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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
Kaiwen Man – Educational and Psychological Measurement, 2024
In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…
Descriptors: Prior Learning, Testing, Behavior, Artificial Intelligence
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
He, Qingping; Meadows, Michelle; Black, Beth – Research Papers in Education, 2022
A potential negative consequence of high-stakes testing is inappropriate test behaviour involving individuals and/or institutions. Inappropriate test behaviour and test collusion can result in aberrant response patterns and anomalous test scores and invalidate the intended interpretation and use of test results. A variety of statistical techniques…
Descriptors: Statistical Analysis, High Stakes Tests, Scores, Response Style (Tests)
Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…
Descriptors: Cheating, Item Response Theory, Reaction Time, Eye Movements
Zopluoglu, Cengiz – International Journal of Assessment Tools in Education, 2019
Unusual response similarity among test takers may occur in testing data and be an indicator of potential test fraud (e.g., examinees copy responses from other examinees, send text messages or pre-arranged signals among themselves for the correct response, item pre-knowledge). One index to measure the degree of similarity between two response…
Descriptors: Item Response Theory, Computation, Cheating, Measurement Techniques
Mor, Ezgi; Kula-Kartal, Seval – International Journal of Assessment Tools in Education, 2022
The dimensionality is one of the most investigated concepts in the psychological assessment, and there are many ways to determine the dimensionality of a measured construct. The Automated Item Selection Procedure (AISP) and the DETECT are non-parametric methods aiming to determine the factorial structure of a data set. In the current study,…
Descriptors: Psychological Evaluation, Nonparametric Statistics, Test Items, Item Analysis
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
Zopluoglu, Cengiz – Educational and Psychological Measurement, 2019
Researchers frequently use machine-learning methods in many fields. In the area of detecting fraud in testing, there have been relatively few studies that have used these methods to identify potential testing fraud. In this study, a technical review of a recently developed state-of-the-art algorithm, Extreme Gradient Boosting (XGBoost), is…
Descriptors: Identification, Test Items, Deception, Cheating
Gorney, Kylie; Wollack, James A. – Practical Assessment, Research & Evaluation, 2022
Unlike the traditional multiple-choice (MC) format, the discrete-option multiple-choice (DOMC) format does not necessarily reveal all answer options to an examinee. The purpose of this study was to determine whether the reduced exposure of item content affects test security. We conducted an experiment in which participants were allowed to view…
Descriptors: Test Items, Test Format, Multiple Choice Tests, Item Analysis
Dimitrov, Dimiter M.; Atanasov, Dimitar V.; Luo, Yong – Measurement: Interdisciplinary Research and Perspectives, 2020
This study examines and compares four person-fit statistics (PFSs) in the framework of the "D"- scoring method (DSM): (a) van der Flier's "U3" statistic; (b) "Ud" statistic, as a modification of "U3" under the DSM; (c) "Zd" statistic, as a modification of the "Z3 (l[subscript z])"…
Descriptors: Goodness of Fit, Item Analysis, Item Response Theory, Scoring
Wang, Chun; Xu, Gongjun; Shang, Zhuoran; Kuncel, Nathan – Journal of Educational and Behavioral Statistics, 2018
The modern web-based technology greatly popularizes computer-administered testing, also known as online testing. When these online tests are administered continuously within a certain "testing window," many items are likely to be exposed and compromised, posing a type of test security concern. In addition, if the testing time is limited,…
Descriptors: Computer Assisted Testing, Cheating, Guessing (Tests), Item Response Theory
Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2017
An increasing concern of producers of educational assessments is fraudulent behavior during the assessment (van der Linden, 2009). Benefiting from item preknowledge (e.g., Eckerly, 2017; McLeod, Lewis, & Thissen, 2003) is one type of fraudulent behavior. This article suggests two new test statistics for detecting individuals who may have…
Descriptors: Test Items, Cheating, Testing Problems, Identification
Ossai, Moses Chukwugi; Ethe, Nathaniel; Edougha, Dennis E. – Education Quarterly Reviews, 2020
The research focused on development, validation and standardization of a diagnostic instrument called Tertiary Examination Behaviour Inventory (TEBI) for determining the tendency of students in tertiary institutions to participate in academic cheating. Anchored on the Modified Theory of Planned Behaviour (MTPB) and Item Response Theory (IRT), the…
Descriptors: Cheating, Validity, Diagnostic Tests, College Students
Vista, Alvin – European Journal of Educational Research, 2019
Cheating detection is an important issue in standardized testing, especially in large-scale settings. Statistical approaches are often computationally intensive and require specialised software to conduct. We present a two-stage approach that quickly filters suspected groups using statistical testing on an IRT-based answer-copying index. We also…
Descriptors: Cheating, Identification, Computer Software, Standardized Tests