Please ensure Javascript is enabled for purposes of website accessibility The Five Building Blocks of Data-informed Instruction


We use cookies to understand how you use our site and to improve your experience. By continuing to use our site, you accept our use of cookies, our Privacy Policy and Terms of Use.


Two teachers review student work.

The five building blocks of data-informed instruction

Guest Author: Joe Siedlecki

The Guardian’s Jonathan Gray recently penned a nuanced breakdown of “What data can and cannot do.” The article isn’t specifically directed at data or data-informed instruction in the education sphere, but it calls for “a more balanced, critical appreciation of the value of data” than currently seems to be in vogue.

Data in any context isn’t powerful or valuable until we put the tools, processes, and training or supports in place for users to accurately understand it and put it into action. From our years of experience working in this space, we have come to believe that data usefulness in schools depends on having five building blocks in place:

1. Leadership commitment to set the tone in a school

School leaders set the cultures within their organizations. For the staff to embrace data-informed instruction, their leaders must visibly support and, ideally, engage in the activity of using data to inform discussions, and drive decisions about instruction and interventions.  Former Chicago Public Schools CEO Ron Huberman lived and breathed data. Not surprisingly, teacher surveys during his tenure indicated a 13 percent increase in the number of teachers discussing student performance data with their colleagues on a weekly basis. (The district also saw its greatest student achievement gains in over a decade.)

2. Data, broadly defined

You can’t have data-driven instruction without data from multiple sources. And you can’t have data from multiple sources if you’re myopically obsessed with test scores. Schools should be defining “data” to include such things as test scores, interim and formative assessments, student engagement, and student work.

3. Tools that capture information from — instead of just delivering it to — teachers

Often data tools are discussed as ways from a school system or government to “deliver data to teachers.”  If you want buy-in from educators, then flip the thinking. Implement data tools that give teachers a way to capture and analyze the copious amounts of data that they generate in the classroom every day. This flip requires schools to acknowledge and champion the idea that teachers are not just consumers of data, but are the critical generators of data on and for their students.

A few more tips on effectively integrating data tools into classrooms:

  • No one tool that solves all problems, so don’t try to find one or sell your teachers on that idea
  • Opt for tools that enable a mash-up of computer-generated data and teacher-generated data (because people trust their intuition, they will be more likely to embrace information from systems that marry their own insights with those generated by tests and/or software-driven assessments)
  • Consider using a standard data model to enable your various tools to talk to one another

4. Capacity and support to help build skills in analyzing and reacting to information

Because schools of education don’t reliably prepare teachers to use data, we now have an army of our most important school-based knowledge workers operating without adequate training in how to analyze, understand and respond to data on their students. Intentional efforts need to be made in schools and systems to build educator capacity to understand and respond to data. These supports can range from traditional professional development to ensuring that instructional coaches help build teacher data skills to having teachers actually collaborate in the creation of assessment items and rubrics for understanding student work.

5. Processes and structures to ensure data-driven techniques are a daily part of the process of teaching and learning

Here is where we see most schools stumbling. In many cases, leaders and teachers never move past the view of “data-driven instruction” as another initiative, rather than as a fundamental part of teaching and learning. In still other cases, school leaders make the assumption that teachers will find time to integrate data analysis and data-informed planning into their daily work. But our experience shows that the effort to weave data into the fabric of existing school processes and structures must be well-planned. If it isn’t, we can almost guarantee you that there will be little to no impact on student learning.

So, what processes and structures must be in place?

  • Instructional leadership and teacher teams whose discussions center on data
  • Daily and weekly blocks of time to plan instruction and then analyze student data, individually and in groups
  • Blocks of classroom time dedicated to reacting to that data (be it re-teaching, tutoring, learning lab or the like).  In this regard, emerging blended learning schools get the priorities right: the entire school day and week are built around responding to data

As a foundation, we learned through trial and error that building tools was the least of our challenges. We’re now hoping that the sector at large can springboard off those lessons, and rise to the more complex challenges of systematically building a more expansive understanding of data, educators’ data skills, data-savvy leadership, and data-inclusive processes. Who’s game?

Read Jonathan Gray’s article, What data can and cannot do.