Proceedings of the 28th International Conference on Computational Linguistics
This paper brings together approaches from the fields of NLP and psychometric measurement to address the problem of predicting examinee proficiency from responses to short-answer questions (SAQs).
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).
Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, 19(1)
This review is a descriptive summary of the development of National EM M4 examinations, Version 1 (V1) and Version 2 (V2), and the NBME EM Advanced Clinical Examination (ACE) and their relevant usage and performance data. In particular, it describes how examination content was edited to affect desired changes in examination performance data and offers a model for educators seeking to develop their own examinations.