Equating and scaling in the context of small sample exams, such as credentialing exams for highly specialized professions, has received increased attention in recent research. Investigators have proposed a variety of both classical and Rasch-based approaches to the problem. This study attempts to extend past research by (1) directly comparing…

In 2015, the American Association of Community Colleges (AACC) announced the AACC Pathways Project, a national initiative designed to support a cohort of community colleges to implement and scale whole-college guided pathways reforms. Thirty community colleges from 17 states were selected for the project and embraced the challenge of redesigning…

Recent research has explored the use of models adapted from Mokken scale analysis as a nonparametric approach to evaluating rating quality in educational performance assessments. A potential limiting factor to the widespread use of these techniques is the requirement for complete data, as practical constraints in operational assessment systems…

One of the largest challenges in educator preparation in higher education is the effective use of data for actionable and meaningful decision making about programs for current and future educators, administrators, and educational leaders. Within programs there are many types of students. These may include elementary, secondary, special education,…

This "AERA Open" special topic takes stock of the current knowledge about scaled-up early childhood education (ECE) programs. Rapidly rising ECE participation rates in recent decades have coincided with wide variability in the types of programming available for young children. This expansion makes understanding heterogeneity in effects…

Researchers commonly interpret effect sizes by applying benchmarks proposed by Jacob Cohen over a half century ago. However, effects that are small by Cohen's standards are large relative to the impacts of most field-based interventions. These benchmarks also fail to consider important differences in study features, program costs, and scalability.…

In 2018 the Center for Universal Education (CUE) at Brookings launched a series of Real-time Scaling Labs (RTSL) to generate more evidence and provide practical recommendations on how to expand, deepen, and sustain the impact of education initiatives leading to transformative change in education systems, especially for the most disadvantaged…

This account of practice describes an online program started in 2022, which helps leaders at BNP Paribas to be more effective problem solvers and inclusive leaders by developing stronger questioning and listening skills. The goals of this program were aligned with action learning and could have been achieved with standard, coach-led action…

Change moves fast, and organizations can struggle to keep up. Mergers and acquisitions create new organizations, and managerial charts flatten, with fewer layers of administration in the middle causing people to be expected to do more with less. The optimal way to achieve critical outcomes is by scaling development opportunities across the entire…

Graph representations underlie many modern computer applications, capturing the structure of such diverse networks as the Internet, personal associations, roads, sensors, and metabolic pathways. While the static structure of graphs is a well-explored field, a new emphasis is being placed on understanding and representing the way these networks…

The purpose of this article was two-fold (1) provide an overview of the commonly reported and under-reported absolute agreement indices in the kinesiology literature for continuous data; and (2) present examples of these indices for hypothetical data along with recommendations for future use. It is recommended that three types of information be…

A distinction is made between scores as measures of a construct and predictions of a criterion or outcome variable. The interpretation attached to predictions of criteria, such as job performance or college grade point average (GPA), differs from that attached to scores that are measures of a construct, such as reading proficiency or knowledge…

In this research brief, SRI presents six lessons about equitable scaling from a retrospective study of the Deeper Learning + Diffusion of Innovation and Scaled Impact Initiative (DL+D initiative). Funded by the William and Flora Hewlett Foundation beginning in 2018, the goal of the DL+D initiative was to generate knowledge about how fundamental…

This article reports findings that describe the role that school- and district-based facilitators play in scaling up a published mathematics professional learning program. The study included 12 local facilitators (three teacher leaders and nine staff developers with specialization in mathematics, special education, or English learner education)…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…