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Showing 1 to 15 of 147 results Save | Export
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Falk, Carl F.; Feuerstahler, Leah M. – Educational and Psychological Measurement, 2022
Large-scale assessments often use a computer adaptive test (CAT) for selection of items and for scoring respondents. Such tests often assume a parametric form for the relationship between item responses and the underlying construct. Although semi- and nonparametric response functions could be used, there is scant research on their performance in a…
Descriptors: Item Response Theory, Adaptive Testing, Computer Assisted Testing, Nonparametric Statistics
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Philippe Goldammer; Peter Lucas Stöckli; Yannik Andrea Escher; Hubert Annen; Klaus Jonas – Educational and Psychological Measurement, 2024
Indirect indices for faking detection in questionnaires make use of a respondent's deviant or unlikely response pattern over the course of the questionnaire to identify them as a faker. Compared with established direct faking indices (i.e., lying and social desirability scales), indirect indices have at least two advantages: First, they cannot be…
Descriptors: Identification, Deception, Psychological Testing, Validity
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Markus T. Jansen; Ralf Schulze – Educational and Psychological Measurement, 2024
Thurstonian forced-choice modeling is considered to be a powerful new tool to estimate item and person parameters while simultaneously testing the model fit. This assessment approach is associated with the aim of reducing faking and other response tendencies that plague traditional self-report trait assessments. As a result of major recent…
Descriptors: Factor Analysis, Models, Item Analysis, Evaluation Methods
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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
Yixi Wang – ProQuest LLC, 2020
Binary item response theory (IRT) models are widely used in educational testing data. These models are not perfect because they simplify the individual item responding process, ignore the differences among different response patterns, cannot handle multidimensionality that lay behind options within a single item, and cannot manage missing response…
Descriptors: Item Response Theory, Educational Testing, Data, Models
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Yoshioka, Sérgio R. I.; Ishitani, Lucila – Informatics in Education, 2018
Computerized Adaptive Testing (CAT) is now widely used. However, inserting new items into the question bank of a CAT requires a great effort that makes impractical the wide application of CAT in classroom teaching. One solution would be to use the tacit knowledge of the teachers or experts for a pre-classification and calibrate during the…
Descriptors: Student Motivation, Adaptive Testing, Computer Assisted Testing, Item Response Theory
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Sinharay, Sandip – Journal of Educational and Behavioral Statistics, 2016
Meijer and van Krimpen-Stoop noted that the number of person-fit statistics (PFSs) that have been designed for computerized adaptive tests (CATs) is relatively modest. This article partially addresses that concern by suggesting three new PFSs for CATs. The statistics are based on tests for a change point and can be used to detect an abrupt change…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Goodness of Fit
Benton, Tom – Research Matters, 2021
Computer adaptive testing is intended to make assessment more reliable by tailoring the difficulty of the questions a student has to answer to their level of ability. Most commonly, this benefit is used to justify the length of tests being shortened whilst retaining the reliability of a longer, non-adaptive test. Improvements due to adaptive…
Descriptors: Risk, Item Response Theory, Computer Assisted Testing, Difficulty Level
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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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Gorney, Kylie; Wollack, James A. – Practical Assessment, Research & Evaluation, 2022
Unlike the traditional multiple-choice (MC) format, the discrete-option multiple-choice (DOMC) format does not necessarily reveal all answer options to an examinee. The purpose of this study was to determine whether the reduced exposure of item content affects test security. We conducted an experiment in which participants were allowed to view…
Descriptors: Test Items, Test Format, Multiple Choice Tests, Item Analysis
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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
Wang, Keyin – ProQuest LLC, 2017
The comparison of item-level computerized adaptive testing (CAT) and multistage adaptive testing (MST) has been researched extensively (e.g., Kim & Plake, 1993; Luecht et al., 1996; Patsula, 1999; Jodoin, 2003; Hambleton & Xing, 2006; Keng, 2008; Zheng, 2012). Various CAT and MST designs have been investigated and compared under the same…
Descriptors: Comparative Analysis, Computer Assisted Testing, Adaptive Testing, Test Items
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Lin, Yin; Brown, Anna – Educational and Psychological Measurement, 2017
A fundamental assumption in computerized adaptive testing is that item parameters are invariant with respect to context--items surrounding the administered item. This assumption, however, may not hold in forced-choice (FC) assessments, where explicit comparisons are made between items included in the same block. We empirically examined the…
Descriptors: Personality Measures, Measurement Techniques, Context Effect, Test Items
Mao, Xiuzhen; Ozdemir, Burhanettin; Wang, Yating; Xiu, Tao – Online Submission, 2016
Four item selection indexes with and without exposure control are evaluated and compared in multidimensional computerized adaptive testing (CAT). The four item selection indices are D-optimality, Posterior expectation Kullback-Leibler information (KLP), the minimized error variance of the linear combination score with equal weight (V1), and the…
Descriptors: Comparative Analysis, Adaptive Testing, Computer Assisted Testing, Test Items
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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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