Year 2021, Volume 8 , Issue 1, Pages 156 - 166 2021-03-15

Defining Cut Point for Kullback-Leibler Divergence to Detect Answer Copying

Arzu UÇAR [1] , Celal DOĞAN [2]


Distance learning has become a popular phenomenon across the world during the COVID-19 pandemic. This led to answer copying behavior among individuals. The cut point of the Kullback-Leibler Divergence (KL) method, one of the copy detecting methods, was calculated using the Youden Index, Cost-Benefit, and Min Score p-value approaches. Using the cut point obtained, individuals were classified as a copier or not, and the KL method was examined for cases where the determination power of the KL method was 1000, and 3000 sample size, 40 test length, copiers' rate was 0.05 and 0.15, and copying percentage was 0.1, 0.3 and 0.6. As a result, when the cut point was obtained with the Min Score p-value approach, one of the cutting methods approaches, it was seen that the power of the KL index to detect copier was high under all conditions. Similarly, under all conditions, it was observed that the second method, in which the detection power of the KL method was high, was the Youden Index approach. When the sample size and the copiers' rate increased, it was observed that the power of the KL method decreased when the cut point with the cost-benefit approach was used.
Copy detection, Cut point, ROC analysis, Answer copying, Kullback-Leibler divergence
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Primary Language en
Subjects Education, Scientific Disciplines
Published Date March
Journal Section Articles
Authors

Orcid: 0000-0002-0099-1348
Author: Arzu UÇAR (Primary Author)
Institution: HAKKARI UNIVERSITY
Country: Turkey


Orcid: 0000-0003-0683-1334
Author: Celal DOĞAN
Institution: ANKARA UNIVERSITY
Country: Turkey


Dates

Publication Date : March 15, 2021

APA Uçar, A , Doğan, C . (2021). Defining Cut Point for Kullback-Leibler Divergence to Detect Answer Copying . International Journal of Assessment Tools in Education , 8 (1) , 156-166 . DOI: 10.21449/ijate.864078