Towards an Empathetic Data Culture
For many educators, data might as well be another four letter word. The mistrust of data has its origins in the radical revolution of the public school system that followed the introduction of No Child Left Behind (NCLB) in 2002 (Klein 2015). As many educators will remember, NCLB put an unprecedented emphasis on standardized testing and allowed student performance to be tied to school funding and teacher compensation.
Two decades later, we are now in an era where – in spite of the legacy NCLB left behind – there is more educational data than ever. The edtech boom of recent years, coupled with the impact of COVID-19 on digital learning, has only intensified the flood of data that educators wade through on a regular basis. For this reason, it is all the more important that we move beyond the paradigms of the past and revise our relationship to education data.
The key word in this revolution is empathy: recognizing that behind the sea of numbers are individual children – along with communities who are deeply invested in their success. Keeping this as your North Star will ensure that the way your school perceives and works with data (in other words, its data culture) will never stray too far off track.
The first step is to recognize that data is far more than assessments. Where NCLB placed an emphasis on standardized test scores, empathetic data analysis sees students as people with lives beyond the bubble sheet. What is most amazing about this shift is that it opens our eyes to the multitude of data points that give us greater insight into the students who walk through our halls and sit in our classrooms. Attendance data, student surveys, socioeconomic considerations are just a few examples of the information that many educators have easy access to thanks to edtech innovation. And – as Dr. Jamila Dugan and Shane Safir preach – learning to recognize information that doesn’t come from a dashboard, but from daily interactions with students and their families, is an equally integral part of this core belief.
The second is that data should be used to ask critical questions, not come up with exact answers. The most powerful example of this that I’ve encountered involves the fifth grade teaching team of one of our schools. They noticed that a small group of students had stagnated in their reading growth, even as they continued to be the top of the class in other subjects. Rather than make assumptions about the “why” behind this lack of growth, the team set up a data deep dive meeting with their colleagues. In this meeting, they reviewed all of the students’ tests from the past year and found out that none of them were able to sound out new vocabulary. A closer look at these tests - coupled with a consultation with a speech therapist - revealed the root cause: none of these students had learned phonics. They had sailed through past ELA classes by having an above average set of sight words. In response, teachers set up small groups that focused on phonic and, sure enough, these students began to demonstrate growth in their reading. I love this example because it demonstrates how treating data as a point of inquiry leads to collaborative, creative and student-centered solutions that are easy to overlook.
The third core belief behind an empathetic data culture is that communities, context and collaboration do count. The beauty of questioning is that it is inherently communal. It is hard to ask critical questions about student data and not be drawn into interactions with the networks that support them. For empathetic data analysis to become the norm, data management needs to become more democratic, with administrators, educators, caregivers and students collaborating at all stages of the process. When these ecosystems of collaboration and care are established, it becomes much easier to treat students as people rather than as stand alone numbers because the data is contextualized.
The great news is that I have seen this shift taking place: We have seen our partner schools take their data with arms full of empathy, and ready to always assume the best of students and families. Is this student repeatedly late because they don’t care about getting to school on time? Or is their route to school dependent on two different public buses that are never on time? Another school has seen a group of students all failing a class. Instead of seeing failing students, the school asked if there have been enough assignments in that class to fairly demonstrate mastery of standards? I am hopeful that, as more and more schools take a different approach to data, greater empathy will abound.