The article describes practical suggestions for measurement researchers and psychometricians to respond to calls for social responsibility in assessment. The underlying assumption is that personalizing large-scale assessment improves the chances that assessment and the use of test scores will contribute to equity in education. This article…

The COVID-19 pandemic has accelerated the digitalization of assessment, creating new challenges for measurement professionals, including big data management, test security, and analyzing new validity evidence. In response to these challenges, "Machine Learning" (ML) emerges as an increasingly important skill in the toolbox of measurement…

This article presents the consensus of an National Council on Measurement in Education Presidential Task Force on Foundational Competencies in Educational Measurement. Foundational competencies are those that support future development of additional professional and disciplinary competencies. The authors develop a framework for foundational…

Professor Gordon argues for a significant reorientation in the focus and impact of assessment in education. For the types of assessment activities that he advocates to prosper and positively impact education, serious attention must be paid to two important topics: (1) the conceptual underpinnings of the assessment practices we develop and use to…

This paper discusses the unprecedented challenges and possible directions in which the field of educational assessment is going after the outbreak of COVID-19. Though the pandemic leads to a lot of pressure related to instruction, learning, and assessment, it also provides opportunities that are likely to require changes to the current theories…

Educational tests are standardized so that all examinees are tested on the same material, under the same testing conditions, and with the same scoring protocols. This uniformity is designed to provide a level "playing field" for all examinees so that the test is "the same" for everyone. Thus, standardization is designed to…

Three examples of extant testing practices (i.e., a classroom instructor's use of a simple pre-post design, the practice of teaching to the test, and the think aloud verbal protocol) are discussed to illustrate the contention that assessment in the service of testing and learning does not necessarily involve radically different assessment…

This article is a written adaptation of the Presidential address I gave at the NCME annual conference in April 2018. The article describes my thoughts on the future of assessment. I discuss eleven likely characteristics of future tests and, for each characteristic, why I think it is important and what to watch with respect to it. Next, I outline…

In this digital ITEMS module, Dr. Sue Lottridge, Amy Burkhardt, and Dr. Michelle Boyer provide an overview of automated scoring. Automated scoring is the use of computer algorithms to score unconstrained open-ended test items by mimicking human scoring. The use of automated scoring is increasing in educational assessment programs because it allows…

The goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design-in-Real-Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment "system." In this article, we lay the foundation for DIRTy…

In this digital ITEMS module, we introduce the framework of nonparametric item response theory (IRT), in particular Mokken scaling, which can be used to evaluate fundamental measurement properties with less strict assumptions than parametric IRT models. We walk through the key distinction between parametric and nonparametric models, introduce the…

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module…

In this digital ITEMS module, Nikole Gregg and Dr. Brian Leventhal discuss strategies to ensure data visualizations achieve graphical excellence. Data visualizations are commonly used by measurement professionals to communicate results to examinees, the public, educators, and other stakeholders. To do so effectively, it is important that these…

Data mining methods for classification and regression are becoming increasingly popular in various scientific fields. However, these methods have not been explored much in educational measurement. This module first provides a review, which should be accessible to a wide audience in education measurement, of some of these methods. The module then…

The main points of Sijtsma and Green and Yang in Educational Measurement: Issues and Practice (34, 4) are that reliability, internal consistency, and unidimensionality are distinct and that Cronbach's alpha may be problematic. Neither of these assertions are at odds with Davenport, Davison, Liou, and Love in the same issue. However, many authors…