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.
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.
Academic Medicine: Volume 98 - Issue 2 - Pages 162-170
The US medical education transition from school to residency is resource-intensive. The Coalition for Physician Accountability aims to improve it, emphasizing learner support, diversity, and minimizing conflicts. This study explores key tensions and offers strategies to align the transition with ideal goals, aiding educators and organizations in implementing recommendations.
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.
Academic Medicine: Volume 96 - Issue 9 - Pages 1324-1331
This study examines associations between USMLE Step 1 and Step 2 Clinical Knowledge (CK) scores and ACGME emergency medicine (EM) milestone ratings.
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.
Medical Teacher: Volume 40 - Issue 11 - p 1143-1150
This study explores a novel milestone-based workplace assessment system that was implemented in 15 pediatrics residency programs. The system provided: web-based multisource feedback and structured clinical observation instruments that could be completed on any computer or mobile device; and monthly feedback reports that included competency-level scores and recommendations for improvement.