A visual analytics approach to facilitate the proctoring of online exams

• Main Authors: LI, Haotian, XU, Min, WANG, Yong, WEI, Huan, QU, Huamin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Head pose estimation; mouse movement; online proctoring; visual analytics; Graphics and Human Computer Interfaces; Online and Distance Education
• Online Access: https://ink.library.smu.edu.sg/sis_research/7163; https://ink.library.smu.edu.sg/context/sis_research/article/8166/viewcontent/3411764.3445294.pdf
• Institution: Singapore Management University

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.