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November 1, 2015
Vol. 73
No. 3

Eliminating the Blame Game

When we use data to dig into problems—not judge colleagues—solutions often appear.

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In many schools today, the mere word data puts people on edge. We assume the conversation will veer toward student test scores and fear we'll be judged by them. We expect statements about teacher evaluation analytics. We assume the worst.
Often, when educators think about data, we find ourselves feeling overwhelmed and disempowered. Certain phrases—and the emotions accompanying them—come to mind: invasive, evaluative, narrow, difficult to gather, hard to analyze, disconnected from the day-to-day.
What if the process of gathering and analyzing data were not only simpler, but more objective? What if our findings let us respond to a problem's root cause rather than a related symptom? And what if educators approached data in a way that helped us solve systemic problems rather than blame individuals?

A Very Human Error

When used systemically, data can make a push for change seem less personal. The issue isn't about you or me; it's about the goal we're trying to achieve.
Although this strategy sounds simple, it can be tricky to execute. Humans instinctively judge other humans; it's a survival trait. It takes careful planning and intention to avoid the fundamental attribution error. This concept, uncovered through psychology experiments in the 1960s, refers to the human tendency to fault people, not systems. Essentially, we're hardwired to overemphasize people's internal characteristics and minimize the impact of the system or situation at hand.
Consider this scenario: You're a (nearly) flawless driver. You always come to a full stop at stop signs, obey the speed limit, and maintain a safe following distance to other cars. You try hard to be considerate of others, realizing how difficult it can be to drive safely and patiently all the time. However, when someone cuts in front of you or blows through a red light, your immediate instinct is to think, "What an inconsiderate person!"
Are you correct? The data you have access to in this scenario provides a limited picture. For all you know, this driver's car is malfunctioning or the driver is experiencing a medical emergency. But it's unlikely that your first instinct would be to consider these possibilities. You'd assume the person is the problem.
Educators and school leaders can fall into the same trap when examining data. In an effort to act swiftly and decisively, we focus on what people are doing wrong. However, awareness is half the battle: Once you know your bias exists, it's easy to reframe your data-based explorations to focus on systems.

Fixing a Broken BYOD

In 2014, Mario and Kara, two leaders in a midwestern U.S. district of 12,000 students, faced a common instructional technology issue. Their bring your own device (BYOD) program was sputtering. Teachers were growing frustrated with students because they weren't bringing in the digital devices needed to engage in personalized learning—which discouraged teachers from trying the new personalized learning strategies the district encouraged. Mario and Kara partnered with our research organization in an effort to get to the bottom of their problem.
Mario and Kara had done their homework. They knew that the growing accessibility and decreasing cost of mobile devices gave most students access to devices at home. However, instead of blaming students (or teachers) for the fact that these devices weren't making it to school, Mario and Kara decided to undertake a close examination of the system operating around BYOD.
They studied how students and teachers were using instructional technology, looking at four main areas: the classroom, home and school access to technology, skill levels with technology, and the environment in the school district. Teachers, students, and school leaders all participated in the study, creating a holistic picture of the systems operating at each school. Hundreds of data points were collected, analyzed, and presented visually. Data came in many forms, including demographic data and information collected through questionnaires. These leaders took advantage of the fact that new technologies make data visualization and analysis easier than ever, making it possible for data to truly tell a story.
As they pored through infographics and visualizations, Mario and Kara discovered something unexpected: Although 95 percent of their students reported access to a digital device at home, almost half of those students were sharing those devices with at least three other family members. In short, those devices weren't always available for students to use at school.
The mounting frustration on the part of teachers and students was a classic case of the fundamental attribution error. The students weren't forgetful, as teachers assumed. And the teachers weren't resistant to personalized learning pedagogies. The devices required for the initiative just weren't available for school use within the parameters of the system.
Mario and Kara went back to the drawing board. They reduced the scope of the BYOD program and reallocated funds from some slated software purchases to bring additional netbook carts into many classrooms. As the system dynamics shifted, so did teacher and student behavior. Teachers began trying new personalized learning strategies. Morale improved.

