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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 4, 2017.
Abstract: With the expansion of Internet and technology over the past decade, E-learning has grown exponentially day by day. Cheating in exams has been a widespread phenomenon all over the world regardless of the levels of development. Therefore, detection of traditional cheating methods may no longer be wholly successful to fully prevent cheating during examinations. Online examination is an integral and vital component of E-learning. Students’ exams in E-learning are remotely submitted without any monitoring from physical proctors. As a result of being able to easily cheat during e-exams, E-learning universities depend on an examination process in which students take a face-to-face examination in a physical place allocated at the institution premises under supervised conditions, however this conflicts with the concept of distant E-learning environment. This paper will investigate the methods used by student for cheating detection in online exams, through continuous authentication and online proctors. In addition, we have implemented an E-exam management system, which used to detect and prevent the cheating in online exams. The system used fingerprint reader authenticator and eye tribe tracker in exam session. We researched two parameters that can define the examinee status as cheating or non-cheating during exam. Through these two parameters: the total time on out screen and the number of times on out screen were computed.
Razan Bawarith, Dr. Abdullah Basuhail, Dr. Anas Fattouh and Prof. Dr. Shehab Gamalel-Din, “E-exam Cheating Detection System” International Journal of Advanced Computer Science and Applications(IJACSA), 8(4), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080425
@article{Bawarith2017,
title = {E-exam Cheating Detection System},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080425},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080425},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {4},
author = {Razan Bawarith and Dr. Abdullah Basuhail and Dr. Anas Fattouh and Prof. Dr. Shehab Gamalel-Din}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.