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Beyza Aksu Dunya; Stefanie Wind – International Journal of Testing, 2025
We explored the practicality of relatively small item pools in the context of low-stakes Computer-Adaptive Testing (CAT), such as CAT procedures that might be used for quick diagnostic or screening exams. We used a basic CAT algorithm without content balancing and exposure control restrictions to reflect low stakes testing scenarios. We examined…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Achievement
Beyza Aksu Dünya; Stefanie A. Wind; Mehmet Can Demir – SAGE Open, 2025
The purpose of this study was to generate an item bank for assessing faculty members' assessment literacy and to examine the applicability and feasibility of a Computerized Adaptive Test (CAT) approach to monitor assessment literacy among faculty members. In developing this assessment using a sequential mixed-methods research design, our goal was…
Descriptors: Assessment Literacy, Item Banks, College Faculty, Adaptive Testing
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
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
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
Ersen, Rabia Karatoprak; Lee, Won-Chan – Journal of Educational Measurement, 2023
The purpose of this study was to compare calibration and linking methods for placing pretest item parameter estimates on the item pool scale in a 1-3 computerized multistage adaptive testing design in terms of item parameter recovery. Two models were used: embedded-section, in which pretest items were administered within a separate module, and…
Descriptors: Pretesting, Test Items, Computer Assisted Testing, Adaptive Testing
Development of a High-Accuracy and Effective Online Calibration Method in CD-CAT Based on Gini Index
Tan, Qingrong; Cai, Yan; Luo, Fen; Tu, Dongbo – Journal of Educational and Behavioral Statistics, 2023
To improve the calibration accuracy and calibration efficiency of cognitive diagnostic computerized adaptive testing (CD-CAT) for new items and, ultimately, contribute to the widespread application of CD-CAT in practice, the current article proposed a Gini-based online calibration method that can simultaneously calibrate the Q-matrix and item…
Descriptors: Cognitive Tests, Computer Assisted Testing, Adaptive Testing, Accuracy
Xiuxiu Tang; Yi Zheng; Tong Wu; Kit-Tai Hau; Hua-Hua Chang – Journal of Educational Measurement, 2025
Multistage adaptive testing (MST) has been recently adopted for international large-scale assessments such as Programme for International Student Assessment (PISA). MST offers improved measurement efficiency over traditional nonadaptive tests and improved practical convenience over single-item-adaptive computerized adaptive testing (CAT). As a…
Descriptors: Reaction Time, Test Items, Achievement Tests, Foreign Countries
Stefanie A. Wind; Beyza Aksu-Dunya – Applied Measurement in Education, 2024
Careless responding is a pervasive concern in research using affective surveys. Although researchers have considered various methods for identifying careless responses, studies are limited that consider the utility of these methods in the context of computer adaptive testing (CAT) for affective scales. Using a simulation study informed by recent…
Descriptors: Response Style (Tests), Computer Assisted Testing, Adaptive Testing, Affective Measures
Kreitchmann, Rodrigo S.; Sorrel, Miguel A.; Abad, Francisco J. – Educational and Psychological Measurement, 2023
Multidimensional forced-choice (FC) questionnaires have been consistently found to reduce the effects of socially desirable responding and faking in noncognitive assessments. Although FC has been considered problematic for providing ipsative scores under the classical test theory, item response theory (IRT) models enable the estimation of…
Descriptors: Measurement Techniques, Questionnaires, Social Desirability, Adaptive Testing
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
Hanif Akhtar – International Society for Technology, Education, and Science, 2023
For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…
Descriptors: Success, Probability, Computer Assisted Testing, Adaptive Testing
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
The Effect of Item Pools of Different Strengths on the Test Results of Computerized-Adaptive Testing
Kezer, Fatih – International Journal of Assessment Tools in Education, 2021
Item response theory provides various important advantages for exams carried out or to be carried out digitally. For computerized adaptive tests to be able to make valid and reliable predictions supported by IRT, good quality item pools should be used. This study examines how adaptive test applications vary in item pools which consist of items…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Item Response Theory
Yang, Lihong; Reckase, Mark D. – Educational and Psychological Measurement, 2020
The present study extended the "p"-optimality method to the multistage computerized adaptive test (MST) context in developing optimal item pools to support different MST panel designs under different test configurations. Using the Rasch model, simulated optimal item pools were generated with and without practical constraints of exposure…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Item Response Theory

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