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Kylie Gorney; Mark D. Reckase – Journal of Educational Measurement, 2025
In computerized adaptive testing, item exposure control methods are often used to provide a more balanced usage of the item pool. Many of the most popular methods, including the restricted method (Revuelta and Ponsoda), use a single maximum exposure rate to limit the proportion of times that each item is administered. However, Barrada et al.…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
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Han, Suhwa; Kang, Hyeon-Ah – Journal of Educational Measurement, 2023
The study presents multivariate sequential monitoring procedures for examining test-taking behaviors online. The procedures monitor examinee's responses and response times and signal aberrancy as soon as significant change is identifieddetected in the test-taking behavior. The study in particular proposes three schemes to track different…
Descriptors: Test Wiseness, Student Behavior, Item Response Theory, Computer Assisted Testing
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Lim, Hwanggyu; Choe, Edison M. – Journal of Educational Measurement, 2023
The residual differential item functioning (RDIF) detection framework was developed recently under a linear testing context. To explore the potential application of this framework to computerized adaptive testing (CAT), the present study investigated the utility of the RDIF[subscript R] statistic both as an index for detecting uniform DIF of…
Descriptors: Test Items, Computer Assisted Testing, Item Response Theory, Adaptive Testing
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Casabianca, Jodi M.; Donoghue, John R.; Shin, Hyo Jeong; Chao, Szu-Fu; Choi, Ikkyu – Journal of Educational Measurement, 2023
Using item-response theory to model rater effects provides an alternative solution for rater monitoring and diagnosis, compared to using standard performance metrics. In order to fit such models, the ratings data must be sufficiently connected in order to estimate rater effects. Due to popular rating designs used in large-scale testing scenarios,…
Descriptors: Item Response Theory, Alternative Assessment, Evaluators, Research Problems
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Xu, Lingling; Wang, Shiyu; Cai, Yan; Tu, Dongbo – Journal of Educational Measurement, 2021
Designing a multidimensional adaptive test (M-MST) based on a multidimensional item response theory (MIRT) model is critical to make full use of the advantages of both MST and MIRT in implementing multidimensional assessments. This study proposed two types of automated test assembly (ATA) algorithms and one set of routing rules that can facilitate…
Descriptors: Item Response Theory, Adaptive Testing, Automation, Test Construction
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Wyse, Adam E.; McBride, James R. – Journal of Educational Measurement, 2021
A key consideration when giving any computerized adaptive test (CAT) is how much adaptation is present when the test is used in practice. This study introduces a new framework to measure the amount of adaptation of Rasch-based CATs based on looking at the differences between the selected item locations (Rasch item difficulty parameters) of the…
Descriptors: Item Response Theory, Computer Assisted Testing, Adaptive Testing, Test Items
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Bergner, Yoav; Choi, Ikkyu; Castellano, Katherine E. – Journal of Educational Measurement, 2019
Allowance for multiple chances to answer constructed response questions is a prevalent feature in computer-based homework and exams. We consider the use of item response theory in the estimation of item characteristics and student ability when multiple attempts are allowed but no explicit penalty is deducted for extra tries. This is common…
Descriptors: Models, Item Response Theory, Homework, Computer Assisted Instruction
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Joo, Seang-Hwane; Lee, Philseok; Stark, Stephen – Journal of Educational Measurement, 2018
This research derived information functions and proposed new scalar information indices to examine the quality of multidimensional forced choice (MFC) items based on the RANK model. We also explored how GGUM-RANK information, latent trait recovery, and reliability varied across three MFC formats: pairs (two response alternatives), triplets (three…
Descriptors: Item Response Theory, Models, Item Analysis, Reliability
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Albano, Anthony D.; Cai, Liuhan; Lease, Erin M.; McConnell, Scott R. – Journal of Educational Measurement, 2019
Studies have shown that item difficulty can vary significantly based on the context of an item within a test form. In particular, item position may be associated with practice and fatigue effects that influence item parameter estimation. The purpose of this research was to examine the relevance of item position specifically for assessments used in…
Descriptors: Test Items, Computer Assisted Testing, Item Analysis, Difficulty Level
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Wang, Chun; Zheng, Chanjin; Chang, Hua-Hua – Journal of Educational Measurement, 2014
Computerized adaptive testing offers the possibility of gaining information on both the overall ability and cognitive profile in a single assessment administration. Some algorithms aiming for these dual purposes have been proposed, including the shadow test approach, the dual information method (DIM), and the constraint weighted method. The…
Descriptors: Item Response Theory, Adaptive Testing, Computer Assisted Testing, Cognitive Ability
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Veldkamp, Bernard P. – Journal of Educational Measurement, 2016
Many standardized tests are now administered via computer rather than paper-and-pencil format. The computer-based delivery mode brings with it certain advantages. One advantage is the ability to adapt the difficulty level of the test to the ability level of the test taker in what has been termed computerized adaptive testing (CAT). A second…
Descriptors: Computer Assisted Testing, Reaction Time, Standardized Tests, Difficulty Level
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Sinharay, Sandip; Wan, Ping; Choi, Seung W.; Kim, Dong-In – Journal of Educational Measurement, 2015
With an increase in the number of online tests, the number of interruptions during testing due to unexpected technical issues seems to be on the rise. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees' scores. Researchers such as…
Descriptors: Computer Assisted Testing, Testing Problems, Scores, Statistical Analysis
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Sinharay, Sandip; Wan, Ping; Whitaker, Mike; Kim, Dong-In; Zhang, Litong; Choi, Seung W. – Journal of Educational Measurement, 2014
With an increase in the number of online tests, interruptions during testing due to unexpected technical issues seem unavoidable. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees' scores. There is a lack of research on this…
Descriptors: Computer Assisted Testing, Testing Problems, Scores, Regression (Statistics)
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Zhang, Jinming; Li, Jie – Journal of Educational Measurement, 2016
An IRT-based sequential procedure is developed to monitor items for enhancing test security. The procedure uses a series of statistical hypothesis tests to examine whether the statistical characteristics of each item under inspection have changed significantly during CAT administration. This procedure is compared with a previously developed…
Descriptors: Computer Assisted Testing, Test Items, Difficulty Level, Item Response Theory
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Li, Feiming; Cohen, Allan; Shen, Linjun – Journal of Educational Measurement, 2012
Computer-based tests (CBTs) often use random ordering of items in order to minimize item exposure and reduce the potential for answer copying. Little research has been done, however, to examine item position effects for these tests. In this study, different versions of a Rasch model and different response time models were examined and applied to…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Models
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