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RESEARCH LIBRARY

View the latest publications from members of the NBME research team

Showing 1 - 5 of 5 Research Library Publications
Posted: June 5, 2023 | 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: July 23, 2020 | M. G. Jodoin, J. D. Rubright

Educational Measurement: Issues and Practice

 

This short, invited manuscript focuses on the implications for certification and licensure assessment organizations as a result of the wide‐spread disruptions caused by the COVID-19 pandemic. 

Posted: June 25, 2020 | M.J. Margolis, R.A. Feinberg (eds)

Integrating Timing Considerations to Improve Testing Practices

 

This book synthesizes a wealth of theory and research on time issues in assessment into actionable advice for test development, administration, and scoring. 

Posted: June 25, 2020 | D. Jurich

Integrating Timing Considerations to Improve Testing Practices

 

This chapter presents a historical overview of the testing literature that exemplifies the theoretical and operational evolution of test speededness.

Posted: February 26, 2020 | B.C. Leventhal, I. Grabovsky

Educational Measurement: Issues and Practice, 39: 30-36

 

This article proposes the conscious weight method and subconscious weight method to bring more objectivity to the standard setting process. To do this, these methods quantify the relative harm of the negative consequences of false positive and false negative misclassification.