Getting to the Bottom of a Backlog

As the new system nudged teachers to use technology in their classrooms more often, the number of tech support requests across the district multiplied. In less than two months, the number of requests assigned to each district technician doubled. Response times plummeted, and grumbles surfaced across the district. Many of these complaints were directed at the technicians themselves, eroding a long-held trust between teachers and support staff.
Once again, Mario and Kara turned to data to fix the problem. As they started asking tough questions, they were careful to remember the ways bias or blame can creep into conversations about data. They knew that the district technicians were working as hard as they could, so they turned their attention to the systems causing so many requests.
A look at the data showed that 71 percent of school staff felt that the technology support across the district was inadequate and that requests took a long time to resolve. However, more than 50 percent of staff in the district felt "very confident" troubleshooting and fixing their own technology problems. Here was a mystery: If so many people felt comfortable working through technology glitches, why were the requests multiplying?
A brief meeting with the technicians revealed that all the devices, including those recently added to support the BYOD program, were locked down—meaning teachers didn't have permission to install updates or fix small problems on their computers or their students' computers.
Aha! The fundamental attribution error was at work again. The technicians weren't ineffective or slow. The existing system simply had created a bottleneck of requests for things that teachers and students would have fixed themselves if the system permitted. The team agreed to unlock the permissions on all district machines and provide short sessions after school to educate willing students and teachers about the most common issues. Within four weeks, the number of requests—and technician response times—had returned to normal.
Again, these small nudges across the system gradually brought about the change and the culture that everyone had wanted from the start. Thaler and Sunstein, professors at the University of Chicago and Harvard Law School, define nudges as gentle influences on the options and choices at our immediate disposal. When using nudges, we don't seek to directly change a person's choices. Instead, we strive to make it easier for that person to choose the desired option, or we increase their efficacy. Empowerment through small actions yields big results.

Facing Down Cyberbullying

The final problem Mario and Kara faced with the BYOD program would require much more than a nudge. With so many students logging on and connecting each day, cyberbullying started to increase. Behavior referrals, especially at the middle school level, were almost exclusively for misbehavior on digital devices and inappropriate sharing in online spaces. As these issues permeated the classroom, teachers became less patient with students. The infamous sayings about "kids these days" rang through the hallways.
It should be no surprise that Mario and Kara again probed the data. A review of their system analysis revealed that most students were receiving only 3–5 hours of digital citizenship instruction per year. In addition, more than 70 percent of instructional staff didn't believe it was their responsibility to teach students about digital citizenship.
Realizing that students needed more education, not more punishment, Mario and Kara faced this issue head on. They used freely available resources to put together a digital citizenship tool kit for teachers and ran sessions at faculty meetings to help teachers understand that promoting good digital behavior was everyone's responsibility. The campaign culminated with a parent night at which students anonymously shared their biggest digital blunders and asked for advice and help.
By the campaign's end, behavioral referrals had decreased and almost every staff member in the schools stated that it was their responsibility to help students become good digital citizens.

The Power of Systemic Change

Mario and Kara's ability to use data as a vehicle for creating small changes to the system made all the difference. Their solutions weren't fancy or expensive. In fact, they pursued many of their most innovative solutions because funding wasn't available. Over the past three years, we've studied thousands of U.S. school districts, and stories like Mario and Kara's rise to the top. Leaders who collect data, target the environment, and execute small changes successfully see healthy gains.
If we want our districts to rise to the top, we must help every member of our organization defeat his or her instinct toward the fundamental attribution error.
Here are three strategies that can help educators avoid this error and find pathways to success.

Raise Awareness

Combating biases around data begins with awareness. When we simply make colleagues aware of these underlying human tendencies, they become more likely to catch themselves engaging in ineffective, judgmental behavior.
Creating an active conversation about using data to change systems can have a tremendous impact on a school or district's process of improvement. After teaching her leadership team about the need to guard against bias, Kara noted, "It was amazing to hear my team pull themselves out of the 'blame game' and really start thinking about change. All I had to do was name it for them."
Tip: Teach your colleagues about the fundamental attribution error. Remind team members to focus on the system before engaging in a data dig.

Search for Root Causes

Sometimes our sense of urgency and predisposition toward action lead to solutions that don't actually acknowledge the root cause of problematic data results. By digging deeper into each issue, Kara and Mario were able to uncover and target systemic inefficiencies. One strategy Mario used was to keep asking why? about any new thing their exploration revealed. Although he joked that this was the same strategy his toddler employed, Mario found that it helped him get to the heart of the matter.
Tip: When trying to determine the root cause of a problem, ask why? at least five times.

Maintain a Formative Outlook

Celebrating improvement and growth, not just success, helps everyone maintain momentum. Even the words we use to talk about our data can signal our mindsets. For example, words such as yet, beginning, or emerging can help people identify growth opportunities instead of deficits. Mario and Kara never saw their work as complete. They viewed it as an ongoing journey toward excellence.
Tip: Use a phrase like not there yet, which suggests an expectation of progress, instead of a phrase like unsatisfactory, which indicates a status of failure.
No matter how hard we try, educators can't eliminate every bias we harbor. But when we shed light on our biases, we can use data to tackle system-level issues with success. When we honor people's work and assume positive intent, innovative solutions follow.
Author's note: All names are pseudonyms.
End Notes

1 Malone, P. S., & Gilbert, D. T. (1995). The correspondence bias. Psychological Bulletin, 117(1), 21–38.

2 Thaler, R. H., & Sunstein, C. R. (2009). Nudge. New York: Penguin Books.

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