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.
Medical Science Educator: Volume 31, p 607–613 (2021)
This study extended previous research on the NBME Clinical Science Mastery Series self-assessments to investigate the utility of recently released self-assessments for students completing Family Medicine clerkships and Emergency Medicine sub-internships and preparing for summative assessments.
Journal of Veterinary Medical Education 2018 45:3, 381-387
This study uses item response data from the November–December 2014 and April 2015 NAVLE administrations (n =5,292), to conduct timing analyses comparing performance across several examinee subgroups. The results provide evidence that conditions were sufficient for most examinees, thereby supporting the current time limits. For the relatively few examinees who may have been impacted, results suggest the cause is not a bias with the test but rather the effect of poor pacing behavior combined with knowledge deficits.