Using Data to Make Meaning

Using Data to Make Meaning - Principal Tribe
Home » News » Learning and Teaching » Assessment » Using Data to Make Meaning

What meaning is tucked away in your school’s data? How do you pull that meaning out? Most importantly, what narratives do you tell by using data to make meaning?

In this article, Jared Roebuck Francis reveals a recent protocol used by his school and district as they use data to make meaning and construct a narrative that leads to greater student success.

Meaning Making for Change

A few weeks back, at the end of semester one finals week, my leadership team was joined at our weekly by our data team and our network superintendent. The purpose of the meeting was to review various pieces of data and begin preparing for a rapidly approaching Data Day at our school.

The data team presents our team with results from 9 different exams, GPA data broken down by course and cohort, as well as results from a tool we use to measure the social and emotional (SEL) development of our students. We review each piece of data, and start to ask ourselves several questions:

  • What trends do see emerging across departments?
  • Are there consistent patterns within a particular grade band?
  • Is there any correlation between student grades and assessment performance?
  • What does the SEL data reveal about the environment we are creating for students?

We consider these and many other questions, as the picture of the health our school begins to emerge.

As the picture comes into focus, I start to hone in the meaning of the data. I seek to understand the story it reveals.

This narrative will be critical to sparking the changes in our practice that will be necessary to move students forward in the coming weeks.

Data on the Long Cycle

At our school, we think of data as occurring on “short” and “long” cycles. These data are used for different purposes and help us construct a more complete story of our school. Both data sources converge on Data Day.

Short Cycle Data

For example, teachers are consistently collecting and acting on data from students in their day to day work. Exit tickets may inform a minilesson the following day. A review of student writing may prompt the need for a peer revision activity in for an upcoming performance task. These are examples of data on the “short cycle”.

Long Cycle Data

The mid and end points of a semester represent the “long cycle” of our data-driven practice. Midterms and finals create opportunities to assess our impact on student learning.

While analyzing performance on these assessments is critical, we know that they only provide a limited view of how students are progressing. Therefore, we use these junctures to reflect other indicators of student achievement including GPA data, levels of engagement in extracurricular activities, as well as data on social and emotional learning (https://helloinsight.org).

By looking at a broader range of data, we capture a more holistic and sharper snapshot of our schools’ performance.

Data Day

The long cycle begins and ends at Data Day. Data Day starts with an all-staff meeting to present and discuss data from across all of the measures described above. Everyone sees everyone’s data because in the end, the data belongs to all of us.

After the launch, we break into department teams. Teachers and instructional leaders analyze their exams and begin to action plan based on their findings. Our operations and culture teams review attendance, culture, and SEL data to initiate their action plans.

Finally, we come together to prepare for family conferences. The staff members that serve as student advisors review each of their advisers cumulative GPA, current academic performance, and SEL data in preparation for the conferences.

Numbers Need Meaning

Throughout midterms and finals weeks, as teachers begin scoring exams, I can always expect a visit from an anxious teacher or leader. As soon as their exams are scored, teachers quickly sign into our assessment platform to begin picking apart the data.

Sometimes, a teacher will spend the entire week feeling defeated based on their initial impression of the data. I take this opportunity to remind the person not to read the tea leaves. There is little use in making too much of any single data point.

We all occasionally fall victim to over responding to our initial impression of assessment results.

But our initial response isn’t helpful in terms of making strategic changes to practice, because reacting isn’t the same as analyzing. As school leaders, this is particularly important, because responding in this way prevents us from doing our critical role as meaning makers.

If our goal is to have a holistic impression of how our students are doing, no single data point will reveal it to us. Ultimately, the numbers need a story. They need to create meaning for our teams:

  • What does the data tell us about where we are?
  • Where we must go moving forward?

As the principal, it is my responsibility to present answers to these questions that prompt our team to reinvest, recommit, and take action.

The narratives that principals and school leaders tell pull and give meaning to student data.

Creating the Narrative

Back to the Data Day prep meeting. In reviewing the data, afew points stood out:

  • In both 9th and 10th-grade, we saw significant growth on assessments aligned to end of year Regents exams. While we still weren’t meeting our end of year performance goals, we were moving in the right direction. In some cases, we saw 20% growth in overall student performance from the midterms assessments.
  • Student GPAs were closer to our school goals than ever before, with the majority of our 9th-grade cohort having achieved at least a 2.7 GPA.
  • On SEL measures, our students demonstrated more growth at the midpoint in this current school year, than we did the entire previous school year—exceeding our end of year performance goal months in advance.
  • Our 9th grade cohort continued to underperform in math and was not making the kind of progress we were expecting in ELA.

What did all this mean? What narrative did our team need toalign on?

Across the data, we found evidence that the team hadresponded to our message coming out of the Data Day that followed midterms. Mymessage to the side then was:

“This is the first pivot we’ll need to make as a team. While overall the data is comparable to our performance year over year,  we should not be satisfied with that outcome. We are a stronger and better school than we were a year ago—so we should be doing better than we were last year. When we pivot we make adjustments to our practice to meet the needs of our kids. If we don’t pivot, our kids won’t reach the goals we have for them or the dreams they have for themselves.”

Looking at the end of term data, I saw that my team had responded to the call to action. More than that, in the previous eight weeks I’d seen our team develop in significant ways.

Our instructional leaders were becoming better at coaching and support teachers. Our grade teams became more consistent in implementing common practices and expectations. Most importantly, students had started to invest more in their academic performance and our school culture.

Given the overall positive growth, there was still the pressing need to make progress in a few critical areas. The narrative that emerged from the meeting, which I delivered at Data Day 2, was simple:

It is time to step on the gas.

Leaders Make Meaning to Make Change

On Data Day my role as the school leader is to tell ourstory. My Data Day launch presentation didn’t just share our collective data.It told our story:

We are a team that met an initial challenge and we are a team that has demonstrated the capacity to tackle even bigger ones as we move forward.

In other words, it was time to step on the gas.

As school leaders, the narratives we provide not only make meaning out of the data, they create the basis for our next actions, influence organizational culture, and recommit our teams to the high expectations we have for ourselves and our students.

Leave a Reply

%d bloggers like this: