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DeMars, Christine E. – Applied Measurement in Education, 2021
Estimation of parameters for the many-facets Rasch model requires that conditional on the values of the facets, such as person ability, item difficulty, and rater severity, the observed responses within each facet are independent. This requirement has often been discussed for the Rasch models and 2PL and 3PL models, but it becomes more complex…
Descriptors: Item Response Theory, Test Items, Ability, Scores
Tang, Xiaodan; Karabatsos, George; Chen, Haiqin – Applied Measurement in Education, 2020
In applications of item response theory (IRT) models, it is known that empirical violations of the local independence (LI) assumption can significantly bias parameter estimates. To address this issue, we propose a threshold-autoregressive item response theory (TAR-IRT) model that additionally accounts for order dependence among the item responses…
Descriptors: Item Response Theory, Test Items, Models, Computation
Lozano, José H.; Revuelta, Javier – Applied Measurement in Education, 2021
The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…
Descriptors: Bayesian Statistics, Computation, Learning, Testing
Karadavut, Tugba – Applied Measurement in Education, 2021
Mixture IRT models address the heterogeneity in a population by extracting latent classes and allowing item parameters to vary between latent classes. Once the latent classes are extracted, they need to be further examined to be characterized. Some approaches have been adopted in the literature for this purpose. These approaches examine either the…
Descriptors: Item Response Theory, Models, Test Items, Maximum Likelihood Statistics
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
El Masri, Yasmine H.; Andrich, David – Applied Measurement in Education, 2020
In large-scale educational assessments, it is generally required that tests are composed of items that function invariantly across the groups to be compared. Despite efforts to ensure invariance in the item construction phase, for a range of reasons (including the security of items) it is often necessary to account for differential item…
Descriptors: Models, Goodness of Fit, Test Validity, Achievement Tests
Pham, Duy N.; Wells, Craig S.; Bauer, Malcolm I.; Wylie, E. Caroline; Monroe, Scott – Applied Measurement in Education, 2021
Assessments built on a theory of learning progressions are promising formative tools to support learning and teaching. The quality and usefulness of those assessments depend, in large part, on the validity of the theory-informed inferences about student learning made from the assessment results. In this study, we introduced an approach to address…
Descriptors: Formative Evaluation, Mathematics Instruction, Mathematics Achievement, Middle School Students
Finch, Holmes; French, Brian F. – Applied Measurement in Education, 2019
The usefulness of item response theory (IRT) models depends, in large part, on the accuracy of item and person parameter estimates. For the standard 3 parameter logistic model, for example, these parameters include the item parameters of difficulty, discrimination, and pseudo-chance, as well as the person ability parameter. Several factors impact…
Descriptors: Item Response Theory, Accuracy, Test Items, Difficulty Level
Guo, Hongwen; Rios, Joseph A.; Haberman, Shelby; Liu, Ou Lydia; Wang, Jing; Paek, Insu – Applied Measurement in Education, 2016
Unmotivated test takers using rapid guessing in item responses can affect validity studies and teacher and institution performance evaluation negatively, making it critical to identify these test takers. The authors propose a new nonparametric method for finding response-time thresholds for flagging item responses that result from rapid-guessing…
Descriptors: Guessing (Tests), Reaction Time, Nonparametric Statistics, Models
George, Ann Cathrice; Robitzsch, Alexander – Applied Measurement in Education, 2018
This article presents a new perspective on measuring gender differences in the large-scale assessment study Trends in International Science Study (TIMSS). The suggested empirical model is directly based on the theoretical competence model of the domain mathematics and thus includes the interaction between content and cognitive sub-competencies.…
Descriptors: Achievement Tests, Elementary Secondary Education, Mathematics Achievement, Mathematics Tests
Using Necessary Information to Identify Item Dependence in Passage-Based Reading Comprehension Tests
Baldonado, Angela Argo; Svetina, Dubravka; Gorin, Joanna – Applied Measurement in Education, 2015
Applications of traditional unidimensional item response theory models to passage-based reading comprehension assessment data have been criticized based on potential violations of local independence. However, simple rules for determining dependency, such as including all items associated with a particular passage, may overestimate the dependency…
Descriptors: Reading Tests, Reading Comprehension, Test Items, Item Response Theory
Gierl, Mark J.; Lai, Hollis; Pugh, Debra; Touchie, Claire; Boulais, André-Philippe; De Champlain, André – Applied Measurement in Education, 2016
Item development is a time- and resource-intensive process. Automatic item generation integrates cognitive modeling with computer technology to systematically generate test items. To date, however, items generated using cognitive modeling procedures have received limited use in operational testing situations. As a result, the psychometric…
Descriptors: Psychometrics, Multiple Choice Tests, Test Items, Item Analysis
Koziol, Natalie A. – Applied Measurement in Education, 2016
Testlets, or groups of related items, are commonly included in educational assessments due to their many logistical and conceptual advantages. Despite their advantages, testlets introduce complications into the theory and practice of educational measurement. Responses to items within a testlet tend to be correlated even after controlling for…
Descriptors: Classification, Accuracy, Comparative Analysis, Models
Roduta Roberts, Mary; Alves, Cecilia B.; Chu, Man-Wai; Thompson, Margaret; Bahry, Louise M.; Gotzmann, Andrea – Applied Measurement in Education, 2014
The purpose of this study was to evaluate the adequacy of three cognitive models, one developed by content experts and two generated from student verbal reports for explaining examinee performance on a grade 3 diagnostic mathematics test. For this study, the items were developed to directly measure the attributes in the cognitive model. The…
Descriptors: Foreign Countries, Mathematics Tests, Cognitive Processes, Models
Kahraman, Nilufer; De Champlain, Andre; Raymond, Mark – Applied Measurement in Education, 2012
Item-level information, such as difficulty and discrimination are invaluable to the test assembly, equating, and scoring practices. Estimating these parameters within the context of large-scale performance assessments is often hindered by the use of unbalanced designs for assigning examinees to tasks and raters because such designs result in very…
Descriptors: Performance Based Assessment, Medicine, Factor Analysis, Test Items
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