Showing 1 - 2 of 2 Research Library Publications

ACTA: Short-Answer Grading in High-Stakes Medical Exams

Posted: | King Yiu Suen, Victoria Yaneva, Le An Ha, Janet Mee, Yiyun Zhou, Polina Harik

Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023), Pages 443-447

 

This paper presents the ACTA system, which performs automated short-answer grading in the domain of high-stakes medical exams. The system builds upon previous work on neural similarity-based grading approaches by applying these to the medical domain and utilizing contrastive learning as a means to optimize the similarity metric. 

Category:Assessment-Oriented Research, Scoring, General Measurement

Leveraging Natural Language Processing: Toward Computer-Assisted Scoring of Patient Notes in the USMLE Step 2 Clinical Skills Exam

Posted: | J. Salt, P. Harik, M. A. Barone

Academic Medicine: March 2019 - Volume 94 - Issue 3 - p 314-316

 

The United States Medical Licensing Examination Step 2 Clinical Skills (CS) exam uses physician raters to evaluate patient notes written by examinees. In this Invited Commentary, the authors describe the ways in which the Step 2 CS exam could benefit from adopting a computer-assisted scoring approach that combines physician raters’ judgments with computer-generated scores based on natural language processing (NLP).

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