We are all machines. Or, more accurately, our brains are the ultimate technological marvel, effortlessly performing tasks that we struggle with in most other venues. The human brain is a finely tuned and integrated solution, collecting data about the world from all of our senses and producing both reaction and prediction about what comes next. It is the ultimate “Integration Engine.” And though it is so personal to all of us, our work has struggled to find systems that can begin to approximate the power of the brain.
This struggle was made clear to me back in 2005, in a former school district. During a presentation to my board of trustees, one trustee, a banker, suggested that what we needed was a student achievement “credit score.” Basing the idea off of the concept of the consumer credit score, it would be a reflection of a number of data points about a student, measured against the performance of others with similar academic and behavior traits. What this trustee was suggesting wasn’t earth-shattering. Instead, it was a rational request based on the volume of information we had about students and the potential to predict what would happen and, hopefully, intervene where necessary.
The challenge we had wasn’t conceptual. It was technical. And that is where many school districts struggle today. Understanding the value of data and its predictive capability is part of our everyday lives. Collecting meaningful data and forming it into something actionable is the tactical step we must take that has so long eluded us. What I believe is missing in this process is an understanding of how to bring solutions together, identify the right data at the right time, and frame the results in terms of student growth.
To begin to solve this problem, we first have to understand the challenge of data distribution. While all schools have centralized ‘master’ data systems, think SIS and ERP solutions, these systems do not encompass the wide variety of data-based requirements in schools. Some systems attempt to be ‘all in one’ solutions, but, more often, schools look for best-of-breed, or solutions that have been vetted to meet their unique needs. That may or may not be a single solution or set of solutions. Often, it is many, and each system carries with it a separate set of requirements for data capture and management. Solving this problem has been an educational white whale, or nearly unachievable dream, for decades. Countless initiatives have been advanced to try and solve this, from state-level data management systems to protocol definitions. Nothing has transformed the landscape yet, either because the solution was incomplete, or because the market and technology evolved, and a “better” solution was just beyond the horizon. The unfortunate reality, though, is that other fields have solved this problem already, and have both standards and technologies in place to ensure that data moves elegantly, reliably, and securely between systems. Do a simple web search for “integration engine” and you’ll see all the other industries that have figured out how to standardize the exchange of data between systems. That we lack a common approach in education is more than unfortunate, it’s borderline irresponsible, given the potential for data to inform quality work with students.
Integrating data, however, is simply the middle stage of a three stage effort to produce a better learning environment for students. First, we must start by shifting our data conversation to one of quality over quantity. Too often we are focused on datadriven decision making, and that focus leads us to gather all the data we can, from all the possible locations it resides, and to put all of that in a data warehouse and dashboard solution that, from the outset, confuses and complicates the issue.
I’ve personally been in environments where district leaders are presented with lengthy and data rich spreadsheets, with very little to connect the numbers on the page to real-world results. It’s one thing to know the standardized test scores of every student in the school for the past ten years. It’s another to filter that down to just the information that allows us to make a decision. One is reflection, the other is action.
We need to shift the conversation about data collection away from data-driven decision making to decision-driven data collection. Let’s first figure out why we collect data, the outcomes we are striving for, and then go out and assess and gather that information. Let’s populate systems with meaningful data that allows educators to focus on results, rather than on becoming data scientists, which is what most solutions encourage by default. Find me a teacher who wants to learn about advanced statistics, and I’ll show you an advanced statistics teacher.
After we collect the right data and foster it into an ecosystem of free data exchange, we can begin to use it in meaningful ways. Analytics is easy. Or, better said, it is relatively easy, compared to the job of transforming analytics into something with real world meaning. Showing data that reflects where we’ve been is pretty standard fare. I’d argue that this is one of the earliest drivers of technology in schools, and that it remains the hallmark of much of what is sold. We are surrounded by data, and almost all of it is reflective.
How do we elicit meaning from data? We turn to predictive analytics. A thorough examination of predictive analytics is outside the scope of our conversation here. A quick primer, though, might help put the value of predictive analytics into perspective. Where analytics derive value from understanding where we’ve been, predictive analytics is used to make predictions about unknown future events. With the power of predictive analytics, it is possible to start building models of what today’s belief actually means for the future. It allows us to leverage the inherent value of large data sets, with historical connections, both correlative and causative, in full view. Where one sliver of that data holds little predictive value, the entirety of the data set opens up new possibilities.
This is what we value when we value things like “data”, and “integration”, and “analysis” in education. It is always important to look back, evaluate our past practice, and learn from it. For today’s students, we are afforded no luxury to take our time and assess long-term historical trends. Instead, we need to cast our glance forward, to mine data that is connected to our real questions and goals, and to begin making predictions. Will a change in this reading program increase comprehension levels amongst our most remedial students? Will that after-school program reduce in-class behavior issues at our middle school? This is what we want to know, and what is responsible to ask for today’s students.
In the end, we must follow the mantra: analyze, predict, act. Be careful in your analysis, ensuring that only quality data, data that matches your purpose, is used. Use decision-driven data collection. Then integrate that data with information from a variety of sources. Look for easy solutions here – openness, flexibility, and an intrinsic ability to work in your systems. Predict the outcomes, attempting to understand how your decisions today impact the students you have now.
Be intelligent consumers of predictive analytics, using them as one tool in your toolbox for creating a better learning environment. Use the power of the vast amount of data you have to understand better the choices you make.
Finally, act. Do something for your students now, and don’t wait for historical data to tell you what to do with the next generation of students that passes through. Lead with passion, intention, and purpose. Leverage the great work you’ve done to find the right data, bring it together, and draw predictive conclusions about your students work. It matters to them as much, or more, than it matters to you.
In the end, create an ecosystem that encourages this kind of quality throughout the organization, focused on conversations informed by the right kind of data, not just any data. By doing so, you’ll find that a difference is made today, for the students you see in the halls right now.