Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2021

Abstract

Online exams have become widely used in recent years to evaluate students’ performance in mastering the knowledge, especially during the pandemic of COVID-19. However, it is challenging to conduct proctoring for online exams due to the lack of face-to-face interactions. Also, prior research has shown that online exams are more vulnerable to various cheating behaviors, which can damage the credibility of online exams. In this paper, we present a novel vi- sual analytics approach to facilitate the proctoring of online exams by analyzing the exam video records and mouse movement data of each student. Specifically, we detect and visualize suspected head and mouse movements of students in three levels of detail, which provides course instructors and teachers with convenient, efficient and reliable proctoring for online exams. Our extensive evaluations, including usage scenarios, carefully-designed user studies and ex- pert interviews, demonstrate the effectiveness and usability of our approach.

Keywords

Head pose estimation, mouse movement, online proctoring, visual analytics

Discipline

Graphics and Human Computer Interfaces | Online and Distance Education

Research Areas

Data Science and Engineering

Publication

CHI '21: Proceedings of the CHI Conference on Human Factors in Computing Systems, Yokohama, May 8-13

First Page

1

Last Page

17

ISBN

9781450380966

Identifier

10.1145/3411764.3445294

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3411764.3445294

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