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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
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Shangchao Min; Kyoungwon Bishop – Language Testing, 2024
This paper evaluates the multistage adaptive test (MST) design of a large-scale academic language assessment (ACCESS) for Grades 1-12, with an aim to simplify the current MST design, using both operational and simulated test data. Study 1 explored the operational population data (1,456,287 test-takers) of the listening and reading tests of MST…
Descriptors: Adaptive Testing, Test Construction, Language Tests, English Language Learners
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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
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Ebru Dogruöz; Hülya Kelecioglu – International Journal of Assessment Tools in Education, 2024
In this research, multistage adaptive tests (MST) were compared according to sample size, panel pattern and module length for top-down and bottom-up test assembly methods. Within the scope of the research, data from PISA 2015 were used and simulation studies were conducted according to the parameters estimated from these data. Analysis results for…
Descriptors: Adaptive Testing, Test Construction, Foreign Countries, Achievement Tests
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
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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
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Wim J. van der Linden; Luping Niu; Seung W. Choi – Journal of Educational and Behavioral Statistics, 2024
A test battery with two different levels of adaptation is presented: a within-subtest level for the selection of the items in the subtests and a between-subtest level to move from one subtest to the next. The battery runs on a two-level model consisting of a regular response model for each of the subtests extended with a second level for the joint…
Descriptors: Adaptive Testing, Test Construction, Test Format, Test Reliability
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Stephen G. Sireci; Javier Suárez-Álvarez; April L. Zenisky; Maria Elena Oliveri – Grantee Submission, 2024
The goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design-In-Real-Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment "system." In this paper, we lay the foundation for DIRTy…
Descriptors: Educational Assessment, Student Needs, Test Format, Test Construction
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Stephen G. Sireci; Javier Suárez-Álvarez; April L. Zenisky; Maria Elena Oliveri – Educational Measurement: Issues and Practice, 2024
The goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design-in-Real-Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment "system." In this article, we lay the foundation for DIRTy…
Descriptors: Educational Assessment, Student Needs, Test Format, Test Construction