As stated earlier, operationalizing a Graduate Profile is pioneering work. It’s experimental, relying on trial-and-error, healthy risk-taking, innovation, and an inquiry mindset. As such, gathering various forms of data is critical to enable frequent cycles of data-informed inquiry to assess needs, planning to address needs, execution to solve needs, and reflection and review.

Short cycles of feedback require the use of readily available data. For continuous improvement efforts to remain focused on students, particularly those on the margins, we must train ourselves to discern “street-level data” (Safir & Dugan, 2021) — i.e., the qualitative, systemic, and experiential data that emerges at eye level and on lower frequencies. Street data are artifacts from the lived experiences of stakeholders. Street data is asset based, building on the tenets of culturally responsive education by helping educators look for what’s right in our students, schools, and communities instead of seeking out what’s wrong. Street data embodies both an ethos and a change methodology that will transform how we analyze, diagnose, and assess everything from student learning to district improvement to policy. It offers us a new way to think about, gather, and make meaning of data. It calls for what Paolo Freire deemed a pedagogy of liberation (Freire, 1970).

Types of Street Data

Safir & Dugan differentiate “street data” from “map data” and “satellite data.” Map data hover closer to the ground, providing a GPS of social-emotional, cultural, and learning trends within a school community (e.g., literacy levels, rubric scores, satisfaction surveys). Satellite data hover far above the classroom and tell an important but incomplete story of equity (e.g., test scores, attendance patterns, graduation rates). Our education system has relied far too heavily on satellite data, which typically is collected and reported annually, thus not accommodating short cycles of improvement. Safir & Dugan argue that now is the time to take an antiracist stance, interrogate our assumptions about knowledge, measurement, and what really matters when it comes to educating young people.

To advance efforts to operationalize a Graduate Profile, districts should incorporate “street data” and work to build routine processes of continuous improvement into the fabric of their operations at all levels — individual practice, projects, programs, classrooms, schools, departments, and systems.


Street Data: A Next-Generation Model for Equity, Pedagogy, and School Transformation (Safir & Dugan, 2021, Corwin Press)


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