Showing 1 - 4 of 4 Research Library Publications
Posted: | Victoria Yaneva, Peter Baldwin, Daniel P. Jurich, Kimberly Swygert, Brian E. Clauser

Academic Medicine: Volume 99 - Issue 2 - p 192-197

 

This report investigates the potential of artificial intelligence (AI) agents, exemplified by ChatGPT, to perform on the United States Medical Licensing Examination (USMLE), following reports of its successful performance on sample items. 

Posted: | Victoria Yaneva, Peter Baldwin, Le An Ha, Christopher Runyon

Advancing Natural Language Processing in Educational Assessment: Pages 167-182

 

This chapter discusses the evolution of natural language processing (NLP) approaches to text representation and how different ways of representing text can be utilized for a relatively understudied task in educational assessment – that of predicting item characteristics from item text.

Posted: | Polina Harik, Janet Mee, Christopher Runyon, Brian E. Clauser

Advancing Natural Language Processing in Educational Assessment: Pages 58-73

 

This chapter describes INCITE, an NLP-based system for scoring free-text responses. It emphasizes the importance of context and the system’s intended use and explains how each component of the system contributed to its accuracy.

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).