Showing 1 - 3 of 3 Research Library Publications

Leveraging Machine Learning Technology to Improve Accuracy and Efficiency of Identification of Enemy Item Pairs

Posted: | Ian Micir, Kimberly Swygert, Jean D'Angelo

Journal of Applied Technology: Volume 23 - Special Issue 1 - Pages 30-40

 

The interpretations of test scores in secure, high-stakes environments are dependent on several assumptions, one of which is that examinee responses to items are independent and no enemy items are included on the same forms. This paper documents the development and implementation of a C#-based application that uses Natural Language Processing (NLP) and Machine Learning (ML) techniques to produce prioritized predictions of item enemy statuses within a large item bank.

Category:Assessment-Oriented Research, Scoring, Applications of Technology

Reporting Subscore Profiles Using Diagnostic Classification Models in Health Professions Education

Posted: | Y.S. Park, A. Morales, L. Ross, M. Paniagua

Evaluation & the Health Professions: Volume: 43 issue: 3, page(s): 149-158

 

This study examines the innovative and practical application of DCM framework to health professions educational assessments using retrospective large-scale assessment data from the basic and clinical sciences: National Board of Medical Examiners Subject Examinations in pathology (n = 2,006) and medicine (n = 2,351).

Category:Assessment-Oriented Research, Scoring, Product-Oriented Research, NBME

Conditional Subscore Reporting Using Iterated Discrete Convolutions

Posted: | R.A. Feinberg, M. von Davier

Journal of Educational and Behavioral Statistics: Vol 45, Issue 5, 2020

 

This article describes a method for identifying and reporting unexpectedly high or low subscores by comparing each examinee’s observed subscore with a discrete probability distribution of subscores conditional on the examinee’s overall ability.

Category:Assessment-Oriented Research, Scoring