X. Nguyen, Viet Man Le-Pham, T. Than, Minh-Son Nguyen
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Organizing exams is an important part of teaching activities that measure learners' learning outcomes. Normally, there are 2 forms of exam organization today: face-to-face and online exams. Proctoring of candidates aims to minimize fraud and to make statistical reports on the unusual behavior of candidates during the exam as the main challenges of online examination [1]. In this paper, we propose a model of Proctoring of Online Test (POT) built on the foundation of an embedded system integrating artificial intelligence algorithms to solve the problem of authentication and predict the cheating behavior of candidates in the exam. The highlight of the system is the ability to automatically and continuously monitor in real time during the online exam. Experimental results show that the POT system is capable of detecting fraud at over 85%. Therefore, the POT solution provides training institutions with a method to assess the learning quality of learners with low operating costs and rapid deployment.
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