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Grochowalski, Joseph H.; Hendrickson, Amy – Journal of Educational Measurement, 2023
Test takers wishing to gain an unfair advantage often share answers with other test takers, either sharing all answers (a full key) or some (a partial key). Detecting key sharing during a tight testing window requires an efficient, easily interpretable, and rich form of analysis that is descriptive and inferential. We introduce a detection method…
Descriptors: Identification, Cooperative Learning, Cheating, Statistical Analysis
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Pan, Yiqin; Wollack, James A. – Journal of Educational Measurement, 2021
As technologies have been improved, item preknowledge has become a common concern in the test security area. The present study proposes an unsupervised-learning-based approach to detect compromised items. The unsupervised-learning-based compromised item detection approach contains three steps: (1) classify responses of each examinee as either…
Descriptors: Test Items, Cheating, Artificial Intelligence, Identification
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Yang Jiang; Mo Zhang; Jiangang Hao; Paul Deane; Chen Li – Journal of Educational Measurement, 2024
The emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…
Descriptors: Integrity, Artificial Intelligence, Technology Uses in Education, Ethics
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Liu, Jinghua; Becker, Kirk – Journal of Educational Measurement, 2022
For any testing programs that administer multiple forms across multiple years, maintaining score comparability via equating is essential. With continuous testing and high-stakes results, especially with less secure online administrations, testing programs must consider the potential for cheating on their exams. This study used empirical and…
Descriptors: Cheating, Item Response Theory, Scores, High Stakes Tests
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Man, Kaiwen; Harring, Jeffrey R.; Sinharay, Sandip – Journal of Educational Measurement, 2019
Data mining methods have drawn considerable attention across diverse scientific fields. However, few applications could be found in the areas of psychological and educational measurement, and particularly pertinent to this article, in test security research. In this study, various data mining methods for detecting cheating behaviors on large-scale…
Descriptors: Information Retrieval, Data Analysis, Identification, Tests
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Belov, Dmitry I. – Journal of Educational Measurement, 2013
The development of statistical methods for detecting test collusion is a new research direction in the area of test security. Test collusion may be described as large-scale sharing of test materials, including answers to test items. Current methods of detecting test collusion are based on statistics also used in answer-copying detection.…
Descriptors: Cheating, Computer Assisted Testing, Adaptive Testing, Statistical Analysis
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van der Ark, L. Andries; Emons, Wilco H. M.; Sijtsma, Klaas – Journal of Educational Measurement, 2008
Two types of answer-copying statistics for detecting copiers in small-scale examinations are proposed. One statistic identifies the "copier-source" pair, and the other in addition suggests who is copier and who is source. Both types of statistics can be used when the examination has alternate test forms. A simulation study shows that the…
Descriptors: Cheating, Statistics, Test Format, Measures (Individuals)
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Frary, Robert B. – Journal of Educational Measurement, 2000
Reviews a book that provides useful information for those who must deal with the problem of cheating on tests. The book explains ethical and practical issues associated with cheating, the frequency with which it occurs, details of cheating methods, and detection of cheating. (SLD)
Descriptors: Cheating, Ethics, Identification, Prevention
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Sotaridona, Leonardo S.; Meijer, Rob R. – Journal of Educational Measurement, 2002
Studied the statistical properties of the K-index (P. Holland, 1996) that can be used to detect copying behavior on a test through a simulation study of the use of the K-statistic with small, medium, and large datasets. Also compared the Type I error rate and detection rate of this index with those of the copying index (J. Wollack, 1997).…
Descriptors: Cheating, Identification, Plagiarism, Sample Size
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Sotaridona, Leonardo S.; Meijer, Rob R. – Journal of Educational Measurement, 2003
Proposed two new indices to detect answer copying on a multiple choice test and conducted a simulation study to investigate the usefulness of both indexes. Discusses conditions under which the proposed indexes can be useful. (SLD)
Descriptors: Cheating, Multiple Choice Tests, Simulation, Testing Problems
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Stocking, Martha L.; Ward, William C.; Potenza, Maria T. – Journal of Educational Measurement, 1998
Explored, using simulations, the use of disclosed items on continuous testing conditions under a worse-case scenario that assumes that disclosed items are always answered correctly. Some item pool and test designs were identified in which the use of disclosed items produces effects on test scores that may be viewed as negligible. (Author/MAK)
Descriptors: Adaptive Testing, Cheating, Computer Assisted Testing, Item Banks
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van der Linden, Wim J.; Sotaridona, Leonardo – Journal of Educational Measurement, 2004
A statistical test for the detection of answer copying on multiple-choice tests is presented. The test is based on the idea that the answers of examinees to test items may be the result of three possible processes: (1) knowing, (2) guessing, and (3) copying, but that examinees who do not have access to the answers of other examinees can arrive at…
Descriptors: Multiple Choice Tests, Test Items, Hypothesis Testing, Statistical Distributions
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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