Four steps to create a data-driven culture in your school district
School districts collect troves of student data, but often struggle to make data-driven decisions. Why? When this data is disorganized, siloed, unreliable, or incomplete, it becomes nearly impossible to make confident decisions or evaluations about a district’s future.
To make matters worse, district leaders and administrators often fail to realize these critical data issues may be preventing them from seeing a complete picture of district successes and areas for improvement.
Better tools and infrastructure to analyze and interpret student data help districts navigate these challenges. But the very best strategies are supported by a data-driven culture within school districts — something that frequently fails to develop in the absence of sound data practices.
Here's what this approach looks like:
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Understand the data you already have at your disposal
Building a data-driven culture starts by asking questions about the student data you already have and how it's organized. What kind of demographic data do you currently collect? What about attendance and test scores? Is this data kept in the same system, and if not, do the systems talk to one another? Through your evaluation, you'll almost certainly discover opportunities to collect or connect more data to improve your understanding of students' academic journeys. But at the end of this process, you may find inconsistencies and data silos within the district.
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Invest in tools that make data actionable
The data you find will likely live in various locations, be updated at irregular cadences, and be managed by different people. To develop a data-driven culture, you need to use all this data to create a holistic picture of the student experience. But analyzing the data to identify trends and insights requires a constant investment of time, energy, resources, and cross-team collaboration. Fortunately, tools now exist that aggregate and analyze this data for you.
Student data insights platforms like Proliftic can help your organization aggregate student data, extract holistic insights, and visualize districtwide patterns. The platform also categorizes information at various levels (e.g., student, class, grade, school, and district) to help you develop more granular insights.
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Use data to develop informed strategies
The implementation of new educational practices requires a comprehensive analysis of whole-child data. Based on your analysis, you can develop intervention strategies such as adjusting core instruction, implementing additional resources as supports or extensions to student learning, or developing lesson plans with parental involvement.
For example, when comparing student achievement across schools, you may notice that third graders in a particular elementary struggle with math comprehension. This discovery prompts you to take a closer look at other student factors like attendance, discipline records, and social and emotional data. You narrow the evaluation to focus on individual third grade classes and discover a wide array of math comprehension in each classroom, resulting in a lower grade-level average. This in turn leads you to implement a math intervention program to tailor instructional activities to each student’s individual needs.
With Proliftic, you can access a customizable bank of research-based interventions and track student growth as a result of instructional adjustments.
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Improve your teams' data literacy
To sustain a data-driven culture in your school district, it’s important to implement data literacy training into your organizational processes. Data literacy training increases your team’s comfort level with managing and interpreting whole-child data. And it can empower you and your team with the skills to develop actionable insights to better support student learning.
In addition, improved data literacy can help you standardize data practices across your district because it equips everyone with the ability to analyze and use student data. To improve your team's data literacy skills, consider offering professional development opportunities like attending industry conferences, participating in data training courses, or adding a staff member who serves as a data coach.