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Zhang, Susu; Li, Anqi; Wang, Shiyu – Educational Measurement: Issues and Practice, 2023
In computer-based tests allowing revision and reviews, examinees' sequence of visits and answer changes to questions can be recorded. The variable-length revision log data introduce new complexities to the collected data but, at the same time, provide additional information on examinees' test-taking behavior, which can inform test development and…
Descriptors: Computer Assisted Testing, Test Construction, Test Wiseness, Test Items
Justin L. Kern – Journal of Educational and Behavioral Statistics, 2024
Given the frequent presence of slipping and guessing in item responses, models for the inclusion of their effects are highly important. Unfortunately, the most common model for their inclusion, the four-parameter item response theory model, potentially has severe deficiencies related to its possible unidentifiability. With this issue in mind, the…
Descriptors: Item Response Theory, Models, Bayesian Statistics, Generalization
Eray Selçuk; Ergül Demir – International Journal of Assessment Tools in Education, 2024
This research aims to compare the ability and item parameter estimations of Item Response Theory according to Maximum likelihood and Bayesian approaches in different Monte Carlo simulation conditions. For this purpose, depending on the changes in the priori distribution type, sample size, test length, and logistics model, the ability and item…
Descriptors: Item Response Theory, Item Analysis, Test Items, Simulation
Sedat Sen; Allan S. Cohen – Educational and Psychological Measurement, 2024
A Monte Carlo simulation study was conducted to compare fit indices used for detecting the correct latent class in three dichotomous mixture item response theory (IRT) models. Ten indices were considered: Akaike's information criterion (AIC), the corrected AIC (AICc), Bayesian information criterion (BIC), consistent AIC (CAIC), Draper's…
Descriptors: Goodness of Fit, Item Response Theory, Sample Size, Classification
Lozano, José H.; Revuelta, Javier – Educational and Psychological Measurement, 2023
The present paper introduces a general multidimensional model to measure individual differences in learning within a single administration of a test. Learning is assumed to result from practicing the operations involved in solving the items. The model accounts for the possibility that the ability to learn may manifest differently for correct and…
Descriptors: Bayesian Statistics, Learning Processes, Test Items, Item Analysis
Abu-Ghazalah, Rashid M.; Dubins, David N.; Poon, Gregory M. K. – Applied Measurement in Education, 2023
Multiple choice results are inherently probabilistic outcomes, as correct responses reflect a combination of knowledge and guessing, while incorrect responses additionally reflect blunder, a confidently committed mistake. To objectively resolve knowledge from responses in an MC test structure, we evaluated probabilistic models that explicitly…
Descriptors: Guessing (Tests), Multiple Choice Tests, Probability, Models
A Sequential Bayesian Changepoint Detection Procedure for Aberrant Behaviors in Computerized Testing
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
Lee, HyeSun; Smith, Weldon Z. – Educational and Psychological Measurement, 2020
Based on the framework of testlet models, the current study suggests the Bayesian random block item response theory (BRB IRT) model to fit forced-choice formats where an item block is composed of three or more items. To account for local dependence among items within a block, the BRB IRT model incorporated a random block effect into the response…
Descriptors: Bayesian Statistics, Item Response Theory, Monte Carlo Methods, Test Format
Jing Lu; Chun Wang; Ningzhong Shi – Grantee Submission, 2023
In high-stakes, large-scale, standardized tests with certain time limits, examinees are likely to engage in either one of the three types of behavior (e.g., van der Linden & Guo, 2008; Wang & Xu, 2015): solution behavior, rapid guessing behavior, and cheating behavior. Oftentimes examinees do not always solve all items due to various…
Descriptors: High Stakes Tests, Standardized Tests, Guessing (Tests), Cheating
Sideridis, Georgios D.; Tsaousis, Ioannis; Alamri, Abeer A. – Educational and Psychological Measurement, 2020
The main thesis of the present study is to use the Bayesian structural equation modeling (BSEM) methodology of establishing approximate measurement invariance (A-MI) using data from a national examination in Saudi Arabia as an alternative to not meeting strong invariance criteria. Instead, we illustrate how to account for the absence of…
Descriptors: Bayesian Statistics, Structural Equation Models, Foreign Countries, Error of Measurement
Lee, Woo-yeol; Cho, Sun-Joo – Journal of Educational Measurement, 2017
Cross-level invariance in a multilevel item response model can be investigated by testing whether the within-level item discriminations are equal to the between-level item discriminations. Testing the cross-level invariance assumption is important to understand constructs in multilevel data. However, in most multilevel item response model…
Descriptors: Test Items, Item Response Theory, Item Analysis, Simulation
Chen, Ping – Journal of Educational and Behavioral Statistics, 2017
Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…
Descriptors: Test Items, Item Response Theory, Test Construction, Adaptive Testing
Kim, Do-Hong; Lambert, Richard G.; Durham, Sean; Burts, Diane C. – Early Education and Development, 2018
Research Findings: This study builds on prior work related to the assessment of young dual language learners (DLLs). The purposes of the study were to (a) determine whether latent subgroups of preschool DLLs would replicate those found previously and (b) examine the validity of GOLD® by Teaching Strategies with empirically derived subgroups.…
Descriptors: Preschool Education, Teaching Methods, Bilingualism, Bilingual Education
Qian, Xiaoyu; Nandakumar, Ratna; Glutting, Joseoph; Ford, Danielle; Fifield, Steve – ETS Research Report Series, 2017
In this study, we investigated gender and minority achievement gaps on 8th-grade science items employing a multilevel item response methodology. Both gaps were wider on physics and earth science items than on biology and chemistry items. Larger gender gaps were found on items with specific topics favoring male students than other items, for…
Descriptors: Item Analysis, Gender Differences, Achievement Gap, Grade 8
Wang, Xiaohui; Bradlow, Eric T.; Wainer, Howard; Muller, Eric S. – Journal of Educational and Behavioral Statistics, 2008
In the course of screening a form of a medical licensing exam for items that function differentially (DIF) between men and women, the authors used the traditional Mantel-Haenszel (MH) statistic for initial screening and a Bayesian method for deeper analysis. For very easy items, the MH statistic unexpectedly often found DIF where there was none.…
Descriptors: Bayesian Statistics, Licensing Examinations (Professions), Medicine, Test Items
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