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Showing 1 to 15 of 328 results Save | Export
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Sessoms, John; Henson, Robert A. – Measurement: Interdisciplinary Research and Perspectives, 2018
Diagnostic classification models (DCMs) classify examinees based on the skills they have mastered given their test performance. This classification enables targeted feedback that can inform remedial instruction. Unfortunately, applications of DCMs have been criticized (e.g., no validity support). Generally, these evaluations have been brief and…
Descriptors: Literature Reviews, Classification, Models, Criticism
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Wang, Shiyu; Zhang, Susu; Douglas, Jeff; Culpepper, Steven – Measurement: Interdisciplinary Research and Perspectives, 2018
Analyzing students' growth remains an important topic in educational research. Most recently, Diagnostic Classification Models (DCMs) have been used to track skill acquisition in a longitudinal fashion, with the purpose to provide an estimate of students' learning trajectories in terms of the change of fine-grained skills overtime. Response time…
Descriptors: Reaction Time, Markov Processes, Computer Assisted Instruction, Spatial Ability
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Minchen, Nathan; de la Torre, Jimmy – Measurement: Interdisciplinary Research and Perspectives, 2018
Cognitive diagnosis models (CDMs) allow for the extraction of fine-grained, multidimensional diagnostic information from appropriately designed tests. In recent years, interest in such models has grown as formative assessment grows in popularity. Many dichotomous as well as several polytomous CDMs have been proposed in the last two decades, but…
Descriptors: Cognitive Measurement, Item Response Theory, Formative Evaluation, Models
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von Davier, Matthias – Measurement: Interdisciplinary Research and Perspectives, 2018
This article critically reviews how diagnostic models have been conceptualized and how they compare to other approaches used in educational measurement. In particular, certain assumptions that have been taken for granted and used as defining characteristics of diagnostic models are reviewed and it is questioned whether these assumptions are the…
Descriptors: Criticism, Psychometrics, Diagnostic Tests, Educational Assessment
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Henson, Robert; DiBello, Lou; Stout, Bill – Measurement: Interdisciplinary Research and Perspectives, 2018
Diagnostic classification models (DCMs, also known as cognitive diagnosis models) hold the promise of providing detailed classroom information about the skills a student has or has not mastered. Specifically, DCMs are special cases of constrained latent class models where classes are defined based on mastery/nonmastery of a set of attributes (or…
Descriptors: Classification, Diagnostic Tests, Models, Mastery Learning
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Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2018
This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Difficulty Level
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Rupp, André A.; van Rijn, Peter W. – Measurement: Interdisciplinary Research and Perspectives, 2018
We review the GIDNA and CDM packages in R for fitting cognitive diagnosis/diagnostic classification models. We first provide a summary of their core capabilities and then use both simulated and real data to compare their functionalities in practice. We found that the most relevant routines in the two packages appear to be more similar than…
Descriptors: Educational Assessment, Cognitive Measurement, Measurement, Computer Software
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Kim, Seohyun; Lu, Zhenqiu; Cohen, Allan S. – Measurement: Interdisciplinary Research and Perspectives, 2018
Bayesian algorithms have been used successfully in the social and behavioral sciences to analyze dichotomous data particularly with complex structural equation models. In this study, we investigate the use of the Polya-Gamma data augmentation method with Gibbs sampling to improve estimation of structural equation models with dichotomous variables.…
Descriptors: Bayesian Statistics, Structural Equation Models, Computation, Social Science Research
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Ames, Allison J.; Au, Chi Hang – Measurement: Interdisciplinary Research and Perspectives, 2018
Stan is a flexible probabilistic programming language providing full Bayesian inference through Hamiltonian Monte Carlo algorithms. The benefits of Hamiltonian Monte Carlo include improved efficiency and faster inference, when compared to other MCMC software implementations. Users can interface with Stan through a variety of computing…
Descriptors: Item Response Theory, Computer Software Evaluation, Computer Software, Programming Languages
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Leventhal, Brian C.; Stone, Clement A. – Measurement: Interdisciplinary Research and Perspectives, 2018
Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…
Descriptors: Bayesian Statistics, Item Response Theory, Models, Psychometrics
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Sinharay, Sandip – Measurement: Interdisciplinary Research and Perspectives, 2018
Producers and consumers of test scores are increasingly concerned about fraudulent behavior before and during the test. There exist several statistical or psychometric methods for detecting fraudulent behavior on tests. This paper provides a review of the Bayesian approaches among them. Four hitherto-unpublished real data examples are provided to…
Descriptors: Ethics, Cheating, Student Behavior, Bayesian Statistics
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Wyse, Adam E. – Measurement: Interdisciplinary Research and Perspectives, 2018
A key part of determining cut-scores when performing Angoff standard setting is utilizing equating methods to place standard-setting ratings onto the scale used to report scores to examinees. This article describes three equating methods that can be employed to place Angoff ratings onto the scale used to report scores to examinees when applying…
Descriptors: Standard Setting (Scoring), Equated Scores, Probability, Regression (Statistics)
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Weeks, Jonathan P. – Measurement: Interdisciplinary Research and Perspectives, 2018
Vertical scales are widely used in educational assessment as a basis for considering grade-to-grade changes in student performance. Typically, the underlying construct is assumed to be essentially unidimensional; however, if there is a change in the measured construct across grades, this assumption may be untenable. Developing a multidimensional…
Descriptors: Multidimensional Scaling, Reading Tests, Reading Skills, Basic Skills
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Albano, Anthony D.; Christ, Theodore J.; Cai, Liuhan – Measurement: Interdisciplinary Research and Perspectives, 2018
Traditional psychometric methods have primarily been developed and applied in the context of high-stakes, large-scale testing. However, these methods are increasingly being used with classroom assessments, including progress monitoring measures where numerous test forms are administered over the course of an academic year. This article provides an…
Descriptors: Progress Monitoring, Hierarchical Linear Modeling, Equated Scores, Raw Scores
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Hansen, Mark; Monroe, Scott – Measurement: Interdisciplinary Research and Perspectives, 2018
This research concerns the application of multidimensional item response theory (e.g., Reckase, 2009) to link not-quite-vertical scales across age/grade levels. The approach allows scores to be related across levels without requiring the assumption of a vertical scale. The multidimensional framework is applied to an English language proficiency…
Descriptors: Item Response Theory, Instructional Program Divisions, Language Tests, Elementary Secondary Education
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