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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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Park, Ryoungsun; Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G. – Educational and Psychological Measurement, 2017
The current study proposes novel methods to predict multistage testing (MST) performance without conducting simulations. This method, called MST test information, is based on analytic derivation of standard errors of ability estimates across theta levels. We compared standard errors derived analytically to the simulation results to demonstrate the…
Descriptors: Testing, Performance, Prediction, Error of Measurement
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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
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He, Wei; Diao, Qi; Hauser, Carl – Educational and Psychological Measurement, 2014
This study compared four item-selection procedures developed for use with severely constrained computerized adaptive tests (CATs). Severely constrained CATs refer to those adaptive tests that seek to meet a complex set of constraints that are often not conclusive to each other (i.e., an item may contribute to the satisfaction of several…
Descriptors: Comparative Analysis, Test Items, Selection, Computer Assisted Testing
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Cheng, Ying; Patton, Jeffrey M.; Shao, Can – Educational and Psychological Measurement, 2015
a-Stratified computerized adaptive testing with b-blocking (AST), as an alternative to the widely used maximum Fisher information (MFI) item selection method, can effectively balance item pool usage while providing accurate latent trait estimates in computerized adaptive testing (CAT). However, previous comparisons of these methods have treated…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
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Leroux, Audrey J.; Lopez, Myriam; Hembry, Ian; Dodd, Barbara G. – Educational and Psychological Measurement, 2013
This study compares the progressive-restricted standard error (PR-SE) exposure control procedure to three commonly used procedures in computerized adaptive testing, the randomesque, Sympson-Hetter (SH), and no exposure control methods. The performance of these four procedures is evaluated using the three-parameter logistic model under the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Comparative Analysis, Statistical Analysis
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Seo, Dong Gi; Weiss, David J. – Educational and Psychological Measurement, 2015
Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm…
Descriptors: Computer Assisted Testing, Adaptive Testing, Accuracy, Fidelity
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Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G.; Park, Ryoungsun – Educational and Psychological Measurement, 2012
This study compared various panel designs of the multistage test (MST) using mixed-format tests in the context of classification testing. Simulations varied the design of the first-stage module. The first stage was constructed according to three levels of test information functions (TIFs) with three different TIF centers. Additional computerized…
Descriptors: Test Format, Comparative Analysis, Computer Assisted Testing, Adaptive Testing
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Lee, HwaYoung; Dodd, Barbara G. – Educational and Psychological Measurement, 2012
This study investigated item exposure control procedures under various combinations of item pool characteristics and ability distributions in computerized adaptive testing based on the partial credit model. Three variables were manipulated: item pool characteristics (120 items for each of easy, medium, and hard item pools), two ability…
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Banks, Ability
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Moyer, Eric L.; Galindo, Jennifer L.; Dodd, Barbara G. – Educational and Psychological Measurement, 2012
Managing test specifications--both multiple nonstatistical constraints and flexibly defined constraints--has become an important part of designing item selection procedures for computerized adaptive tests (CATs) in achievement testing. This study compared the effectiveness of three procedures: constrained CAT, flexible modified constrained CAT,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Item Analysis
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Choi, Seung W.; Grady, Matthew W.; Dodd, Barbara G. – Educational and Psychological Measurement, 2011
The goal of the current study was to introduce a new stopping rule for computerized adaptive testing (CAT). The predicted standard error reduction (PSER) stopping rule uses the predictive posterior variance to determine the reduction in standard error that would result from the administration of additional items. The performance of the PSER was…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Evaluation Methods
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Frey, Andreas; Seitz, Nicki-Nils – Educational and Psychological Measurement, 2011
The usefulness of multidimensional adaptive testing (MAT) for the assessment of student literacy in the Programme for International Student Assessment (PISA) was examined within a real data simulation study. The responses of N = 14,624 students who participated in the PISA assessments of the years 2000, 2003, and 2006 in Germany were used to…
Descriptors: Adaptive Testing, Literacy, Academic Achievement, Achievement Tests
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Cheng, Ying; Chang, Hua-Hua; Douglas, Jeffrey; Guo, Fanmin – Educational and Psychological Measurement, 2009
a-stratification is a method that utilizes items with small discrimination (a) parameters early in an exam and those with higher a values when more is learned about the ability parameter. It can achieve much better item usage than the maximum information criterion (MIC). To make a-stratification more practical and more widely applicable, a method…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
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Chen, Ssu-Kuang; Hou, Liling; Dodd, Barbara G. – Educational and Psychological Measurement, 1998
A simulation study was conducted to investigate the application of expected a posteriori (EAP) trait estimation in computerized adaptive tests (CAT) based on the partial credit model and compare it with maximum likelihood estimation (MLE). Results show the conditions under which EAP and MLE provide relatively accurate estimation in CAT. (SLD)
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Estimation (Mathematics)
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De Ayala, R. J. – Educational and Psychological Measurement, 1989
A polychotomous nominal response model-based computerized adaptive test (CAT) was simulated using data from 1,093 University of Texas students. The ability estimation of this model and its overall performance were compared with those of a dichotomous three-parameter logistic model-based CAT. Advantages and drawbacks of nominal response CAT are…
Descriptors: Adaptive Testing, College Students, Comparative Analysis, Computer Assisted Testing
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