“I just go with my gut.”
A colleague said this once in response to a data question during a planning meeting. The comment wasn’t flippant – it reflected something deeper: uncertainty, discomfort, maybe even fear. It’s not that teachers don’t care about data. It’s that many of us were never really taught how to use it beyond inputting grades or checking test scores. But in 2025, this isn’t good enough.

In today’s schools, teachers sit at the front-line of a data revolution. From algorithmically generated dashboards to parent-tracking portals, from student learning analytics to behavioral flags – data is everywhere. But most of us are trying to make sense of it without a road map.

So let’s discuss what data literacy really is. We need to understand why it’s urgent. It’s important to learn how to stop being passive consumers of data. We must become active, empowered professionals who use data to drive equity, agency, and instruction.

What Is Teacher Data Literacy?

According to Gebre (2022), data literacy in education is often narrowly framed as a technical skill. It involves being able to read and interpret student scores, track trends, or input grades. But that’s only one slice of the pie.

Gebre outlines four broad conceptions of data literacy that apply directly to secondary teachers.

If you’re only leaning on the first one, you might be missing opportunities. These opportunities include teaching more powerfully, advocating for student needs, and protecting your own professional integrity.

Why It’s Urgent And Not Optional

Education is increasingly governed by algorithms and metrics. “Data-driven instruction” is in every policy document. Edtech platforms offer real-time analytics on everything from reading comprehension to emotional regulation.

And yet:

• How many teachers know where this data goes?
• How many can spot flawed metrics or misapplied benchmarks?
• How many feel confident pushing back on reductive interpretations of student performance?

According to Gebre (2022), instructional approaches are still too focused on deficit-based models. Teachers are told to “fix” low scores without context, question, or agency.

We cannot afford to be passive. As educators, we must understand how data shapes instruction, assessment, and accountability. We must also comprehend how it affects our students’ lives and identities.

Practical Ways Teachers Can Build Data Literacy

Here’s how to move from overwhelmed to empowered:

1. Start with Your Students’ Stories, Not Their Scores

Combine quantitative data (grades, test results) with qualitative evidence (student writing, conversations, surveys). Ask: What does this data not tell me? What context is missing?

2. Use Data to Ask, Not Just Answer

Instead of jumping to action from a score drop, frame questions:

• What patterns do I see across class demographics?
• Are boys consistently underperforming on creative writing tasks?
• Do ELA students need different scaffolds?

Data is a conversation starter, not a verdict.

3. Learn Together

Join or start a PLC focused on data use. Frame meetings around inquiry cycles (e.g., what does the data say, why might that be, what can we try?).

Teaching Data Literacy = Teaching for Equity

When data is used uncritically, it reinforces stereotypes and masks bias. But when we use it contextually and ethically, it can spotlight systemic gaps and push for change.

For example, if students identified as gifted are rarely being challenged, it may not show up in test scores. However, a data-informed inquiry could reveal this pattern. That’s why Gebre (2022) emphasizes the importance of “context-oriented data literacy.” Data should not just be analyzed. It must also be questioned, contextualized, and humanized.

Sources

• Gebre, E. (2022). Conceptions and perspectives of data literacy in secondary education. British Journal of Educational Technology, 53, 1080–1095. https://doi.org/10.1111/bjet.13246

Join the Conversation

This isn’t about turning every teacher into a statistician. It’s about reclaiming data as a tool for learning—not compliance.

So ask yourself:

• How do I define data in my classroom?
• Whose stories are told – and whose are hidden – by the data I use?
• How can I grow in data literacy this year?

Let’s stop fearing the spreadsheets and start owning the story behind them.