Continuous and Transparent E-Invigilation of E-Assessments

Abstract

A massive number of users are currently utilizing e-learning. Despite the flexibility provided, the traditional methods of course delivery are still used, including e-examinations. There is significant concern about the potential for cheating. The current solutions in this respect fundamentally fail to offer the required level of security. This paper seeks to develop an e-invigilator that will provide continuous and transparent invigilation of examinees. The study involves a detailed presentation of the proposed architecture and a complete design to be the core of the system, which captures, processes, and monitors students in a controlled and convenient fashion. The proposed framework prototype was developed, presented, and utilized, involving 51 participants to conduct an experiment to explore the viability of the proposed framework. For all 51 participants in this experiment, the false rejection rate was 0 in 2D facial recognition mode, while in 3D facial recognition mode it was 0.04827. Moreover, in order to evaluate the robustness of the approach against targeted misuse, three participants were tasked with a series of nine threat scenarios. The false acceptance rate was 0.038 in the 2D mode and 0 in the 3D mode.