Across the country, educators are awash in data. From standardized test scores to attendance reports, from district dashboards to state accountability metrics, schools are collecting more information than ever. Yet despite this deluge, many educators feel starved for the kinds of insights that could truly drive improvement in teaching, learning, and student well-being.
What would it look like to reimagine how we define, collect, and use data—not as a compliance tool, but as a catalyst for equitable, student-centered transformation? In Connecticut and beyond, educators are asking how to distinguish between the kinds of data that burden us and the kinds that liberate us.
The Data We Drown In
A first step is recognizing the trap of mistaking “measurement” for “meaning.” Schools often spend enormous energy collecting data for state or federal reporting, diverting attention from the lived experiences of students and teachers.
High-stakes accountability systems have reinforced this dynamic, privileging narrow indicators—typically standardized test scores—as proxies for overall school health. While useful for system-wide comparisons, these metrics rarely provide real-time guidance for improvement.
Andrew Volkert, Program Coordinator, PEL
As Paul Cobb and Paul LeMahieu explain in Measuring to Improve: Practical Measurement to Support Continuous Improvement in Education, there is a critical difference between “accountability data” and “improvement data.” Accountability data is backward-looking, designed for reporting outcomes. Improvement data is forward-facing, collected in real time, and embedded in the everyday work of educators striving to learn and adapt.
Andrew Volkert, program coordinator at Partners, underscores the point by citing Dylan Wiliam: “We need to move from ‘data-driven decision-making’ to decision-driven data collection. In other words, educators should collect data only in service of the specific problem they’re trying to solve.”
“There is this important framing,” Volkert adds. “Data for improvement is different than data for accountability. The more appropriate a measure is for one, the more ill-suited it is for the other. Healthy systems need both.”
Equally important is what happens once data is gathered. “Culture is reinforced if you show that you’re using the data. But it degrades if the data isn’t used quickly, in real time, or brought back to the people who provided it. People see the value when they see it in action,” Volkert says.
Real-Time Learning: Street Data in Practice
A powerful model for gathering data comes from Shane Safir and Jamila Dugan’s Street Data: A Next-Generation Model for Equity, Pedagogy, and School Transformation. They describe three levels:
- “Satellite data” offers the broadest, most distant view—like test scores and graduation rates.
- “Map data” includes things like surveys and interim assessments that provide a closer look.
- “Street data” is on-the-ground, human-centered, and deeply contextual—gathered through student interviews, classroom observations, and teacher reflections.
Transformation happens with street data. As Safir notes, “Google Maps doesn’t work if it only gives you a satellite view. You need turn-by-turn directions. That’s what street data provides.”
To gather street data, it’s important to ask what’s happening for different people in the system you are seeking to understand. Listening to what teachers and students say gives school leaders access to needed information they would otherwise not be privy to.
“If we define data as any information that helps us understand how we’re functioning and how we could improve, then stories count as data,” says Rydell Harrison, program coordinator at Partners.
Why do stories matter? Harrison points to two reasons: “First, because they lift up voices that have been at the margins. But it’s not just about representation—these students have experiences we need to bring into the conversation for improvement to happen. It’s a different approach to data.”
He offers a practical example: “Starting this year, Bristol leaders are bringing teachers into improvement work focused on student voice. They’ve reframed their improvement process around ‘understanding your system.’ They look at three lenses: research, bright spots in classrooms, and student experiences. They know that without all three, the picture is incomplete.”
Harrison, along with program coordinator Kerry Lord, puts this into practice through the new Student Voice Institute, where district teams practice empathy interviews, lead focus groups, and reflect on qualitative student data. Participants create deeper connections to student realities and space for co-construction—not just compliance.
From the Margins to the Center
Making classrooms and schools work for all students requires us to rethink not only what data we collect but whose voices we center. Too often, marginalized voices—students of color, multilingual learners, students with disabilities—are absent from data conversations. Yet these perspectives can reveal blind spots and opportunities for change.
As Safir and Dugan write, “By choosing the margins as the starting point for our data conversations, we invert the pyramid, shift the dynamics of power, and bring children to the center of educational discourse.” In this model, data collection becomes an act of listening—and a mechanism for shared power.
Harrison, co-author with Isobel Stevenson of Equitable School Improvement: The Critical Need for the Human Side of Change, connects this to a broader systems view: “Educators have a mental model that ‘anecdotal evidence’ is inadequate, and we have to point out that what people say about their experience is the foundation of many research traditions.”
Shifting from Compliance to Curiosity
What will it take to move from data as compliance to data as curiosity? It starts with asking different questions. Instead of, “Are we closing the achievement gap?” we might ask, “What are our students trying to tell us with their behaviors, their disengagement, their joy?” Instead of, “Did we meet the benchmark?” we might ask, “How are our students experiencing school right now?”
The most powerful data conversations often happen in professional learning communities, where teachers examine student work together, ask reflective questions, and identify next steps. In these spaces, data becomes a springboard for learning, not judgment.
This shift calls for new tools:
- Student voice artifacts (interviews, storytelling, participatory research)
- Instructional artifacts (student work, discussion transcripts, video reflections)
- Belonging and identity indicators (emotional safety, inclusion, cultural relevance)
And just as important: we must interrogate the data we collect. Do our metrics align with our values? Do they reinforce deficit narratives or illuminate student strengths? Are we collecting data with communities—or simply extracting it from them?
The Role of Leadership
At the heart of this reimagining is leadership. Safir and Dugan call for a “pedagogy of voice”—centering student agency, prioritizing inquiry over compliance, and valuing feedback over grades. They highlight the role of “warm demanders”—leaders who balance high expectations with deep care by:
- Building authentic trust and relationships
- Embracing failure as part of learning
- Creating inclusive spaces for collective growth
Looking Ahead
District and school leaders set the tone for how data is collected and used. We must continue supporting professional learning communities in gathering and reflecting on real-time, “street-level” data, and partnering with communities to design systems that reflect shared values—not just state mandates.
The questions remain important: Whose data matters? What stories are we missing? How can data serve—not sort—our students?
If we are awash in data, let’s be sure we are not starved for meaning, because our task is not to manage data but to listen, learn, and lead in ways that support every student’s best outcome.
