RESEARCH LIBRARY

Academic Medicine: Volume 99 - Issue 7 - Pages 778-783

This study examined score comparability between in-person and remote proctored administrations of the 2020 Internal Medicine In-Training Examination (IM-ITE) during the COVID-19 pandemic. Analysis of data from 27,115 IM residents revealed statistically significant but educationally nonsignificant differences in predicted scores, with slightly larger variations observed for first-year residents. Overall, performance did not substantially differ between the two testing modalities, supporting the continued use of remote proctoring for the IM-ITE amidst pandemic-related disruptions.

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.

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. 

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.

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.