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Ye Ma; Deborah J. Harris – Educational Measurement: Issues and Practice, 2025
Item position effect (IPE) refers to situations where an item performs differently when it is administered in different positions on a test. The majority of previous research studies have focused on investigating IPE under linear testing. There is a lack of IPE research under adaptive testing. In addition, the existence of IPE might violate Item…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
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Yuan, Lu; Huang, Yingshi; Li, Shuhang; Chen, Ping – Journal of Educational Measurement, 2023
Online calibration is a key technology for item calibration in computerized adaptive testing (CAT) and has been widely used in various forms of CAT, including unidimensional CAT, multidimensional CAT (MCAT), CAT with polytomously scored items, and cognitive diagnostic CAT. However, as multidimensional and polytomous assessment data become more…
Descriptors: Computer Assisted Testing, Adaptive Testing, Computation, Test Items
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Aybek, Eren Can – Journal of Applied Testing Technology, 2021
The study aims to introduce catIRT tools which facilitates researchers' Item Response Theory (IRT) and Computerized Adaptive Testing (CAT) simulations. catIRT tools provides an interface for mirt and catR packages through the shiny package in R. Through this interface, researchers can apply IRT calibration and CAT simulations although they do not…
Descriptors: Item Response Theory, Computer Assisted Testing, Simulation, Models
Ozge Ersan Cinar – ProQuest LLC, 2022
In educational tests, a group of questions related to a shared stimulus is called a testlet (e.g., a reading passage with multiple related questions). Use of testlets is very common in educational tests. Additionally, computerized adaptive testing (CAT) is a mode of testing where the test forms are created in real time tailoring to the test…
Descriptors: Test Items, Computer Assisted Testing, Adaptive Testing, Educational Testing
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Musa Adekunle Ayanwale; Mdutshekelwa Ndlovu – Journal of Pedagogical Research, 2024
The COVID-19 pandemic has had a significant impact on high-stakes testing, including the national benchmark tests in South Africa. Current linear testing formats have been criticized for their limitations, leading to a shift towards Computerized Adaptive Testing [CAT]. Assessments with CAT are more precise and take less time. Evaluation of CAT…
Descriptors: Adaptive Testing, Benchmarking, National Competency Tests, Computer Assisted Testing
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Cooperman, Allison W.; Weiss, David J.; Wang, Chun – Educational and Psychological Measurement, 2022
Adaptive measurement of change (AMC) is a psychometric method for measuring intra-individual change on one or more latent traits across testing occasions. Three hypothesis tests--a Z test, likelihood ratio test, and score ratio index--have demonstrated desirable statistical properties in this context, including low false positive rates and high…
Descriptors: Error of Measurement, Psychometrics, Hypothesis Testing, Simulation
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Bengs, Daniel; Kroehne, Ulf; Brefeld, Ulf – Journal of Educational Measurement, 2021
By tailoring test forms to the test-taker's proficiency, Computerized Adaptive Testing (CAT) enables substantial increases in testing efficiency over fixed forms testing. When used for formative assessment, the alignment of task difficulty with proficiency increases the chance that teachers can derive useful feedback from assessment data. The…
Descriptors: Computer Assisted Testing, Formative Evaluation, Group Testing, Program Effectiveness
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Sahin Kursad, Merve; Cokluk Bokeoglu, Omay; Cikrikci, Rahime Nukhet – International Journal of Assessment Tools in Education, 2022
Item parameter drift (IPD) is the systematic differentiation of parameter values of items over time due to various reasons. If it occurs in computer adaptive tests (CAT), it causes errors in the estimation of item and ability parameters. Identification of the underlying conditions of this situation in CAT is important for estimating item and…
Descriptors: Item Analysis, Computer Assisted Testing, Test Items, Error of Measurement
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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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Fuchimoto, Kazuma; Ishii, Takatoshi; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2022
Educational assessments often require uniform test forms, for which each test form has equivalent measurement accuracy but with a different set of items. For uniform test assembly, an important issue is the increase of the number of assembled uniform tests. Although many automatic uniform test assembly methods exist, the maximum clique algorithm…
Descriptors: Simulation, Efficiency, Test Items, Educational Assessment
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Chen, Chia-Wen; Wang, Wen-Chung; Chiu, Ming Ming; Ro, Sage – Journal of Educational Measurement, 2020
The use of computerized adaptive testing algorithms for ranking items (e.g., college preferences, career choices) involves two major challenges: unacceptably high computation times (selecting from a large item pool with many dimensions) and biased results (enhanced preferences or intensified examinee responses because of repeated statements across…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
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Ghio, Fernanda Belén; Bruzzone, Manuel; Rojas-Torres, Luis; Cupani, Marcos – European Journal of Science and Mathematics Education, 2022
In the last decades, the development of computerized adaptive testing (CAT) has allowed more precise measurements with a smaller number of items. In this study, we develop an item bank (IB) to generate the adaptive algorithm and simulate the functioning of CAT to assess the domains of mathematical knowledge in Argentinian university students…
Descriptors: Test Items, Item Banks, Adaptive Testing, Mathematics Tests
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Kárász, Judit T.; Széll, Krisztián; Takács, Szabolcs – Quality Assurance in Education: An International Perspective, 2023
Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…
Descriptors: Test Length, Probability, Comparative Analysis, Difficulty Level
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Lee, Chansoon; Qian, Hong – Educational and Psychological Measurement, 2022
Using classical test theory and item response theory, this study applied sequential procedures to a real operational item pool in a variable-length computerized adaptive testing (CAT) to detect items whose security may be compromised. Moreover, this study proposed a hybrid threshold approach to improve the detection power of the sequential…
Descriptors: Computer Assisted Testing, Adaptive Testing, Licensing Examinations (Professions), Item Response Theory
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Berger, Stéphanie; Verschoor, Angela J.; Eggen, Theo J. H. M.; Moser, Urs – Journal of Educational Measurement, 2019
Calibration of an item bank for computer adaptive testing requires substantial resources. In this study, we investigated whether the efficiency of calibration under the Rasch model could be enhanced by improving the match between item difficulty and student ability. We introduced targeted multistage calibration designs, a design type that…
Descriptors: Simulation, Computer Assisted Testing, Test Items, Difficulty Level
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