Showing 1 - 3 of 3 Research Library Publications
Posted: | Andrew A. White, Ann M. King, Angelo E. D’Addario, Karen Berg Brigham, Suzanne Dintzis, Emily E. Fay, Thomas H. Gallagher, Kathleen M. Mazor

JMIR Medical Education: Volume 8 - Issue 2 - e30988

 

This article aims to compare the reliability of two assessment groups (crowdsourced laypeople and patient advocates) in rating physician error disclosure communication skills using the Video-Based Communication Assessment app.

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: | S. Tackett, M. Raymond, R. Desai, S. A. Haist, A. Morales, S. Gaglani, S. G. Clyman

Medical Teacher: Volume 40 - Issue 8 - p 838-841

 

Adaptive learning requires frequent and valid assessments for learners to track progress against their goals. This study determined if multiple-choice questions (MCQs) “crowdsourced” from medical learners could meet the standards of many large-scale testing programs.