Showing 1 - 3 of 3 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

Correlations Between the USMLE Step Examinations, American College of Physicians In-Training Examination, and ABIM Internal Medicine Certification Examination

Posted: | F.S. McDonald, D. Jurich, L.M. Duhigg, M. Paniagua, D. Chick, M. Wells, A. Williams, P. Alguire

Academic Medicine: September 2020 - Volume 95 - Issue 9 - p 1388-1395

 

This article aims to assess the correlations between United States Medical Licensing Examination (USMLE) performance, American College of Physicians Internal Medicine In-Training Examination (IM-ITE) performance, American Board of Internal Medicine Internal Medicine Certification Exam (IM-CE) performance, and other medical knowledge and demographic variables.

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

Automated Item Generation with Recurrent Neural Networks

Posted: | M. von Davier

Psychometrika 83, 847–857 (2018)

 

Utilizing algorithms to generate items in educational and psychological testing is an active area of research for obvious reasons: Test items are predominantly written by humans, in most cases by content experts who represent a limited and potentially costly resource. Using algorithms instead has the appeal to provide an unlimited resource for this crucial part of assessment development.

Category:Assessment-Oriented Research, Applications of Technology