NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
What Works Clearinghouse Rating
Showing 1 to 15 of 89 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Hwanggyu Lim; Kyung T. Han – Educational Measurement: Issues and Practice, 2024
Computerized adaptive testing (CAT) has gained deserved popularity in the administration of educational and professional assessments, but continues to face test security challenges. To ensure sustained quality assurance and testing integrity, it is imperative to establish and maintain multiple stable item pools that are consistent in terms of…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
Peer reviewed Peer reviewed
Direct linkDirect link
Pan, Yiqin; Wollack, James A. – Educational Measurement: Issues and Practice, 2023
Pan and Wollack (PW) proposed a machine learning method to detect compromised items. We extend the work of PW to an approach detecting compromised items and examinees with item preknowledge simultaneously and draw on ideas in ensemble learning to relax several limitations in the work of PW. The suggested approach also provides a confidence score,…
Descriptors: Artificial Intelligence, Prior Learning, Item Analysis, Test Content
Peer reviewed Peer reviewed
Direct linkDirect link
Belzak, William C. M. – Educational Measurement: Issues and Practice, 2023
Test developers and psychometricians have historically examined measurement bias and differential item functioning (DIF) across a single categorical variable (e.g., gender), independently of other variables (e.g., race, age, etc.). This is problematic when more complex forms of measurement bias may adversely affect test responses and, ultimately,…
Descriptors: Test Bias, High Stakes Tests, Artificial Intelligence, Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
Berenbon, Rebecca F.; McHugh, Bridget C. – Educational Measurement: Issues and Practice, 2023
To assemble a high-quality test, psychometricians rely on subject matter experts (SMEs) to write high-quality items. However, SMEs are not typically given the opportunity to provide input on which content standards are most suitable for multiple-choice questions (MCQs). In the present study, we explored the relationship between perceived MCQ…
Descriptors: Test Items, Multiple Choice Tests, Standards, Difficulty Level
Peer reviewed Peer reviewed
Direct linkDirect link
Pan, Yiqin; Livne, Oren; Wollack, James A.; Sinharay, Sandip – Educational Measurement: Issues and Practice, 2023
In computerized adaptive testing, overexposure of items in the bank is a serious problem and might result in item compromise. We develop an item selection algorithm that utilizes the entire bank well and reduces the overexposure of items. The algorithm is based on collaborative filtering and selects an item in two stages. In the first stage, a set…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
Peer reviewed Peer reviewed
Direct linkDirect link
Zhang, Susu; Li, Anqi; Wang, Shiyu – Educational Measurement: Issues and Practice, 2023
In computer-based tests allowing revision and reviews, examinees' sequence of visits and answer changes to questions can be recorded. The variable-length revision log data introduce new complexities to the collected data but, at the same time, provide additional information on examinees' test-taking behavior, which can inform test development and…
Descriptors: Computer Assisted Testing, Test Construction, Test Wiseness, Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
Sinharay, Sandip – Educational Measurement: Issues and Practice, 2022
Administrative problems such as computer malfunction and power outage occasionally lead to missing item scores, and hence to incomplete data, on credentialing tests such as the United States Medical Licensing examination. Feinberg compared four approaches for reporting pass-fail decisions to the examinees with incomplete data on credentialing…
Descriptors: Testing Problems, High Stakes Tests, Credentials, Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
Lewis, Jennifer; Lim, Hwanggyu; Padellaro, Frank; Sireci, Stephen G.; Zenisky, April L. – Educational Measurement: Issues and Practice, 2022
Setting cut scores on (MSTs) is difficult, particularly when the test spans several grade levels, and the selection of items from MST panels must reflect the operational test specifications. In this study, we describe, illustrate, and evaluate three methods for mapping panelists' Angoff ratings into cut scores on the scale underlying an MST. The…
Descriptors: Cutting Scores, Adaptive Testing, Test Items, Item Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Dongmei; Kapoor, Shalini – Educational Measurement: Issues and Practice, 2022
Population invariance is a desirable property of test equating which might not hold when significant changes occur in the test population, such as those brought about by the COVID-19 pandemic. This research aims to investigate whether equating functions are reasonably invariant when the test population is impacted by the pandemic. Based on…
Descriptors: Test Items, Equated Scores, COVID-19, Pandemics
Peer reviewed Peer reviewed
Direct linkDirect link
An, Lily Shiao; Ho, Andrew Dean; Davis, Laurie Laughlin – Educational Measurement: Issues and Practice, 2022
Technical documentation for educational tests focuses primarily on properties of individual scores at single points in time. Reliability, standard errors of measurement, item parameter estimates, fit statistics, and linking constants are standard technical features that external stakeholders use to evaluate items and individual scale scores.…
Descriptors: Documentation, Scores, Evaluation Methods, Longitudinal Studies
Peer reviewed Peer reviewed
Direct linkDirect link
Arikan, Serkan; Aybek, Eren Can – Educational Measurement: Issues and Practice, 2022
Many scholars compared various item discrimination indices in real or simulated data. Item discrimination indices, such as item-total correlation, item-rest correlation, and IRT item discrimination parameter, provide information about individual differences among all participants. However, there are tests that aim to select a very limited number…
Descriptors: Monte Carlo Methods, Item Analysis, Correlation, Individual Differences
Peer reviewed Peer reviewed
Direct linkDirect link
Student, Sanford R.; Gong, Brian – Educational Measurement: Issues and Practice, 2022
We address two persistent challenges in large-scale assessments of the Next Generation Science Standards: (a) the validity of score interpretations that target the standards broadly and (b) how to structure claims for assessments of this complex domain. The NGSS pose a particular challenge for specifying claims about students that evidence from…
Descriptors: Science Tests, Test Validity, Test Items, Test Construction
Peer reviewed Peer reviewed
Direct linkDirect link
Fu, Yanyan; Choe, Edison M.; Lim, Hwanggyu; Choi, Jaehwa – Educational Measurement: Issues and Practice, 2022
This case study applied the "weak theory" of Automatic Item Generation (AIG) to generate isomorphic item instances (i.e., unique but psychometrically equivalent items) for a large-scale assessment. Three representative instances were selected from each item template (i.e., model) and pilot-tested. In addition, a new analytical framework,…
Descriptors: Test Items, Measurement, Psychometrics, Test Construction
Peer reviewed Peer reviewed
Direct linkDirect link
Steedle, Jeffrey T.; Cho, Young Woo; Wang, Shichao; Arthur, Ann M.; Li, Dongmei – Educational Measurement: Issues and Practice, 2022
As testing programs transition from paper to online testing, they must study mode comparability to support the exchangeability of scores from different testing modes. To that end, a series of three mode comparability studies was conducted during the 2019-2020 academic year with examinees randomly assigned to take the ACT college admissions exam on…
Descriptors: College Entrance Examinations, Computer Assisted Testing, Scores, Test Format
Peer reviewed Peer reviewed
Direct linkDirect link
Kim, Sooyeon; Walker, Michael E. – Educational Measurement: Issues and Practice, 2022
Test equating requires collecting data to link the scores from different forms of a test. Problems arise when equating samples are not equivalent and the test forms to be linked share no common items by which to measure or adjust for the group nonequivalence. Using data from five operational test forms, we created five pairs of research forms for…
Descriptors: Ability, Tests, Equated Scores, Testing Problems
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4  |  5  |  6