Online Cheating

2021 ◽  
pp. 127-130
Author(s):  
Robert Ubell
Keyword(s):  
2021 ◽  
Vol 182 ◽  
pp. 196-211
Author(s):  
Eren Bilen ◽  
Alexander Matros
Keyword(s):  

2020 ◽  
Vol 9 (2) ◽  
pp. 248
Author(s):  
Delbert Goff ◽  
Jarrod Johnston ◽  
Bryan Bouboulis

As the number of online courses being offered at universities has increased dramatically over the past several years, the level of oversight has lagged and created an environment ripe for cheating. We find that students admit to higher levels of cheating in online classes and believe other students also cheat more relative to face-to-face classes. This is likely due to the lack of tools to combat online cheating and the lack of policy from universities. We know from previous studies that business colleges have a comparatively high level of cheating and the amount of cheating at universities has been rising. These trends threaten to create an unfair system where cheaters are rewarded with higher grades than non-cheaters, thereby encouraging otherwise honest students to cheat. This may result in declining and erratic knowledge among university graduates, diminishing the value of a university education.


2021 ◽  
Vol 57 ◽  
pp. 100753
Author(s):  
Kenneth J. Smith ◽  
David J. Emerson ◽  
Shawn Mauldin
Keyword(s):  

2020 ◽  
Author(s):  
Eren Bilen ◽  
Alexander Matros
Keyword(s):  

Author(s):  
Adrian Hoffmann ◽  
Birk Diedenhofen ◽  
Bruno Verschuere ◽  
Jochen Musch

Abstract. We constructed an online cheating paradigm that could be used to validate the Crosswise Model ( Yu, Tian, & Tang, 2008 ), a promising indirect questioning technique designed to control for socially desirable responding on sensitive questions. Participants qualified for a reward only if they could identify the target words from three anagrams, one of which was virtually unsolvable as shown on a pretest. Of the 664 participants, 15.5% overreported their performance and were categorized as cheaters. When participants were asked to report whether they had cheated, a conventional direct question resulted in a substantial underestimate (5.1%) of the known prevalence of cheaters. Using a CWM question resulted in a more accurate estimate (13.0%). This result shows that the CWM can be used to control for socially desirable responding and provides estimates that are much closer to the known prevalence of a sensitive personal attribute than those obtained using a direct question.


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