Every school collects student data.

Benchmark assessments. Student work samples. Attendance records. Classroom observations. Common formative assessments.

The challenge isn't collecting the data—it's making sense of what we have and deciding what, if anything, we should do next.

Too often, meetings that include looking at student data become exercises in finding "the answer." Teams identify a trend, decide what it means in that one instance, and move on. In doing so, we can lose so much of the richness of why we collected the data in the first place. But when we slow down and look at the same data through multiple lenses, we can learn much more from what we collected.

Dataspire recently created a professional learning resource centered around this very idea: using collaborative routines to deepen conversations about student growth rather than rushing to conclusions. The idea is to give teams structures that help them slow down, hear what others see, and make sense of the data together. And we wanted to share it as we are starting our new school year!

Data Doesn't Tell the Story—People Do

One of the most powerful ideas from Dataspire's resource is this:

Data doesn't tell the story—we make meaning from it.

In our experience, this is a small but really important mindset shift.

→ A spreadsheet cannot explain why students struggled with a concept.

→ A graph cannot tell us which instructional strategy made the difference.

Data gives us evidence, but it is educators—with their wealth of context and understanding of the students, classroom, and school—who interpret what that evidence might mean.

Keeping that distinction in mind can change the kinds of conversations we have when we sit down together to look at student data. Below, we share three strategies we've found helpful for putting this mindset into practice.

Also, if you're looking for additional strategies to strengthen this mindset, our article on Building Data Literacy Skills in the Classroom expands on how educators can develop stronger habits of data-informed thinking.

Strategy 1: Invite Multiple Perspectives Before Drawing Conclusions

One of the simplest routines from the resource asks educators to examine the same dataset from several different perspectives (slides 6-12).

For example:

• What does the classroom teacher notice?
• What might the student notice?
• What questions would a parent ask?
• What would an instructional coach see?
• What patterns would an administrator identify?

It's the same data, but changing the perspective can change what we notice and the questions we ask.

Thinking intentionally about the perspective we're bringing—and, just as importantly, how someone with a different perspective might see the same data—can enrich the conversation immensely. We may notice something from another perspective that we simply wouldn't have seen from our own.

This also mirrors how we know actual change happens in schools. School improvement (that lasts) doesn't come from one perspective alone. It comes from bringing together different perspectives to build shared understanding about where we are and where we might go next.

Strategy 2: Slow Down with a "Notice → Compare → Expand" Routine

One of my favorite routines in the resource (slides 13-16) encourages educators to resist the temptation to jump directly from graph to conclusion.

Instead, teams move through three intentional steps:

1. Notice

• What patterns immediately stand out?
• What surprises you?
• What questions begin to emerge?

2. Compare

• How do your observations compare with someone else's?
• Did another team member notice something you overlooked?

3. Expand

• How has your understanding changed after hearing additional perspectives?

The routine intentionally slows us down before we jump to interpretation. Hearing what someone else notices can challenge what we thought we saw—or help us notice something we missed altogether.

Strategy 3: Better Questions Lead to Better Conclusions

Perhaps the strongest takeaway from the resource is this:

Strong conclusions begin with strong questions.

Instead of asking,

"What does this data prove/show/tell us/mean?"

try asking:

• What additional information would help?
• What assumptions might we be making?
• What patterns deserve further exploration?
• What might another team notice?

These questions invite curiosity instead of certainty. And that curiosity matters because no single dataset gives us the whole picture. We need to consider it alongside other evidence of student learning and what we know about the students, classroom, and broader school context.

This strategy can also help us to distinguish observations from interpretations.

Three Ideas to Try in Your Next Data Meeting

Fortunately you don't need a brand-new initiative around this to improve collaborative data conversations this coming school year.

Instead, consider introducing one of these routines during your next team meeting.

✔ Change the Lens

Invite educators to intentionally analyze the same data from different stakeholder perspectives.

✔ Delay Conclusions

Spend the first five minutes only recording observations.

No explanations.

No solutions.

Truly just noticing. (As a note, we adults are HORRIBLE at this! But that means it's even more important to put a structure around it that pushes us outside our comfort zones.)

✔ Start with Questions

Before discussing instructional next steps, ask every participant to write one new question inspired by the data discussion.

You'll likely discover that the questions are just as valuable as the proposed next steps.

Why This Matters for Student Growth

Looking at student data collaboratively gives us opportunities to:

• identify instructional strengths
• recognize learning opportunities
• challenge assumptions
• develop more responsive teaching practices

Ultimately, collaborative data reflection isn't about collecting more information.

It's about making better use of the information we already have.

Continue the Conversation

One routine in one meeting won't change how a school uses data. But consistently creating space to slow down, hear different perspectives, and ask better questions can begin to change the conversations we have around student learning.

If your school or district is looking to strengthen how educator teams analyze student growth, facilitate productive PLC conversations, and make confident instructional decisions together, explore Dataspire's In-School Trainings.

If you're interested in bringing this kind of thinking into your school's or district's professional learning, you can learn more about Dataspire's In-School Trainings here: https://www.dataspire.org/in-school-trainings.

Keep Exploring

Interested in more ideas around these strategies? Check out:

• Critical Data Literacy: What Is It and Why Should It Be Part of Our Classrooms? – explores why slowing down our thinking leads to stronger conclusions
• Upgrade the Claim: Guiding Students to Stronger Data-Based Conclusions – discusses how to distinguish observations from interpretations