The Stanford Education Data Archive (SEDA) launched in 2016 to provide nationally comparable, publicly available test score data for U.S. public school districts. I introduce a special collection of six articles that each use SEDA to lend their questions and findings a national scope. Together, these articles demonstrate a range of uses of SEDA…

This study investigates how youth from two cities in the United States engage in critical data practices as they learn about and take action in their lives and communities in relation to COVID-19 and its intersections with justice-related concerns. Guided by theories of critical data literacies and data justice, a historicized and future-oriented…

Although numerous survey-based studies have found that students who identify as lesbian, gay, bisexual, or questioning (LGBQ) have elevated risk for many negative academic, disciplinary, psychological, and health outcomes, the validity of the types of data on which these results rest have come under increased scrutiny. Over the past several years,…

As state governments seek to improve the performance of institutions of K-12 and higher education, they often adopt educational policies that have similar names but different characteristics across states and with variations over time within states. Yet quantitative analyses generally examine the absence or presence of an educational policy…

The school discipline literature has expanded rapidly in recent decades, yet the conceptualization and measurement of school discipline patterns remains overlooked. In this paper, we present a comprehensive analytic framework to examine school discipline patterns that encompasses school-level metrics that capture the prevalence and disparity in…

In addition to providing a set of techniques to analyze educational data, I claim that data science as a field can provide broader insights to education research. In particular, I show how the bias-variance tradeoff from machine learning can be formally generalized to be applicable to several prominent educational debates, including debates around…

Big data from massive open online courses (MOOCs) have enabled researchers to examine learning processes at almost infinite levels of granularity. Yet, such data sets do not track every important element in the learning process. Many strategies that MOOC learners use to overcome learning challenges are not captured in clickstream and log data. In…

Research has shown that mathematical proficiency gaps are related to students' and schools' indicators of poverty, with fewer studies on neighborhood effects on achievement gaps. Although this literature has accounted for students' nesting within schools, so far, methodological constraints have not allowed researchers to formally account for…

Currently, the state of California has dedicated much focus to reducing absenteeism in schools through the In School + On Track initiative, which revitalizes efforts made to keep accurate and informative attendance data. Additionally, absenteeism has been integrated into California's Local Control and Accountability Plan to monitor district…

The prospect of "big data" at once evokes optimistic views of an information-rich future and concerns about surveillance that adversely impacts our personal and private lives. This overview article explores the implications of big data in education, focusing by way of example on data generated by student writing. We have chosen writing…

Despite substantial federal, state, and local investments in improving early care and education (ECE), we know little about whether ECE program quality has improved over time. The lack of data tracking the quality of publicly funded ECE programs at scale creates a substantial evidence gap for policymakers attempting to weigh the returns on, and…

This mixed-methods observational study analyzes Advanced Placement (AP) Biology teachers' engagement in microblogging for professional learning. Data from three hashtag-based Twitter communities--#apbiochat, #apbioleaderacad, and #apbioleaderacademy (121 users; 2,253 tweets)--are analyzed using educational data mining, qualitative two-cycle…

The Stanford Educational Data Archive (SEDA) is the first data set to allow comparisons of district academic achievement and growth from Grades 3 to 8 across the United States, shining a light on the distribution of educational opportunities. This study describes a convergent validity analysis of the SEDA growth estimates in mathematics and…

In this article, I discuss the promise of geospatial techniques for education policy research and how increased attention to the historical context of spatial data can enhance that work. While scholarship utilizing geographic information systems has added considerable breadth to our understanding of education policy, recent geospatial studies in…