RESEARCH LIBRARY

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.

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. 

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.

Journal of Educational Measurement: Volume 57, Issue 2, Pages 216-229

This article presents two generalizability-theory–based analyses of the proportion of the item variance that contributes to error in the cut score. For one approach, variance components are estimated on the probability (or proportion-correct) scale of the Angoff judgments, and for the other, the judgments are transferred to the theta scale of an item response theory model before estimating the variance components.

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.

Applied Psychological Measurement: Volume: 42 issue: 8, page(s): 595-612

Conventional methods for evaluating the utility of subscores rely on reliability and correlation coefficients. However, correlations can overlook a notable source of variability: variation in subtest means/difficulties. Brennan introduced a reliability index for score profiles based on multivariate generalizability theory, designated as G, which is sensitive to variation in subtest difficulty. However, there has been little, if any, research evaluating the properties of this index. A series of simulation experiments, as well as analyses of real data, were conducted to investigate G under various conditions of subtest reliability, subtest correlations, and variability in subtest means.

Medical Care: April 2017 - Volume 55 - Issue 4 - p 436-441

The objective of this study is to identify modifiable factors that improve the reliability of ratings of severity of health care–associated harm in clinical practice improvement and research.