Multi-Modal Online Exam Cheating Detection

Online exams have been the standard approach adopted by universities and institutes because of the COVID-19 pandemic which forces the world to go towards distance learning and online exams. But with this approach come the challenges such as online exam proctoring which is considered one of the most difficult challenges to solve. It is a must to ensure the academic honesty and credibility of the online exam. Existing proctoring techniques require a few proctors to observe a huge number of students to detect cheating students, and due to it is time-consuming and labor-intensive, we implemented multi-modalities to detect the student’s activity during the online exam using a webcam and sent a report to the proctor for the suspected student. Those modalities are head-pose, object detection and eye-gaze estimation. This proposed solution is tested and evaluated on 29 students with a total of four exam sessions to ensure the effectiveness of our proposed solution. The events’ detection accuracy of the multi-modalities experiment was 95.69%.