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Setting Up a Data-Driven Culture

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May 25th, 2017

I like to think that using data while teaching is like using a GPS while driving.

When you’re using a GPS, you enter the final destination. It’s the place you want to get to. Along the way, the GPS will say things like “Turn left…turn right…exit here,” and based on this new information, you adjust your course.

Using data to inform instruction is kind of the same concept.

At the beginning of the school year, instructors have a set of standards, learning goals and summative tests—tools that will indicate whether the students have achieved the goals of that course. But during the year, teachers need to be able to gauge student mastery to determine if the students are on track to meet those goals, or if the teacher needs to adjust course to meet their learning needs.

Using data based on student assessments—quizzes, homework, or even conversations—will help drive your students towards your class goal.

There are several different models of the data-driven instruction cycle, but I prefer one with three simple steps: Assessment, Analysis, Action.

Step 1: Assessments

According to Paul Bambrick-Santoyo in his book Driven by Data, there are core drivers that should be considered when developing quality assessments:

  • Transparent Starting Point – They should be written in advance before the teaching starts, and teachers must be able to see them—they are the roadmap. It is NOT enough to only see the standards.
  • Common and Interim – They should apply to all students in a grade level and should occur on a regular interval (e.g., every 6-8 weeks).
  • Aligned to State Tests – They should be aligned to state tests in format, content, and length, and aligned to the higher bar of college readiness.
  • Aligned to Instructional Sequence – They should be aligned to teachers’ pacing guides so that what is assessed is what has been taught.
  • Reassessed – Interim assessments should continuously reassess previously taught standards.

Step 2: Analysis

Analysis is a process that can be guided and supported by school leaders, but ultimately, that teachers need to own in order to be effective. There are certain steps they should go through before the test, right after the test, and within one week of the test.

Before the test, teachers should review the assessment and make predictions about what they think is going to happen when students take the test (i.e., were they well-prepared for the standards or not?).

Within 48 hours of giving the assessment, teachers should get a chance to look at the results. Ideally, the students are involved in this process as well. The ultimate goal of data-driven instruction is to have students work with their own data and take ownership of their learning: “Could you provide me more resources to help with this standard?”

Within a week or so, teachers should get together with their PLC, data team, or grade-level team to talk about the standards they struggled on. They should look for resources within the group, as well as determine what actions they can take to get their students back on track to meet their goals.

Key point: it’s pretty much impossible to do this without the test in hand. If the test goes away as soon as I’ve given it to my students, then there’s no feedback or meaningful review I can do that will lead to a deep understanding of what my students did and did not get. In other words, test-in-hand analysis is not one possible way to analyze student error—it’s the only way to do effective analysis.

Step 3: Action

After data analysis on the assessment, it’s time to take action and do something about the results. This can happen in several different forums:

  • PLC’s/collaborative teams – This is where a lot of conversations happen that can improve instruction. Teachers can share best practices, ideas or resources to help.
  • Observing master teachers – This can mean observing teachers in another class, school or even district. It can be logistically difficult, but it can help teachers learn new practices quickly.
  • Content-based coaching/mentoring – Similar to observations, it can leverage educators in the school or be based on external PD.
  • Experimenting with new ideas – Great results can come when teachers are encouraged to just try out new lesson plans or activities. When they know that failure isn’t punished, teachers will begin to think outside the box and produce some unexpected results.

Once you’ve taken any one (or all) of those actions, you should assess again. How did that action work? Did they learn what you’re trying to teach them? Are they now back on track?

Performing those three steps consistently, and then doing it all over again, is the foundation of the data-driven cycle.

Final Thoughts

Not using data while teaching your classroom is similar to driving while ignoring all your GPS directions. Might you get to that final destination without a GPS? It’s possible, but it’s not likely. And it’ll probably take more time than you have. Data provides the step-by-step instruction that gets you to that big goal efficiently and effectively.


Bambrick-Santoyo, Paul. Driven by Data: A Practical Guide to Improve Instruction. San Francisco: Jossey-Bass, 2010. Print.

Would you like to learn more about setting up a data-driven culture? We recently hosted a webinar that you can replay here:


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