When the first steam locomotive was unveiled to the public in Liverpool in 1829, its previously unimaginable power and speed captivated and terrified the public imagination. Some were concerned that it would be impossible to breath while traveling that quickly, while many others worried that the steam would cause the engine to explode. Once the public got firsthand experience riding these locomotives, though, these fears were replaced by appreciation for its efficiency and potential to revolutionize transportation. By 1854, 92,000,000 journeys were made each year by train in the United Kingdom alone.
In many ways, big data is like those early steam locomotives. It’s an immensely powerful tool that has already profoundly changed how the world works, but can also seem impersonal, scary, or even dangerous if not handled correctly. Student data can seem even scarier—headlines about data breaches and school funding tied to test scores can give even the most radical data evangelist pause.
So how do schools harness the potential power of student data while addressing the valid concerns around how it’s used? The answer is simple—by not losing sight of the role empathy can play in humanizing and enriching the discussions and decisions made around student data.
In a 2012 research feature in the MIT Sloan Management Review, Ritu Agarwal and Peter Weill argued that companies using both data and empathy to respond to risks can improve their chances of success in volatile environments compared to those that didn’t. In the article, the authors cite the Indian telecom provider Airtel’s use of contextual data from news reports, emails, and on-the-ground sources about potential service disruptions to help interpret and make decisions on daily usage metrics.
Agarwal and Weill also assert that using data alone to optimize business processes and make decisions can have disastrous results. As the retail chain Target discovered in 2015, after ending its failed expansion into Canada, this is entirely true. Two years previously, Target, which was already a well-regarded brand in Canadian cities near the U.S. border, opened 124 stores across Canada simultaneously. They achieved this by buying the store leases of the defunct Canadian discount store, Zellers, in order to reduce the time and cost building their own stores. But although Target had done extensive research on their own brand in Canada, they failed to take into consideration the negative reputation that Zellers had with their target audience. This negative opinion tarnished Target’s reputation in Canada and is cited as one of the central causes of their $5.4 billion mistake.
Much like Target in their failed expansion attempt, school districts have become so focused on optimizing their systems for measures of success (which in many cases means test scores), that they’ve lost their connection with the very population that they’re trying to serve. At the very least, this empathy gap can cause distrust between parents and school districts, but at worst, it can mean that school districts might make decisions that aren’t in the best interest of their students. So, how can school districts talk about and use data without losing the human connection in the decision-making processes?
Openly: Lack of access to student data immediately makes it mysterious to those who can’t see it. Parents want to know what outside vendors might be doing with information about their child, and teachers want to know how assessment data is used to rate their performance. By clearly explaining what student data is being collected and who is using it, teachers, parents, and students are given enough information to make an informed decision about their feelings.
Explicitly: Student data is a tool, not an end result. Any discussions around collecting student data—whether it’s test scores, demographics, or “checks for understanding” in the classroom—should be explicitly tied to an intended outcome. Schools should share these intended outcomes with teachers, parents, and students before the data is collected to set appropriate expectations for what can be achieved.
Constructively: Why would anyone want to collect or agree to share data that it’s going to be used against them? Student data isn’t a weapon and it should never be used as one. Once data is used punitively against teachers, parents, or students, any trust in that data evaporates. This doesn’t mean that student data shouldn’t be used to track progress or as an accountability measure. Instead, data should be used to reinforce more personal accountability measures such as classroom observations or interviews.
Sparingly: Student data shouldn’t replace conversation—it should enhance it. Whenever I watch live sports, I’m always fascinated by the useless stats and metrics presented to fill time; “Steph Curry has more points per second than any other player with a food as their last name.”
Student data is similarly used as a time-filler in meetings because it’s easier to discuss than a student’s stories or experience. By referencing data sparingly in conversations about students, the focus can remain on the individual needs of the student, rather than defining them by their data points.
Compassionately: It’s sometimes easy to forget that each data point in a database is a student that deserves a high-quality education. Without providing a human context to discussions around student data, the most important voice at the table—the student—is lost. And when we make decisions that those students, it can be devastating. Using data to reinforce individual student stories creates a powerful narrative, and puts a face to the decisions being made.
Blending empathy with data isn’t always easy or enjoyable. It often involves more difficult conversations and requires a deeper understanding of the individual data elements and the context behind them. But using empathetic language when discussing data with teachers, parents, and students can have a profound effect on the direction of the conversations and help alleviate any misgivings about how student data is collected and used. By successfully blending data with empathy, school districts can demonstrate that like the early steam locomotives, data is more than just scary, it’s scary useful.
Owen Willis (@jowenwillis) is a former special education teacher with expertise in data analysis, business development and product management.
Stay up to date on edtech.News, research, and opportunities - sent weekly, for free.