Reporting Subscore Profiles Using Diagnostic Classification Models in Health Professions Education.
Yoon Soo Park1, Amy Morales2, Linette Ross2
1Department of Medical Education, College of Medicine, University of Illinois at Chicago, IL, USA.
Diagnostic classification models (DCMs) offer reliable subscores for health professions education assessments. This approach provides fine-grained proficiency profiles, enabling targeted feedback for learners and educators.
Area of Science:
- Educational Measurement
- Psychometrics
- Health Professions Education
Background:
- Health professions education requires detailed assessment feedback beyond overall scores.
- Concerns about reliability have limited the practical use of subscores.
- Diagnostic classification models (DCMs) offer a solution for reliable subscore reporting.
Purpose of the Study:
- To examine the application of DCMs for generating subscores in health professions education.
- To assess the psychometric properties and practical utility of DCMs using large-scale assessment data.
Main Methods:
- Retrospective analysis of National Board of Medical Examiners Subject Examinations in pathology and medicine.
- Fitting and analyzing DCMs to generate examinee subscores and proficiency profiles.
- Evaluating model fit, classification reliability, and parameter estimates.
Main Results:
- DCMs demonstrated good psychometric properties and reliable examinee classification into subscore profiles.
- Analysis revealed useful information regarding varying subscore distributions.
- High consistency in classification indicates reliable fine-grained subscore results.
Conclusions:
- The DCM framework is a promising approach for reporting reliable subscores in health professions education.
- DCMs enable targeted and specific feedback to learners based on fine-grained proficiency.
- This methodology addresses the need for more detailed assessment information in medical education.
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