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Sunbul, Onder; Yormaz, Seha – International Journal of Evaluation and Research in Education, 2018
In this study Type I Error and the power rates of omega (?) and GBT (generalized binomial test) indices were investigated for several nominal alpha levels and for 40 and 80-item test lengths with 10,000-examinee sample size under several test level restrictions. As a result, Type I error rates of both indices were found to be below the acceptable…
Descriptors: Difficulty Level, Cheating, Duplication, Test Length
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Yormaz, Seha; Sünbül, Önder – Educational Sciences: Theory and Practice, 2017
This study aims to determine the Type I error rates and power of S[subscript 1] , S[subscript 2] indices and kappa statistic at detecting copying on multiple-choice tests under various conditions. It also aims to determine how copying groups are created in order to calculate how kappa statistics affect Type I error rates and power. In this study,…
Descriptors: Statistical Analysis, Cheating, Multiple Choice Tests, Sample Size
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Romero, Mauricio; Riascos, Álvaro; Jara, Diego – Journal of Educational and Behavioral Statistics, 2015
Multiple-choice exams are frequently used as an efficient and objective method to assess learning, but they are more vulnerable to answer copying than tests based on open questions. Several statistical tests (known as indices in the literature) have been proposed to detect cheating; however, to the best of our knowledge, they all lack mathematical…
Descriptors: Cheating, Multiple Choice Tests, Statistical Analysis, Models
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Maeda, Hotaka; Zhang, Bo – International Journal of Testing, 2017
The omega (?) statistic is reputed to be one of the best indices for detecting answer copying on multiple choice tests, but its performance relies on the accurate estimation of copier ability, which is challenging because responses from the copiers may have been contaminated. We propose an algorithm that aims to identify and delete the suspected…
Descriptors: Cheating, Test Items, Mathematics, Statistics