Published on Real Clear Education, October 15, 2015, by Multi-Classroom Leader Maggie Vadala
This piece is the sixth in a series of monthly pieces by teachers participating in the Opportunity Culture initiative, a movement launched in 2011 by education policy and consulting firm Public Impact. Pilot schools in Charlotte-Mecklenburg and Cabarrus County, N.C,; Nashville, Tenn.; Syracuse, N.Y.; Big Spring, Texas; and Indianapolis are using Public Impact’s new job models and career paths. These “Opportunity Culture” models are aimed at improving the quality of education by extending the reach of excellent teachers and their teams, to encourage teacher selectivity, increase opportunities for teachers to advance in their careers without leaving the classroom, promote on-the-job learning, and boost teacher pay — all within regular budgets.
I’m practically a Syracuse City Schools lifetime member—from student, to teacher, to coach, then nearly into administration—but with a happy detour. I got to return to the classroom in a new position of multi-classroom leader. As the MCL, I lead a team of teachers while continuing to teach—the sweet spot for this point in my career.
But at a school new to me, in a new leadership role, with teachers who didn’t necessarily sign up for the total collaboration and openness of this team-teaching model, I faced challenges. I knew we needed to focus on data—we did need data to “drive our instruction”—and that meant sharing our students’ results with the whole team.
My school, Seymour Dual Language Academy, serves 513 students from pre-K to fifth grade, with 91 percent eligible for free and reduced-price lunch. This is a struggling student population; Seymour ranks in the bottom 10 percent on state exams. In 2015, our test results ticked up slightly—to 5 percent proficient in reading and 6 percent in math.
So we face a huge task. I set three targets: identify and address problems by analyzing data; engage in sustained professional development and dialogue about barriers to achievement; and help the team develop the capacity to question evidence and interpret results. That meant we needed to set high expectations for everyone; plan backward to align lessons; and design enriched, personalized instruction. I taught social studies or science for two blocks, using the other two blocks to co-teach, plan, observe, collect data, or debrief—whatever it took.
As I dug into the data, I realized I left one important item out: relationships! I was working with five third-grade teachers and 75 students. Altogether, the five teachers had just 11 years of teaching experience.
So while we were sharing our students’ sometimes dismal data, a far-from-comfortable experience for teachers used to working alone, I had to simultaneously build trust. They were welcoming but suspicious about my role—was I just there to run to the principal whenever they made a mistake? Where was I going with all that data? I had a group of committed people; now, they had to trust that I could guide us to accomplish more together than independently.
I needed them to see “data-driven instruction” as fundamental. My school made sure we had data analysis and data-informed planning time daily. That’s key: These structures must be well planned, or there would be little to no impact on learning. Classroom time focused on reacting to the data (such as by re-teaching, tutoring, or using learning labs)—the entire day was built around responding to data.
Selecting student work to share was the centerpiece of our group discussions. There was so much data to look at—weekly assessments, unit tests, “AIMSweb,” “Running Records,” “A-Net” and more. For me, and certainly my less-experienced teachers, it’s almost overwhelming.
Having to discuss their students’ data can make teachers feel exposed: Show them where they really stand in specific areas, and they want to crawl under the table. I chose a structured dialogue format—clearly defining who talks when, and about what—that helped manage the discussion. While at first it seemed rigid and artificial, it actually freed us to focus on struggling students and teachers.
I stressed keeping this simple: Let’s just look at the data and move forward with it. Don’t manipulate it, don’t change it. The temptation is letting it become a blame game, or coming up with excuses: “He’s special ed.” “His mother doesn’t live with him.” Structured dialogue helped us just see from the data what a student needs, and provide it.
This forced teachers to go deeper, as when one could see how she rushed to stick to a lesson plan in her 45 minutes. Instead of worrying about pacing, we needed to worry about quality, to keep students moving forward.
All that seemed promising, but we had clouds looming that point to the drawbacks of relying on the data we get. Using one daily assessment, our kids seemed to be making great progress—up from an initial 6 percent on grade level to 28 percent by the third quarter. But, as I showed our teachers in a chart that made us all queasy, according to another assessment taken three times a year, most of the kids stayed stuck where they started.
That was a shock—one we’re still analyzing. The silver lining came in how my team reacted: While upset, they immediately turned to “we can fix this.” We focused on two learning standards that we thought would best support all that we needed to work on.
One year in, we have hopes and beliefs: We believe our students will make significant progress, and we hope that data systems and assessments continue to improve, so we can trust what they spit out.
What we know is the difference this made in classrooms. The team’s teachers became aware of how to tap into the rich array of information that surrounds them—from one another, me, and the data. They drew from what their students know and can do, instead of marching through prepared lessons that may—or may not—meet their students’ needs. Through all the setbacks and challenges of working in a high-need school, they kept on pushing themselves to move forward—and we’ll keep moving our students forward, too.