Building a better data culture can be the path to better results and greater equity in schools. But what do we mean by data? Your students are not just statistics. They aren't simply a set of numbers or faceless dots on a proficiency scale. They are vibrant collections of experiences, thoughts, perspectives, emotions, wants, and dreams. And taken…

Collecting data for the purpose of decision making has become an integral part of the landscape of education in the United States over the past decade. Many educators are swamped with such an overwhelming amount of information that it can be difficult to sort and analyze, leaving them floundering under wave after wave of data. The SWIS facilitator…

The Grand Challenges for Assessment in Higher Education project is a collaborative effort of 10 endorsing organizations and over 400 volunteers to increase the extent to which assessment (1) supports equity; (2) is visible, actionable, and drives innovation; and (3) guides rapid improvements in pedagogy (Singer-Freeman and Robinson 2020). Several…

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…

State postsecondary education data systems are vital assets for policymakers, researchers, and the public. The State Higher Education Executive Officers Association's (SHEEO) Communities of Practice project builds upon SHEEO's efforts to measure the capacity and effective use of state postsecondary data systems and provides states with…

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting, and student-success interventions. Because predictive algorithms rely on historical data, they capture societal injustices, including racism. In this study, we examine…

In current contexts of education, educators are tasked with using data, most often without any critical preparation to do so. In this way, data are presented as objective measures of student progress and participation in school without consideration of the systemic and structural influences on that progress and participation. This article reports…

Student participation in summer programming can be an effective way to address students' academic and developmental needs. When well implemented and well attended, summer enrichment programs, academic programs, and employment programs have demonstrated positive outcomes for youth in areas related to program content, including academic achievement…

As federal funding for summer learning as a pandemic recovery strategy phases out, state governments face decisions about their future role in supporting students' access to quality summer learning opportunities. This brief is based on the full report, "How States Are Expanding Quality Summer Learning Opportunities," and summarizes…

Institutional researchers are acutely aware of the systemic inequities pervasive throughout higher education in the United States because the data that we collect, analyze, visualize, and disseminate quantifies and reveals them. As calls for addressing issues of equity have intensified across campuses, the question of how institutional research…

Institutions of higher education are asked to consider how their work can advance equity in institutional outcomes. Assessment, too, has been asked to consider the ways in which traditional student assessment "privileges and validates certain types of learning and evidence of learning over others" (Montenegro and Jankowski 2017, p. 5).…

The Data Must Speak (DMS) Positive Deviance research aims to improve the equity and quality of education through the use of data by studying the practices and behaviours of 'positive deviant' schools -- schools that outperform others despite operating in similar contexts and with equivalent resources. The analysis aims to inform practical…

Whilst technology may have been the 'saviour' of HE from the immediate challenges of the pandemic, the opportunistic dialogue emerging in response is imbued with notions of the pandemic as a catalyst for change. Empowered by the apparent success of technology's deliverance, the door has been opened to unprecedented investment into a pervasive and…

Despite increasing calls to build equitable data infrastructures, the education field has yet to have a shared guideline around equitable education data management and stewardship. To address this gap, we propose one framework from the data governance literature: the FAIR (Findable, Accessible, Interoperable, Reusable) data management principles…