Showing 1 - 7 of 7 Research Library Publications
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. 

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: | Daniel Jurich, Michelle Daniel, Karen E. Hauer, Christine Seibert, Latha Chandran, Arnyce R. Pock, Sara B. Fazio, Amy Fleming, Sally A. Santen

Teaching and Learning in Medicine: Volume 33 - Issue 4 - p 366-381

 

CSE scores for students from eight schools that moved Step 1 after core clerkships between 2012 and 2016 were analyzed in a pre-post format. Hierarchical linear modeling was used to quantify the effect of the curriculum on CSE performance. Additional analysis determined if clerkship order impacted clinical subject exam performance and whether the curriculum change resulted in more students scoring in the lowest percentiles before and after the curricular change.

Posted: | M. M. Hammoud, L. M.Foster, M. M.Cuddy, D. B. Swanson, P. M. Wallach

American Journal of Obstetrics and Gynecology, Volume 223, Issue 3, Pages 435.e1-435.e6

 

The purpose of this study was to examine medical student reporting of electronic health record use during the obstetrics and gynecology clerkship.

Posted: | M. J. Margolis, B. E. Clauser

Handbook of Automated Scoring

 

In this chapter we describe the historical background that led to development of the simulations and the subsequent refinement of the construct that occurred as the interface was being developed. We then describe the evolution of the automated scoring procedures from linear regression modeling to rule-based procedures.

Posted: | P. M. Wallach L. M. Foster, M. M. Cuddy, M. M. Hammoud, K. Z. Holtzman, D. B. Swanson

J Gen Intern Med 34, 705–711 (2019)

 

This study examines medical student accounts of EHR use during their internal medicine (IM) clerkships and sub-internships during a 5-year time period prior to the new clinical documentation guidelines.