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Lang, Joseph B. – Journal of Educational and Behavioral Statistics, 2023
This article is concerned with the statistical detection of copying on multiple-choice exams. As an alternative to existing permutation- and model-based copy-detection approaches, a simple randomization p-value (RP) test is proposed. The RP test, which is based on an intuitive match-score statistic, makes no assumptions about the distribution of…
Descriptors: Identification, Cheating, Multiple Choice Tests, Item Response Theory
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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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Alessio, Helaine M.; Malay, Nancy; Maurer, Karsten; Bailer, A. John; Rubin, Beth – International Review of Research in Open and Distributed Learning, 2018
Traditional and online university courses share expectations for quality content and rigor. Student and faculty concerns about compromised academic integrity and actual instances of academic dishonesty in assessments, especially with online testing, are increasingly troublesome. Recent research suggests that in the absence of proctoring, the time…
Descriptors: Supervision, Majors (Students), Computer Assisted Testing, Scores
Steinkamp, Susan Christa – ProQuest LLC, 2017
For test scores that rely on the accurate estimation of ability via an IRT model, their use and interpretation is dependent upon the assumption that the IRT model fits the data. Examinees who do not put forth full effort in answering test questions, have prior knowledge of test content, or do not approach a test with the intent of answering…
Descriptors: Test Items, Item Response Theory, Scores, Test Wiseness
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Guo, Jing; Tay, Louis; Drasgow, Fritz – International Journal of Testing, 2009
Test compromise is a concern in cognitive ability testing because such tests are widely used in employee selection and administered on a continuous basis. In this study, the resistance of cognitive tests, deployed in different test systems, to small-scale cheating conspiracies, was evaluated regarding the accuracy of ability estimation.…
Descriptors: Cheating, Cognitive Tests, Adaptive Testing, Computer Assisted Testing
Bay, Luz – 1995
An index is proposed to detect cheating on multiple-choice examinations, and its use is evaluated through simulations. The proposed index is based on the compound binomial distribution. In total, 360 simulated data sets reflecting 12 different cheating (copying) situations were obtained and used for the study of the sensitivity of the index in…
Descriptors: Cheating, Class Size, Identification, Multiple Choice Tests
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Roberts, Dennis M. – Journal of Educational Measurement, 1987
This study examines a score-difference model for the detection of cheating based on the difference between two scores for an examinee: one based on the appropriate scoring key and another based on an alternative, inappropriate key. It argues that the score-difference method could falsely accuse students as cheaters. (Author/JAZ)
Descriptors: Answer Keys, Cheating, Mathematical Models, Multiple Choice Tests