Optimized collusion prevention for online exams during social distancing

Abstract Online education is important in the COVID-19 pandemic, but online exam at individual homes invites students to cheat in various ways, especially collusion. While physical proctoring is impossible during social distancing, online proctoring is costly, compromises privacy, and can lead to pr...

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Autores principales:	Mengzhou Li, Lei Luo, Sujoy Sikdar, Navid Ibtehaj Nizam, Shan Gao, Hongming Shan, Melanie Kruger, Uwe Kruger, Hisham Mohamed, Lirong Xia, Ge Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Special aspects of education LC8-6691 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/4b985adc8f864ecf96460e21ce866e20
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spelling	oai:doaj.org-article:4b985adc8f864ecf96460e21ce866e202021-12-02T13:30:09ZOptimized collusion prevention for online exams during social distancing10.1038/s41539-020-00083-32056-7936https://doaj.org/article/4b985adc8f864ecf96460e21ce866e202021-03-01T00:00:00Zhttps://doi.org/10.1038/s41539-020-00083-3https://doaj.org/toc/2056-7936Abstract Online education is important in the COVID-19 pandemic, but online exam at individual homes invites students to cheat in various ways, especially collusion. While physical proctoring is impossible during social distancing, online proctoring is costly, compromises privacy, and can lead to prevailing collusion. Here we develop an optimization-based anti-collusion approach for distanced online testing (DOT) by minimizing the collusion gain, which can be coupled with other techniques for cheating prevention. With prior knowledge of student competences, our DOT technology optimizes sequences of questions and assigns them to students in synchronized time slots, reducing the collusion gain by 2–3 orders of magnitude relative to the conventional exam in which students receive their common questions simultaneously. Our DOT theory allows control of the collusion gain to a sufficiently low level. Our recent final exam in the DOT format has been successful, as evidenced by statistical tests and a post-exam survey.Mengzhou LiLei LuoSujoy SikdarNavid Ibtehaj NizamShan GaoHongming ShanMelanie KrugerUwe KrugerHisham MohamedLirong XiaGe WangNature PortfolioarticleSpecial aspects of educationLC8-6691Neurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENnpj Science of Learning, Vol 6, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Special aspects of education LC8-6691 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Special aspects of education LC8-6691 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Mengzhou Li Lei Luo Sujoy Sikdar Navid Ibtehaj Nizam Shan Gao Hongming Shan Melanie Kruger Uwe Kruger Hisham Mohamed Lirong Xia Ge Wang Optimized collusion prevention for online exams during social distancing
description	Abstract Online education is important in the COVID-19 pandemic, but online exam at individual homes invites students to cheat in various ways, especially collusion. While physical proctoring is impossible during social distancing, online proctoring is costly, compromises privacy, and can lead to prevailing collusion. Here we develop an optimization-based anti-collusion approach for distanced online testing (DOT) by minimizing the collusion gain, which can be coupled with other techniques for cheating prevention. With prior knowledge of student competences, our DOT technology optimizes sequences of questions and assigns them to students in synchronized time slots, reducing the collusion gain by 2–3 orders of magnitude relative to the conventional exam in which students receive their common questions simultaneously. Our DOT theory allows control of the collusion gain to a sufficiently low level. Our recent final exam in the DOT format has been successful, as evidenced by statistical tests and a post-exam survey.
format	article
author	Mengzhou Li Lei Luo Sujoy Sikdar Navid Ibtehaj Nizam Shan Gao Hongming Shan Melanie Kruger Uwe Kruger Hisham Mohamed Lirong Xia Ge Wang
author_facet	Mengzhou Li Lei Luo Sujoy Sikdar Navid Ibtehaj Nizam Shan Gao Hongming Shan Melanie Kruger Uwe Kruger Hisham Mohamed Lirong Xia Ge Wang
author_sort	Mengzhou Li
title	Optimized collusion prevention for online exams during social distancing
title_short	Optimized collusion prevention for online exams during social distancing
title_full	Optimized collusion prevention for online exams during social distancing
title_fullStr	Optimized collusion prevention for online exams during social distancing
title_full_unstemmed	Optimized collusion prevention for online exams during social distancing
title_sort	optimized collusion prevention for online exams during social distancing
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/4b985adc8f864ecf96460e21ce866e20
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Optimized collusion prevention for online exams during social distancing

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