Artificial Intelligence in the Educational System: Theoretical Perspectives and a Practical Application for Cheating Detection in Examination Halls"

Abstract

This article reviewed some of the roles played by artificial intelligence (AI) as a modern technology in the educational system. We also tested an AI-based application to detect cheating during exams by analyzing facial and eye movements. The system uses computer vision techniques via the OpenCV library, along with an alert device designed based on Arduino, allowing for real-time monitoring and response. Haar Cascade algorithms were used to detect faces and eyes, and head movement and gaze direction were tracked using optical flow and motion center calculation techniques. An SVM classification algorithm was used to identify suspicious behavior based on features extracted from the image.
Experiments showed that the proposed system achieved an accuracy of more than 90% in detecting cheating cases in real time. There are also some challenges such as poor lighting. The research is considered a contributing factor in enhancing academic integrity in educational institutions. The results indicate that AI-based surveillance systems can be effective in educational settings, and suggest future development of the system using deep learning techniques and multiple cameras to improve performance.