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Showing 1 to 15 of 35 results Save | Export
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Finch, W. Holmes – Educational and Psychological Measurement, 2023
Psychometricians have devoted much research and attention to categorical item responses, leading to the development and widespread use of item response theory for the estimation of model parameters and identification of items that do not perform in the same way for examinees from different population subgroups (e.g., differential item functioning…
Descriptors: Test Bias, Item Response Theory, Computation, Methods
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Wang, Shiyu; Xiao, Houping; Cohen, Allan – Journal of Educational and Behavioral Statistics, 2021
An adaptive weight estimation approach is proposed to provide robust latent ability estimation in computerized adaptive testing (CAT) with response revision. This approach assigns different weights to each distinct response to the same item when response revision is allowed in CAT. Two types of weight estimation procedures, nonfunctional and…
Descriptors: Computer Assisted Testing, Adaptive Testing, Computation, Robustness (Statistics)
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Jewsbury, Paul A.; van Rijn, Peter W. – Journal of Educational and Behavioral Statistics, 2020
In large-scale educational assessment data consistent with a simple-structure multidimensional item response theory (MIRT) model, where every item measures only one latent variable, separate unidimensional item response theory (UIRT) models for each latent variable are often calibrated for practical reasons. While this approach can be valid for…
Descriptors: Item Response Theory, Computation, Test Items, Adaptive Testing
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Lai, Rina P. Y. – ACM Transactions on Computing Education, 2022
Computational Thinking (CT), entailing both domain-general and domain-specific skills, is a competency fundamental to computing education and beyond. However, as a cross-domain competency, appropriate assessment design and method remain equivocal. Indeed, the majority of the existing assessments have a predominant focus on measuring programming…
Descriptors: Computer Assisted Testing, Computation, Thinking Skills, Computer Science Education
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Choe, Edison M.; Kern, Justin L.; Chang, Hua-Hua – Journal of Educational and Behavioral Statistics, 2018
Despite common operationalization, measurement efficiency of computerized adaptive testing should not only be assessed in terms of the number of items administered but also the time it takes to complete the test. To this end, a recent study introduced a novel item selection criterion that maximizes Fisher information per unit of expected response…
Descriptors: Computer Assisted Testing, Reaction Time, Item Response Theory, 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
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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
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O'Keeffe, Cormac – E-Learning and Digital Media, 2017
International Large Scale Assessments have been producing data about educational attainment for over 60 years. More recently however, these assessments as tests have become digitally and computationally complex and increasingly rely on the calculative work performed by algorithms. In this article I first consider the coordination of relations…
Descriptors: Achievement Tests, Foreign Countries, Secondary School Students, International Assessment
Chen, Guanhua – ProQuest LLC, 2018
This study is part of a larger design study that iteratively improves a robotics programming curriculum as well as a computational thinking (CT) instrument. Its focus was majorly on CT assessment and particularly on an online CT instrument with logging functionality that can store a student's problem-solving process by recording interactions…
Descriptors: Elementary School Students, Test Construction, Cognitive Tests, Computer Assisted Testing
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Thissen, David – Journal of Educational and Behavioral Statistics, 2016
David Thissen, a professor in the Department of Psychology and Neuroscience, Quantitative Program at the University of North Carolina, has consulted and served on technical advisory committees for assessment programs that use item response theory (IRT) over the past couple decades. He has come to the conclusion that there are usually two purposes…
Descriptors: Item Response Theory, Test Construction, Testing Problems, Student Evaluation
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Han, Kyung T.; Guo, Fanmin – Practical Assessment, Research & Evaluation, 2014
The full-information maximum likelihood (FIML) method makes it possible to estimate and analyze structural equation models (SEM) even when data are partially missing, enabling incomplete data to contribute to model estimation. The cornerstone of FIML is the missing-at-random (MAR) assumption. In (unidimensional) computerized adaptive testing…
Descriptors: Maximum Likelihood Statistics, Structural Equation Models, Data, Computer Assisted Testing
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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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Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G. – Applied Psychological Measurement, 2013
Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…
Descriptors: Test Construction, Test Items, Item Banks, Automation
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Wang, Wen-Chung; Liu, Chen-Wei; Wu, Shiu-Lien – Applied Psychological Measurement, 2013
The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…
Descriptors: Computer Assisted Testing, Adaptive Testing, Models, Bayesian Statistics
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Özyurt, Hacer; Özyurt, Özcan – Eurasian Journal of Educational Research, 2015
Problem Statement: Learning-teaching activities bring along the need to determine whether they achieve their goals. Thus, multiple choice tests addressing the same set of questions to all are frequently used. However, this traditional assessment and evaluation form contrasts with modern education, where individual learning characteristics are…
Descriptors: Probability, Adaptive Testing, Computer Assisted Testing, Item Response Theory
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