Showing 1 - 2 of 2 Research Library Publications

A Comparison of Remote vs In-Person Proctored In-Training Examination Administration for Internal Medicine

Posted: | Thai Ong, Becky Krumm, Margaret Wells, Susan Read, Linda Harris, Andrea Altomare, Miguel Paniagua

Academic Medicine: Volume 99 - Issue 7 - Pages 778-783

 

This study examined score comparability between in-person and remote proctored administrations of the 2020 Internal Medicine In-Training Examination (IM-ITE) during the COVID-19 pandemic. Analysis of data from 27,115 IM residents revealed statistically significant but educationally nonsignificant differences in predicted scores, with slightly larger variations observed for first-year residents. Overall, performance did not substantially differ between the two testing modalities, supporting the continued use of remote proctoring for the IM-ITE amidst pandemic-related disruptions.

Category:Assessment-Oriented Research, Scoring, 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