Education Sciences, Vol. 13, Pages 194: Educational Innovation Faced with COVID-19: Deep Learning for Online Exam Cheating Detection

Education Sciences, Vol. 13, Pages 194: Educational Innovation Faced with COVID-19: Deep Learning for Online Exam Cheating Detection

Education Sciences doi: 10.3390/educsci13020194

Authors: Intan Nurma Yulita Fauzan Akmal Hariz Ino Suryana Anton Satria Prabuwono

Because the COVID-19 epidemic has limited human activities, it has touched almost every sector. Education is one of the most affected areas. To prevent physical touch between students, schools and campuses must adapt their complete learning system to an online environment. The difficulty with this technique arises when the teachers or lecturers administer exams. It is difficult to oversee pupils one by one online. This research proposes the development of a computer program to aid in this effort. By applying deep learning models, this program can detect a person’s activities during an online exam based on a web camera. The reliability of this system is 84.52% based on the parameter F1-score. This study built an Indonesian-language web-based application. Teachers and lecturers in Indonesia can use this tool to evaluate whether students are cheating on online exams. Unquestionably, this application is a tool that may be utilized to develop distance learning educational technology in Indonesia.