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.
Academic Medicine: May 2018 - Volume 93 - Issue 5 - p 781-785
In 2007, the United States Medical Licensing Examination embedded multimedia simulations of heart sounds into multiple-choice questions. This study investigated changes in item difficulty as determined by examinee performance over time. The data reflect outcomes obtained following initial use of multimedia items from 2007 through 2012, after which an interface change occurred.