Tom was one of my best English teachers — compassionate, dedicated, brilliant. He came to me frustrated about Mario, who could chat easily in English during class discussions, but he wasn't completing any reading or writing assignments. "He speaks English fine," Tom told me, "so he must just be lazy." We tend to think like this as educators. We see a behavior and make a quick judgment. Student is late? Must be lazy. Not turning in work? Doesn't care. Causing trouble? Bad attitude.
I get it. We have hundreds of students and very little time. Sometimes we need to make quick judgements, but these quick judgments should be checked against data. And here's what's interesting: the same teacher who calls a student lazy for being late will walk into professional development twenty minutes behind schedule and have a perfectly good reason. "I was helping a student." "There was traffic." "My mother's sick." We want people to understand our circumstances, but we rarely extend that same understanding to our students.
That's the attribution error in education. We blame students' problems on their character while excusing our own behavior because of circumstances. But what if we're missing the real story? What if data could show us what we're not seeing? When we let data guide us past our quick judgments, we discover truths about our students that transform how we teach them.
Misreading Students: The Cost of Ignoring Data
Tom's discovery about Mario changed everything. When Tom gave Mario the CELDT (California English Language Development Test) himself instead of passing it off to a coordinator, the results shook him. "I had no idea!” said Tom. “Mario is basically illiterate in English." Like many of our students, Mario had picked up enough English to get by in conversation, but he was lost when it came to academic reading and writing. What we'd labeled as laziness was actually a language barrier we'd failed to see.
This pattern kept showing up. Brian, one of our physics teachers, refused to hold a circle discussion after a student death. "The students don't need it," he said. He had no idea the victim's three cousins were sitting in his class, silently grieving. He saw their withdrawal as disengagement until the data showed us their connection to the tragedy. What looked like apathy was actually trauma.
We could address these situations quickly because we were tracking comprehensive data about our students. When Tom came to me about Mario, I could immediately look at his language assessments. When Brian’s students seemed disengaged, our regular tracking of family circumstances and trauma indicators revealed their connection to the tragedy. The data we collected — from language proficiency to health access to school safety concerns — gave us insight that moved us past assumptions to understanding.
What Straight As Don't Tell Us
This same data tracking system revealed stories we might otherwise have missed. Our high-performing students seemed just fine based on their GPAs and attendance. But our school experience surveys and mental health surveys told a different story. Some of these "perfect" students were scoring between 18 and 24 on our trauma scale — and 24 is the highest trauma score a student can get.
Looking at all our indicators together made things clearer. We could see when a student might have excellent grades but no adult on campus they trusted. Or when someone was acing tests but hadn't had access to basic healthcare. Some were maintaining a 4.0 GPA while dealing with intense anxiety or depression that nobody noticed because their grades never slipped.
It's like what I learned when tracking graduation credit histories — just because a senior has good grades doesn't mean they're on track to graduate. You have to look at the whole picture. Some students maintain perfect attendance, get straight As, but they're silently struggling. If you're not looking at all the data points — from how safe they feel at school to whether they have an adult they can talk to — you might create a great solution to a problem that doesn't exist or simply miss a problem all together.
This data changed how we supported all our students, not just the ones who were visibly struggling. Because sometimes the students who look like they need us least are actually carrying the heaviest loads.
The Right Data Leads to Real Solutions
Understanding what our data really meant led to surprisingly simple solutions. For example, a group of girls wasn’t coming to first period. When we looked at our safety data from the school experience and mental health surveys, we discovered they felt unsafe walking to school. Young men who didn't work were hanging out along their route, harassing them. The solution? We had our school police officer park his car on that side of the school instead of the front. That's all it took.
When students were frequently absent, our data often revealed they hadn't seen a doctor in years. Instead of punishing them for missing school, we brought a mobile clinic to campus. Students could get basic healthcare without missing an entire day waiting at a free clinic.
Our trauma scores helped us allocate resources where they were really needed. When data showed near one hundred students dealing with high levels of trauma, we could prove we needed more mental health support. One PSW wasn't enough. We needed one for each grade level. Looking at the real needs behind behavior changed everything about how we responded to students. We weren't looking to excuse student behavior, but to understand and heal what was causing it.
The data kept showing us that what looks like a student problem is often a system problem. Once we understood what students were really facing, we could be strategic about how to support them. That's what good data does — it helps you build solutions that actually work for students.
From Numbers to Understanding
Without data, Mario was just another student not doing the work. With data, we saw what he really needed. Mario illustrates the choice we face every day as educators. We can trust our quick judgments or we can look deeper. We have to ask ourselves: Are we looking to judge or to understand, to heal or to punish?
I've learned that data isn't just about numbers. It's about asking the right questions. Why is this student really late? What's behind that perfect grade? What's causing that behavior? Sometimes we need to understand what looks like a character issue is really about circumstances — just like when we want others to understand our own situations or actions.
I used to think knowing my students meant caring about them. But caring without understanding is like treating a patient without running tests. You might have good intentions, but you're still guessing. Data gives us the ability to be precise. Data takes us beyond what we think we know to what we need to know. And in education, that's everything.
Our students don't need our assumptions. They need us to see them for who they really are: not problems to be solved, but potential to be realized.
Ready to Transform Your School's Data Story?
Let's work together to create a data system that reveals instead of reduces, that illuminates instead of isolates. Whether you need a full-day workshop on building effective data tracking systems or a keynote to inspire your staff to see beyond the numbers, I can help your school develop a data culture that changes lives.
Contact me to start the conversation about:
Creating efficient data collection systems that tell the full story
Training staff to gather and use meaningful student data
Building advisory programs that deepen student understanding
Developing data-driven solutions that actually work
Let’s bring data with soul to your school.
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