Online Exam Proctoring

Abstract

In recent years, online examinations have been increasingly utilized to assess students' abilities to teach knowledge, particularly during the COVID-19 outbreak. However, due to the lack of face-to-face connection, proctoring online tests is difficult. Furthermore, past study has demonstrated that online examinations are vulnerable to nu- serous duping techniques, which can compromise their legitimacy. Specifically, this project detects suspected student by user verification, Head-Pose Analysis, Gaze Estimation, Person Counting, Active Window detection, Mobile Phone Detection, Multiple Monitor Detection. Massive open online courses (M O O Cs) and other kinds of distance learning are growing in popularity and reach. The ability to successfully proctor remote online tests is a key limiting issue in this next stage of education's scalability. Human proctoring is currently the most frequent method of assessment, which involves either forcing test takers to visit an examination center or watching them visually and audibly throughout exams via a digital camera.