Teachers' use of student data to inform instruction is commonly accepted as sound educational practice, and this data use is only likely to grow as more data, as well as more-complex data, become increasingly available to educators. However, numerous studies reveal inconsistent data use among teachers and an overall lack of the preparation and…

Clustered data structures are common in many areas of educational and psychological research (e.g., students clustered in schools, patients clustered by clinician). In the course of conducting research, questions are often administered to obtain scores reflecting latent constructs. Multilevel measurement models (MLMMs) allow for modeling…

Research information management (RIM) is a rapidly growing area of investment in US research universities. RIM systems that support the collection and use of research outputs metadata have been in place for many years. Globally, the RIM ecosystem is quite mature in locales where national research assessment exercises like the United Kingdom's…

Research Information Management (RIM) is a rapidly growing area of investment in US research universities, comprised of a variety of use cases, stakeholders, and products. This growth has been characteristically decentralized, resulting in silos, multiple systems, and frequent duplication of efforts at many institutions. This report is a two-part…

For creating and reading data visualizations, visual literacy is crucial. This article advances the knowledge about graphical variations and conventions related to the basic graphical element of the graphical line used as a connector in data visualizations. Some visual characteristics of connecting lines can be used to show directionality and thus…

This conceptual framework aims to build a shared and comprehensive understanding of what constitute EiE data and of the concepts and processes that underpin and guide work on education in emergencies data across a range of contexts, including acute emergencies, protracted crises, and displacement. The framework also presents a number of strategic…

Machine learning (ML) provides a powerful framework for the analysis of high-dimensional datasets by modelling complex relationships, often encountered in modern data with many variables, cases and potentially non-linear effects. The impact of ML methods on research and practical applications in the educational sciences is still limited, but…

This article provides a conceptual framework for considering both the theoretical and methodological factors that underpin the successful validation of a competency framework. Drawing on educational assessment literature, this article argues that a valid competency framework relates to an interpretive judgement of the credibility of the claims…

As the education and workforce development community looks more and more to CTE to help ensure students are both college and career ready, understanding and using CTE data and research becomes increasingly important. This is the first in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE)…

"Fostering Youth Transitions 2023: State and National Data to Drive Foster Care Advocacy" is a unique compilation of data designed to inform federal and state policy efforts aimed at making a difference for young people in foster care. This overview brief and detailed profiles of the latest available data from all 50 states, along with…

There is a broad impetus across policy and institutional domains to expand public engagement and involvement with emerging technology research and innovation. Yet innovative theory, methods, and practices to critically explore algorithmic system controversies and democratic possibilities are still in nascent form. In this paper, we bring together…

High demand exists for data to analyze the equitable distribution of school funding within and across school districts. In response to this growing demand, the National Center for Education Statistics (NCES) developed a new collection of finance data at the school level--the School-Level Finance Survey (SLFS). The SLFS collects at the school level…

The first step to addressing equity gaps is to identify them. How can community colleges determine, with some degree of certainty, whether one or more student groups on a campus is in need of assistance in order to succeed? This paper tackles this question by delving into the three methods typically used to identify equity gaps, comparing and…

By partnering with researchers, state CTE administrators have the opportunity to better understand CTE programming and practices across their states. This is the fourth in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE) Research Network Lead. Designed for CTE practitioners and state…

The work of the National Forum on Education Statistics (Forum) is a key aspect of the National Cooperative Education Statistics System (Cooperative System). The Cooperative System was established to produce and maintain, with the cooperation of the states, comparable and uniform education information and data that are useful for policymaking at…