ArticlePsychometrika2020
Using Response Times and Response Accuracy to Measure Fluency Within Cognitive Diagnosis Models.
Article in Psychometrika, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A general dynamic learning model framework for cognitive diagnosis.The British journal of mathematical and statistical psychology · 2025Article
- A Mixture Fluency model using responses and response times with cognitive diagnosis model framework.Behavior research methods · 2024Article
- Longitudinal joint modeling for assessing parallel interactive development of latent ability and processing speed using responses and response times.Behavior research methods · 2024Article
- DIAGNOSTIC Classification Analysis of Problem-Solving Competence using Process Data: An Item Expansion Method.Psychometrika · 2022Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The recent "Every Student Succeed Act" encourages schools to use an innovative assessment to provide feedback about students' mastery level of grade-level content standards. Mastery of a skill requires the ability to complete the task with not only accuracy but also fluency. This paper offers a new sight on using both response times and response accuracy to measure fluency with cognitive diagnosis model framework. Defining fluency as the highest level of a categorical latent attribute, a polytomous response accuracy model and two forms of response time models are proposed to infer fluency jointly. A Bayesian estimation approach is developed to calibrate the newly proposed models. These models were applied to analyze data collected from a spatial rotation test. Results demonstrate that compared with the traditional CDM that using response accuracy only, the proposed joint models were able to reveal more information regarding test takers' spatial skills. A set of simulation studies were conducted to evaluate the accuracy of model estimation algorithm and illustrate the various degrees of model complexities.
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Registered trials
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