Most educators see the start of the school year as a time of renewal for themselves and their students, full of opportunity. But quite often, the first few weeks of school are a chaotic mix of excitement and exhaustion. It can feel like a pendulum swinging between new adventures and one crisis after another.
For coaches, moving at a million miles an hour means we aren’t slowing down enough to focus on the teachers in front of us. That’s when the information around us gets distorted. We struggle to see the full picture of what’s happening in a classroom or school. Our analysis of the data in front of us becomes rushed. Implicit biases creep in. Consider the impact of a coach’s judgments based on a 15-minute classroom observation, or a coach’s assumptions about a teacher’s beliefs when that teacher publicly challenges a new district initiative during an all-staff meeting, or a coach’s sudden shift in priorities when a student complains to them about their teacher. Such occurrences can skew our perception and make us rush to judgment in ways that aren't necessarily helpful to the educator.
What’s most concerning is that our quick pace often results in a return to normalcy—and “normal” has not historically resulted in equitable results for teachers or students.
How do we strike a balance between the urgency of helping the teachers who need support and the need to take the time to ground our support in accurate information? How can coaches slow down enough to place equity, cultural competence, and antiracism at the heart of our data practices?
What We’re Hearing
We recently spoke with a few colleagues who are instructional coaches and who are caught up in the beginning-of-year hustle. They shared their excitement about coaching teachers, many of whom are “new and need a lot of support.” One coach shared, “We need to raise the bar this year to help counteract the effects the pandemic has had on students.”
Enthusiasm for hitting the ground running often means frenzied data collection—a quick visit to a new teacher’s classroom followed by a quick judgment of their abilities (Looks like Ms. Nancy is going to need a lot of help with instructional rigor this year.)
As coaches, we often know when we’re moving too quickly. We feel the pressure of our supervisors in our ears (We have to get our math scores up this year.) And we know the stakes and how much teacher effectiveness can predict a great year or a terrible year for students (If Mr. Evans doesn’t get his classroom management together in the next few weeks, kids aren’t going to learn anything.)
Slowing Down
Our new ASCD book, Equity in Data: A Framework for What Counts in Schools, outlines four steps that help practitioners engage with data in a manner that’s more culturally responsive, ethical, and effective. Below, we highlight two of these steps, along with coaching tips for slowing down our data practices at the start of the school year.
Gather Data That Matters
Start by gathering data from the teachers you’re coaching:
- Send out a coaching questionnaire with questions about their prior experiences with coaching, their needs for the coaching relationship, and a little bit about themselves. (You might share a model with your own answers to the same questions—vulnerability will build trust!)
- Hold a few introductory meetings with the teacher in which they have space to share why they teach, more about their story and how they came to teaching, how their identities show up in their teaching, and their beliefs about education. Don’t rush these conversations. It takes time to build a relationship.
Then, go beyond a one-off classroom visit:
- Have conversations with multiple students—including those you don’t usually talk with—to understand their perspectives and opinions about their teacher.
- Observe teacher interactions with students at the beginning of the day or class period. Those are the times when you’ll likely see the teacher’s relationship-building skills come alive (or not). This is when teachers don’t have to juggle instructional expectations and are focused on connecting with students.
- Engage in multiple visits to the teacher’s classroom, ideally during different periods.
- Pull together student academic (and other) data to get a general sense of which classrooms might need more instructional support.
The most accurate data takes time and comes from all corners of the school. Instead of rushing to judge a teacher’s developmental needs, triangulate the information you’re gathering using multiple sources of data. It’s important to remember to include the teacher’s stated needs and beliefs as part of the data.
Engage in Asset-Based Analysis
As you process the data you’ve gathered, bring an asset-based lens:
- Spend some time reflecting on the coaching questionnaire or early introductory meetings. Consider how your biases might be showing up in the coaching relationship, what identity-based needs might come up for the teacher, and which of their strengths you can lean into.
- Bring in critical friends—either coaches at your school or coaching colleagues from other schools—to help you make sense of the data you’ve gathered. Additional perspectives help us check our assumptions and get us to pause before we jump to conclusions.
- Disaggregate student data by race, gender, and other identity markers that might reveal inequities. The classrooms with higher rates of disproportionality might require more coaching conversations with the teacher around identity and systemic oppression.
- Disaggregate teacher data by race, specifically. Schools persistently fail to retain teachers of color, so explore ways your coaching can better engage the BIPOC educators you serve.
- When you see something you don’t like, take a deep breath. Be curious, not furious. Maybe the teacher who didn’t update their bulletin board was using their time in a different, more meaningful way—and that might provide insight into their strengths and beliefs.
As you analyze data, instead of looking for the good, bad, and ugly, try to find the great, unknown, and beautiful. You can still scrutinize and evaluate what’s right for students. You can still be student-outcome-centered. But you can also show deference to teacher self-awareness and keep an open mind; what we see at first glance is rarely the full story.
At its core, coaching is about building teachers’ capacity to be independently inquisitive about their craft, and then creatively solves the problems they encounter in their work. As coaches, gathering and analyzing data provides a perfect opportunity to model those same behaviors we want teachers to use.
Equity in Data: A Framework for What Counts in Schools
When we put equity first, we put students first. Equity in Data outlines a four-part framework that helps educators demystify and democratize data.
