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Data Fluency Incentives for Educators

STRATEGY: Encourage data literacy and reward fluency among professionals in the school to address chronic absenteeism, academic warnings, whole-child development, and other issues.

According to the South Carolina Department of Education, “Data literacy is the ability to gather, interpret, and use multiple data sources effectively to improve student learning. Data literacy is a habit and growth-oriented mindset that is part of the culture of a school or school district. Modeling and eliciting data literate behaviors during whole-school conversations can begin building the kind of culture for which instructional leaders and teachers are able to design and select better assessments, make more accurate inferences about student learning, gauge student thinking, and engage in productive inquiry about how students learn and what instruction will help them learn.”

Data literacy is at the heart of effective decisionmaking in classrooms, schools, districts, and communities. All students, including those in need of acceleration, remediation, or intervention, provide teachers, counselors, interventionists, coaches, and administrators with a true wealth of data in various forms. Teachers and administrators who excel at using and learning from whole-child data approaches (academic, social, emotional, behavioral) to better meet the needs of their students, schools, and communities should be recognized as local thought leaders, change makers, and innovators.


Ellen Mandevich wrote that when teachers and leaders are “data literate,” they

  • Recognize empirical data over subjective, persuasive, or filtered data.
  • Evaluate the impact and effect data has on a question, topic, etc.
  • Differentiate instruction to meet the needs of all students.
  • Formulate hypotheses about students’ learning needs and instructional strategies.
  • Collect and use multiple sources of data.
  • Use formative, summative, interim, benchmark, and common assessments to make decisions, as well as student classroom work products.
  • Modify instructional practice according to the data collected.
  • Drill down to the item level to gain a deeper understanding of performance.
  • Use student work, not just tests, and other sources of data.
  • Monitor outcomes.
  • Focus on all children, not just the “bubble” kids.
  • Look for causes of failure that can be remediated.
  • Work in data teams to examine data.

In addition, education leaders can employ a “systems thinking” approach to data literacy among all educators.

First Steps to Consider

It is critically important to understand where personnel are in terms of data literacy, and effective school and district leaders work to understand that level of knowledge, as a baseline from which to work.

Presentation of the data and comfort with different presentation approaches are also important. At its core, data is information that tells a story; instead of assuming that the audience understands and can interact with the typical set of charts and graphs, for example, begin with infographics, a far simpler approach. Once staff members are familiar with that model, teacher leaders and/or administrators can share raw data with teachers, have them create their own infographics, and have them shape the data into other, more traditional presentations. It is this kind of tool creation that will build data literacy and fluency.

Another first step would be to research and integrate a data warehouse and/or school management system that can integrate multiple data sources in one place. Teachers want to be able to look at the data meaningfully, and that means having the data in one easily accessible and manageable location.

Complexities & Pitfalls

  • Assume nothing. Building a culture of data literacy takes time, effort, and personalized professional learning pathways.
  • Data literacy and analysis doesn’t mean “technology.” If the people doing the analysis struggle with technology use and integration, then using it when starting to build a culture of data literacy is the wrong approach. Use technology to leverage learning, and if it becomes more of a block than a support, avoid it.
  • Ensure multiple layers of inquiry when starting a data literacy culture. If data is analyzed and the first, immediate answer is taken as truth, then something was probably missed in the analysis. Embed a “5 Why” protocol (one that simply asks “Why?” five times in the process of data analysis and interpretation) to ensure deep and thorough conversation, examination, and analysis.

Guiding Questions

  • How is data currently interpreted, analyzed, and implemented?
  • How can this data be more easily and quickly interpreted and understood?
  • To what extent has the school or district team thoroughly examined the data? How is that known?
  • To what extent is data easy to access, manage, manipulate, analyze, evaluate, and make actionable?