State education departments find themselves pressured to reduce costs while improving student performance. To do so, state education departments must measure the performance of each school district in an objective, data-informed manner. We present a benchmarking methodology and illustrate its application in New York State school districts. We…

Datafication of student learning has carved out an influential space for public and private actors who design technologies for visualizing data. As data visualizations shape how teachers' interpret data, they are powerful devices. This paper examines how teachers get configured as data users in the making of Danish national test data…

An administrative rule allowed students who failed an exam to retake it shortly after, triggering strong `teach to the test' incentives to raise these students' test scores for the retake. We develop a model that accounts for truncation and find that these students score 0.14 standard deviations higher on the retest. Using a regression…

An advantage of well-designed survey research is that, typically, it yields large volumes of quantitative and qualitative data. A key challenge researchers face is mining and reporting these data appropriately and promptly to inform research publications and presentations. When mixed methods are employed, and researchers attempt to master computer…

This descriptive and correlational research studies 15,658 students from 335 secondary schools in the state of Chihuahua, Mexico, through the results of the examination of admission to high school education (National High School Admission Test--EXANI I from the National Assessment Center for Education--CENEVAL) on logical-mathematical and verbal…

We study the effect of exposure to immigrants on the educational outcomes of US-born students, using a unique dataset combining population-level birth and school records from Florida. This research question is complicated by substantial school selection of US-born students, especially among White and comparatively affluent students, in response to…

Juxtaposed with the emerging body of literature about datafication in schooling, this paper examines the increasing encroachment of data into the Japanese education system, in particular, the use of data associated with standardised academic assessments for governance purposes. In so doing, we use the Japanese 'case' to expose the possible limits…

Is public housing bad for children? Critics charge that public housing projects concentrate poverty and create neighborhoods with limited opportunities, including low-quality schools. However, whether the net effect is positive or negative is theoretically ambiguous and likely to depend on the characteristics of the neighborhood and schools…

Policymakers and professional educators attempt to be good stewards of public funds while simultaneously raising expectations for student outcomes that reflect academic excellence in the public school system. The purpose of this study was to determine the efficiency of Texas public school districts and the factors influencing the inefficiency of…

Federal law requires states and school districts to institute accountability systems that report disaggregated student data to ensure that all children make academic progress. However, one of the mandated categories for disaggregation -- English Learner (EL) -- is reported as a single group despite representing students who are beginning,…

This article draws upon recent theorising of the "becoming topological" of space--specifically, how new social spaces are constituted through relations rather than physical locations--to explore how standardised data, and specifically test data, have influenced teachers' work and learning. We outline the varied ways in which teacher…

The Education Equality Index (EEI), created through a unique collaboration of GreatSchools and Education Cities, is a nationally comparative measure that looks at how well students from low-income families are achieving in schools, cities, and states across the country and The EEI taps GreatSchools' national school information database and…

Data-driven decision making (DDDM) helps educators identify children not responding to intervention, individualize instruction, and monitor response to intervention in multitiered systems of support (MTSS). More prevalent in K-12 special education, MTSS practices are emerging in early childhood. In previous reports, we described the Making Online…

The academic achievement gap is a persistent and pernicious educational challenge confounded with race and socioeconomic status. The achievement gap persists despite over three decades of interventions and federal, state, and local policies and initiatives meant to close it. We examine the achievement gap in one of the most diverse states in the…

Data-driven decision making (DDDM) helps educators identify children not responding to intervention, individualize instruction, and monitor response to intervention in multitiered systems of support (MTSS). More prevalent in K-12 special education, MTSS practices are emerging in early childhood. In previous reports, we described the Making Online…