Testing season is once again behind us—pencils are down, laptops are closed, proctoring duties are over, and somewhere in a state database, students’ results are quietly waiting to be processed and reported. For many teachers and leaders, this in-between period can feel like a refreshing return to curriculum and instruction. In fact, it’s one of the most important windows of the year for preparing teams to use data in ways that genuinely improve instructional practice and outcomes for all students.
Extensive research has clarified what makes data teams effective, and recent work has turned attention toward data teams that struggle (Schildkamp & Datnow, 2020). The findings are both grounding and instructive. The biggest barriers to meaningful data use typically stem not from the data itself, but from the conditions surrounding it, specifically:
The research also suggests that teams that rely solely on standardized assessment data may struggle to make meaningful instructional improvements. State assessment results can offer a high-level view of where students stand relative to grade-level expectations, but they often arrive late, can be difficult to connect directly to daily instruction, and may best describe patterns across groups rather than the needs of individual students.
The most effective data teams use state assessment results as just one lens among many, drawing on a mix of quantitative and qualitative sources: formative and summative assessments, surveys, classroom observations, student work samples, exit tickets, and more. This fuller, more comprehensive view gives teachers and teams a better picture of what individual students have learned and what they need next.
Just as important as what data teams examine is how they examine it. Research suggests that conversations focused mainly on group-level trends—for example, percentages of students below benchmark, subgroup patterns, or "bubble kids”—don't typically translate into meaningful improvements in daily classroom practice. These data points are useful starting points, but they are only starting points.
High-functioning data teams push further into asking student-specific questions: What does this student understand? Where is the gap showing up in their work? What does this student need next? This shift from trends to individual students is characteristic of teams that move from simply reviewing data to actually improving teaching and learning.
Before state results arrive, there are four research-based questions worth raising with your team. These questions can help ensure that teachers, leaders, and ultimately students get the greatest benefit from data-focused work:
The research is clear: leaders set the conditions that make everything else possible. When leaders provide time and tools for data inquiry, model genuine curiosity, ensure data is never used to blame or shame, and actively invite teachers’ voices into the process, data-focused work strengthens both instruction and professional learning communities. Equally important, leaders influence which data gets examined and at what level of specificity. This determines whether data conversations stay at the surface or move to the individual students who need something different.
As data teams wait for state assessment results to arrive, what they build together right now matters. By strengthening trust, clarifying shared purpose, keeping individual students at the center, and cultivating a collaborative culture of continuous improvement, teams will already be doing work that makes a difference.