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Harold Doran; Testsuhiro Yamada; Ted Diaz; Emre Gonulates; Vanessa Culver – Journal of Educational Measurement, 2025
Computer adaptive testing (CAT) is an increasingly common mode of test administration offering improved test security, better measurement precision, and the potential for shorter testing experiences. This article presents a new item selection algorithm based on a generalized objective function to support multiple types of testing conditions and…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
Jyun-Hong Chen; Hsiu-Yi Chao – Journal of Educational and Behavioral Statistics, 2024
To solve the attenuation paradox in computerized adaptive testing (CAT), this study proposes an item selection method, the integer programming approach based on real-time test data (IPRD), to improve test efficiency. The IPRD method turns information regarding the ability distribution of the population from real-time test data into feasible test…
Descriptors: Data Use, Computer Assisted Testing, Adaptive Testing, Design
Jing Ma – ProQuest LLC, 2024
This study investigated the impact of scoring polytomous items later on measurement precision, classification accuracy, and test security in mixed-format adaptive testing. Utilizing the shadow test approach, a simulation study was conducted across various test designs, lengths, number and location of polytomous item. Results showed that while…
Descriptors: Scoring, Adaptive Testing, Test Items, Classification
Andreas Frey; Christoph König; Aron Fink – Journal of Educational Measurement, 2025
The highly adaptive testing (HAT) design is introduced as an alternative test design for the Programme for International Student Assessment (PISA). The principle of HAT is to be as adaptive as possible when selecting items while accounting for PISA's nonstatistical constraints and addressing issues concerning PISA such as item position effects.…
Descriptors: Adaptive Testing, Test Construction, Alternative Assessment, Achievement Tests
Hyo Jeong Shin; Christoph König; Frederic Robin; Andreas Frey; Kentaro Yamamoto – Journal of Educational Measurement, 2025
Many international large-scale assessments (ILSAs) have switched to multistage adaptive testing (MST) designs to improve measurement efficiency in measuring the skills of the heterogeneous populations around the world. In this context, previous literature has reported the acceptable level of model parameter recovery under the MST designs when the…
Descriptors: Robustness (Statistics), Item Response Theory, Adaptive Testing, Test Construction
Montserrat Beatriz Valdivia Medinaceli – ProQuest LLC, 2023
My dissertation examines three current challenges of international large-scale assessments (ILSAs) associated with the transition from linear testing to an adaptive testing design. ILSAs are important for making comparisons among populations and informing countries about the quality of their educational systems. ILSA's results inform policymakers…
Descriptors: International Assessment, Achievement Tests, Adaptive Testing, Test Items
Umi Laili Yuhana; Eko Mulyanto Yuniarno; Wenny Rahayu; Eric Pardede – Education and Information Technologies, 2024
In an online learning environment, it is important to establish a suitable assessment approach that can be adapted on the fly to accommodate the varying learning paces of students. At the same time, it is essential that assessment criteria remain compliant with the expected learning outcomes of the relevant education standard which predominantly…
Descriptors: Adaptive Testing, Electronic Learning, Elementary School Students, Student Evaluation
Yiqin Pan – ProQuest LLC, 2022
Item preknowledge refers to the phenomenon in which some examinees have access to live items before taking a test. It is one of the most common and significant concerns within the testing industry. Thus, various statistical methods have been proposed to detect item preknowledge in computerized linear or adaptive testing. However, the success of…
Descriptors: Artificial Intelligence, Prior Learning, Test Items, Algorithms
Cai, Liuhan; Albano, Anthony D.; Roussos, Louis A. – Measurement: Interdisciplinary Research and Perspectives, 2021
Multistage testing (MST), an adaptive test delivery mode that involves algorithmic selection of predefined item modules rather than individual items, offers a practical alternative to linear and fully computerized adaptive testing. However, interactions across stages between item modules and examinee groups can lead to challenges in item…
Descriptors: Adaptive Testing, Test Items, Item Response Theory, Test Construction
Han, Kyung T.; Dimitrov, Dimiter M.; Al-Mashary, Faisal – Educational and Psychological Measurement, 2019
The "D"-scoring method for scoring and equating tests with binary items proposed by Dimitrov offers some of the advantages of item response theory, such as item-level difficulty information and score computation that reflects the item difficulties, while retaining the merits of classical test theory such as the simplicity of number…
Descriptors: Test Construction, Scoring, Test Items, Adaptive Testing
Chun Wang; Ping Chen; Shengyu Jiang – Journal of Educational Measurement, 2020
Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait [theta] estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence, questions remain as to how to…
Descriptors: Test Construction, Test Items, Adaptive Testing, Maximum Likelihood Statistics
Luo, Xiao; Wang, Xinrui – International Journal of Testing, 2019
This study introduced dynamic multistage testing (dy-MST) as an improvement to existing adaptive testing methods. dy-MST combines the advantages of computerized adaptive testing (CAT) and computerized adaptive multistage testing (ca-MST) to create a highly efficient and regulated adaptive testing method. In the test construction phase, multistage…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Construction, Psychometrics
Sahin, Melek Gulsah – International Journal of Assessment Tools in Education, 2020
Computer Adaptive Multistage Testing (ca-MST), which take the advantage of computer technology and adaptive test form, are widely used, and are now a popular issue of assessment and evaluation. This study aims at analyzing the effect of different panel designs, module lengths, and different sequence of a parameter value across stages and change in…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Response Theory
Designing Computer-Based Tests: Design Guidelines from Multimedia Learning Studied with Eye Tracking
Dirkx, K. J. H.; Skuballa, I.; Manastirean-Zijlstra, C. S.; Jarodzka, H. – Instructional Science: An International Journal of the Learning Sciences, 2021
The use of computer-based tests (CBTs), for both formative and summative purposes, has greatly increased over the past years. One major advantage of CBTs is the easy integration of multimedia. It is unclear, though, how to design such CBT environments with multimedia. The purpose of the current study was to examine whether guidelines for designing…
Descriptors: Test Construction, Computer Assisted Testing, Multimedia Instruction, Eye Movements
Yamamoto, Kentaro; Shin, Hyo Jeong; Khorramdel, Lale – OECD Publishing, 2019
This paper describes and evaluates a multistage adaptive testing (MSAT) design that was implemented for the Programme for International Student Assessment (PISA) 2018 main survey for the major domain of Reading. Through a simulation study, recovery of item response theory model parameters and measurement precision were examined. The PISA 2018 MSAT…
Descriptors: Adaptive Testing, Test Construction, Achievement Tests, Foreign Countries

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