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.
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.
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.
Academic Medicine: September 2020 - Volume 95 - Issue 9 - p 1388-1395
This article aims to assess the correlations between United States Medical Licensing Examination (USMLE) performance, American College of Physicians Internal Medicine In-Training Examination (IM-ITE) performance, American Board of Internal Medicine Internal Medicine Certification Exam (IM-CE) performance, and other medical knowledge and demographic variables.
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.