Student outcome data is essential for decision-making in higher education, informing choices at the student, institutional, and state levels. Within state authorization--the gatekeeping process for institutional entry, continued operation, and closure--these data support oversight, accountability, and consumer transparency. This brief summarizes…

Policymakers across the country are seeking to better understand credentials of value--the education and training programs that help workers fill in-demand and growing jobs in their states. But right now, leaders are lacking the complete set of information they need to understand P-20W (early childhood, K-12, postsecondary, and workforce) pathways…

While there are many different types of education data, policymakers and education leaders often place heavy emphasis on data from large-scale quantitative measures, such as annual state assessments. But data from these sources alone do not provide a complete picture of learning and are often not well suited to informing improvements at the local…

The underrepresentation and underperformance of low-income, first-generation, gender minoritized, Black, Latine, and Indigenous students in Science, Technology, Engineering, and Mathematics (STEM) occurs for a variety of reasons, including, that students in these groups experience opportunity gaps in STEM classes. A critical approach to disrupting…

Speculative reform jumps the gun on notions of data-driven reform, requiring administrators to anticipate and act to ensure problems (and the data that would show them) do not materialize. Speculative reforms are incapable of delivering the outcomes they promise, as they are fueled by a fear of the future that their reforms do not extinguish. In…

This guide by DaSy, NCPMI, and ECTA provides cross-sector teams at the state, territory, tribal, and local levels with strategies for collecting and using data across the mixed delivery system of early care and education programs. Collecting and analyzing qualitative and quantitative data can help inform teams to develop policy and practices that…

Computer-based learning environments (CBLEs) are powerful tools to support student learning. Increasingly of interest is the data that is recorded as learners interact with a CBLE. This "process data" yields opportunities for researchers to examine learners' engagement with a CBLE and explore whether specific interactions are associated…

Students, families, colleges, and lawmakers need clearer information on postsecondary outcomes to make informed decisions. By leveraging data available at institutions and federal agencies, a nationwide student-level data network (SLDN) would close information gaps that persist in our higher education landscape to answer critical questions about…

This article explores utilizing a post-graduation success lens to help community college leaders frame the challenges of achieving equitable improvement for their students. Specifically, it posits that providing and exploring customized labor market data presented in an accessible format can help institutional leaders provide a "true…

The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…

The University of Missouri Kansas City (UMKC) is an urban research university with a special emphasis on fostering diversity. In 2021, the Center for Advancing Faculty Excellence created a Faculty Fellows program to develop comprehensive resources and support in four areas: teaching and learning, service and engagement, research and creativity,…

The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…

Online education is an important component of education reform and one of the important learning modes in today's society, which can achieve the goal of learning anytime, anywhere and for everyone. Therefore, this paper constructs an analysis model of online education course emotional perception and course resource integration based on new media…

Out-of-school-time (OST) programs and their funders rely on sound data to make decisions about everything from professional development and student recruitment to the selection of activities to offer students. Programs operate at a range of times (before and after school, weekends, summer) and in a variety of locations (e.g., schools,…

Survey methodology is the dominant approach among universities in the United States for reporting employment outcomes for recent graduates. However, past studies have shown that survey methodology may yield upwardly biased results, which can result in overreporting of employment rates and salary outcomes. This case study describes the development…