An Intelligent Solution based on a Multi-agent System for the Detection of Cheating in Online Exams

Abstract

Given the extreme necessity of the process of distance teaching and online learning as flexible and sustainable solutions to some major challenges in university institutions in various countries around the world, including the importance of allowing students to take exams remotely under appropriate conditions similar to those in normal in-person teaching situations, this article focuses on studying a group of online exam platforms, including learning management system platforms that enable exam creation and management, as well as monitoring software. The choice of platform depends on several criteria; the platform must be open source, reliable, and allow for the integration of other tools and software. Our work is focused on an intelligent architecture that aims to detect cheating in online exams by adopting the technique of tracking students' movements throughout the exam period. Thus, the solution we propose is based on the coupling of three tools: LMS (Moodle), with integration of the Safe Exam Browser (SEB) platform and an online monitoring tool.