Showing 1 - 7 of 7 Research Library Publications
Posted: | Victoria Yaneva (editor), Matthias von Davier (editor)

Advancing Natural Language Processing in Educational Assessment

 

This book examines the use of natural language technology in educational testing, measurement, and assessment. Recent developments in natural language processing (NLP) have enabled large-scale educational applications, though scholars and professionals may lack a shared understanding of the strengths and limitations of NLP in assessment as well as the challenges that testing organizations face in implementation. This first-of-its-kind book provides evidence-based practices for the use of NLP-based approaches to automated text and speech scoring, language proficiency assessment, technology-assisted item generation, gamification, learner feedback, and beyond.

Posted: | Martin G. Tolsgaard, Martin V. Pusic, Stefanie S. Sebok-Syer, Brian Gin, Morten Bo Svendsen, Mark D. Syer, Ryan Brydges, Monica M. Cuddy, Christy K. Boscardin

Medical Teacher: Volume 45 - Issue 6, Pages 565-573

 

This guide aims aim to describe practical considerations involved in reading and conducting studies in medical education using Artificial Intelligence (AI), define basic terminology and identify which medical education problems and data are ideally-suited for using AI.

Posted: | Ian Micir, Kimberly Swygert, Jean D'Angelo

Journal of Applied Technology: Volume 23 - Special Issue 1 - Pages 30-40

 

The interpretations of test scores in secure, high-stakes environments are dependent on several assumptions, one of which is that examinee responses to items are independent and no enemy items are included on the same forms. This paper documents the development and implementation of a C#-based application that uses Natural Language Processing (NLP) and Machine Learning (ML) techniques to produce prioritized predictions of item enemy statuses within a large item bank.

Posted: | Martin G. Tolsgaard, Christy K. Boscardin, Yoon Soo Park, Monica M. Cuddy, Stefanie S. Sebok-Syer

Advances in Health Sciences Education: Volume 25, p 1057–1086 (2020)

 

This critical review explores: (1) published applications of data science and ML in HPE literature and (2) the potential role of data science and ML in shifting theoretical and epistemological perspectives in HPE research and practice.

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: | 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.

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

Academic Medicine: November 2018 - Volume 93 - Issue 11S - p S14-S20

 

An important goal of medical education is to teach students to use an electronic health record (EHR) safely and effectively. The purpose of this study is to examine medical student accounts of EHR use during their core inpatient clinical clerkships using a national sample. Paper health records (PHRs) are similarly examined.