Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 7 |
Since 2016 (last 10 years) | 15 |
Since 2006 (last 20 years) | 19 |
Descriptor
Cheating | 22 |
Identification | 22 |
Statistical Analysis | 22 |
Test Items | 7 |
Item Response Theory | 6 |
Probability | 6 |
Multiple Choice Tests | 5 |
Bayesian Statistics | 3 |
Computer Assisted Testing | 3 |
Scores | 3 |
Testing Problems | 3 |
More ▼ |
Source
Author
Sinharay, Sandip | 7 |
Johnson, Matthew S. | 4 |
Liu, Yang | 2 |
Wang, Xi | 2 |
Becker, Kirk | 1 |
Belov, Dmitry I. | 1 |
Black, Beth | 1 |
Davenport, Ernest C., Jr. | 1 |
Dogan, Celal Deha | 1 |
Dunlap, Jody | 1 |
Dwyer, David J. | 1 |
More ▼ |
Publication Type
Journal Articles | 14 |
Reports - Research | 14 |
Reports - Descriptive | 3 |
Reports - Evaluative | 3 |
Dissertations/Theses -… | 1 |
Information Analyses | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Higher Education | 2 |
Postsecondary Education | 2 |
Elementary Education | 1 |
Grade 5 | 1 |
Intermediate Grades | 1 |
Middle Schools | 1 |
Two Year Colleges | 1 |
Audience
Location
California | 1 |
Laws, Policies, & Programs
Higher Education Act 1965 | 1 |
Assessments and Surveys
Law School Admission Test | 1 |
What Works Clearinghouse Rating
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
Becker, Kirk; Meng, Huijuan – Journal of Applied Testing Technology, 2022
The rise of online proctoring potentially provides more opportunities for item harvesting and consequent brain dumping and shared "study guides" based on stolen content. This has increased the need for rapid approaches for evaluating and acting on suspicious test responses in every delivery modality. Both hiring proxy test takers and…
Descriptors: Identification, Cheating, Computer Assisted Testing, Observation
The Use of Theory of Linear Mixed-Effects Models to Detect Fraudulent Erasures at an Aggregate Level
Peng, Luyao; Sinharay, Sandip – Educational and Psychological Measurement, 2022
Wollack et al. (2015) suggested the erasure detection index (EDI) for detecting fraudulent erasures for individual examinees. Wollack and Eckerly (2017) and Sinharay (2018) extended the index of Wollack et al. (2015) to suggest three EDIs for detecting fraudulent erasures at the aggregate or group level. This article follows up on the research of…
Descriptors: Cheating, Identification, Statistical Analysis, Testing
Sinharay, Sandip; Johnson, Matthew S. – Journal of Educational and Behavioral Statistics, 2021
Score differencing is one of the six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…
Descriptors: Probability, Bayesian Statistics, Cheating, Statistical Analysis
Ucar, Arzu; Dogan, Celal Deha – International Journal of Assessment Tools in Education, 2021
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…
Descriptors: Cheating, Identification, Cutting Scores, Statistical Analysis
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2021
Score differencing is one of six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…
Descriptors: Probability, Bayesian Statistics, Cheating, Statistical Analysis
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)
Wang, Xi; Liu, Yang – Journal of Educational and Behavioral Statistics, 2020
In continuous testing programs, some items are repeatedly used across test administrations, and statistical methods are often used to evaluate whether items become compromised due to examinees' preknowledge. In this study, we proposed a residual method to detect compromised items when a test can be partitioned into two subsets of items: secure…
Descriptors: Test Items, Information Security, Error of Measurement, Cheating
Wang, Xi; Liu, Yang; Robin, Frederic; Guo, Hongwen – International Journal of Testing, 2019
In an on-demand testing program, some items are repeatedly used across test administrations. This poses a risk to test security. In this study, we considered a scenario wherein a test was divided into two subsets: one consisting of secure items and the other consisting of possibly compromised items. In a simulation study of multistage adaptive…
Descriptors: Identification, Methods, Test Items, Cheating
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2019
According to Wollack and Schoenig (2018), score differencing is one of six types of statistical methods used to detect test fraud. In this paper, we suggested the use of Bayes factors (e.g., Kass & Raftery, 1995) for score differencing. A simulation study shows that the suggested approach performs slightly better than an existing frequentist…
Descriptors: Cheating, Deception, Statistical Analysis, Bayesian Statistics
Sinharay, Sandip – Grantee Submission, 2019
Benefiting from item preknowledge (e.g., McLeod, Lewis, & Thissen, 2003) is a major type of fraudulent behavior during educational assessments. This paper suggests a new statistic that can be used for detecting the examinees who may have benefitted from item preknowledge using their response times. The statistic quantifies the difference in…
Descriptors: Test Items, Cheating, Reaction Time, Identification
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2019
According to Wollack and Schoenig (2018), benefitting from item preknowledge is one of the three broad types of test fraud that occur in educational assessments. We use tools from constrained statistical inference to suggest a new statistic that is based on item scores and response times and can be used to detect the examinees who may have…
Descriptors: Scores, Test Items, Reaction Time, Cheating
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
Haberman, Shelby J.; Lee, Yi-Hsuan – ETS Research Report Series, 2017
In investigations of unusual testing behavior, a common question is whether a specific pattern of responses occurs unusually often within a group of examinees. In many current tests, modern communication techniques can permit quite large numbers of examinees to share keys, or common response patterns, to the entire test. To address this issue,…
Descriptors: Student Evaluation, Testing, Item Response Theory, Maximum Likelihood Statistics
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
Previous Page | Next Page ยป
Pages: 1 | 2