experimental
results demonstrate the effectiveness of AI-driven proctoring in reducing
malpractice rates and fostering a culture of academic honesty. This research
highlights the potential of real-time AI surveillance to revolutionize
examination security, ensuring a fair and credible evaluation process for
educational institutions worldwide.
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Pages:72-75
How to cite this article:
Sunita Ganesh Satpute, Thorat Shubham Babasaheb "Real-time AI solutions for preventing academic cheating and malpractices in examinations". International Journal of Advanced Scientific Research, Vol 10, Issue 3, 2025, Pages 72-75
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