Showing 1 - 2 of 2 Research Library Publications

Differential Item Functioning Analysis of United States Medical Licensing Examination Step 1 Items

Posted: | Jonathan D. Rubright, Michael Jodoin, Stephanie Woodward, Michael A. Barone

Academic Medicine: Volume 97 - Issue 5 - Pages 718-722

 

The purpose of this 2019–2020 study was to statistically identify and qualitatively review USMLE Step 1 exam questions (items) using differential item functioning (DIF) methodology.

Category:Product-Oriented Research, USMLE, Assessment-Oriented Research, Links to Outcomes

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