Access is no longer the problem.
Let's begin with a little history lesson.
The very first organized school in the United States started in the year 1635 in Boston.
We can reasonably assume that on the first day of school at the Latin School, teachers took attendance. Yes, for nearly 400 years, educators have been collecting student data.
It's only been in the most recent few decades that student data has become a regular part of the educational conversation. And that is mostly due to the advent of not only the computer, but powerful student information and data warehouse systems.
Data warehouse systems have been around for decades - but until very recently, they were not accessible to small to mid-sized school districts.
But, as the terms "data-driven instruction" - or "data informed instruction" became popular, smaller, easier to use data warehouse systems (like ion) started coming into the market.
Finally, small districts had access to powerful systems.
It's funny - I remember at the beginning of one school year, the district I worked in brought a nationally known speaker to give a "start of the year" motivating talk. In it, he said "data-driven instruction is the stupidest thing I've ever heard of." The crowd went wild. He then went on to say "what we should be working toward is evidence-driven instruction."
Lots of nodding in agreement.
Now, I understand the nuance in what he was saying - but at the core, data is evidence, and evidence is data.
As educators, with today's online platforms, assessments, devices and such, we collect mountains of student data.
Recent surveys show that most teachers will use student data - when they have time. The Data Quality Campaign reports that 95% of teachers use a combination of academic and non-academic data in the classroom.
But, a staggering 57% of teachers report that they don't have the time to use the data for which they have access. 34% of teachers say there is too much data.
So, we can conclude that (whether from a streamlined, easy to use system or not), data is available to teachers and administrators, there is either too much of it - so it doesn't get used. Or, there is not enough time in the day, so it doesn't get used.
If access to data isn't the problem, then what is?
Let's use one of my favorite diagnostic tools, the "5 Whys" to dig down and see if we can understand the issue of time.
5 Whys Analysis
Why #1: Why do teachers not have enough time to use data to inform instruction?
Answer: Because using data requires many tasks that compete with instruction, intervention, planning, grading, communication and meetings.
Why #2: Why does data require so many tasks?
Answer: Because teachers must locate, interpret, and combine information from multiple data sources, assessments and systems before they can begin to interpret it.
Why #3: Why do they have to locate and interpret the data themselves?
Answer: Because most data platforms deliver dashboards, reports and charts rather than conclusions and recommended actions.
Why #4: Why are student data platforms designed that way?
Answer: Because the industry has historically viewed the problem as providing access to data instead of reducing the cognitive work required to use it.
Why #5: Why has the industry focused on access instead of cognition?
Answer: Because the industry assumed that if educators had the right dashboards, they would naturally analyze the data and act on it. In reality, getting to the dashboard is far quicker than analyzing and interpreting. Attention, not access, therefore, is the scarce resource.
Cognitive Load
Defined as "the total amount of mental effort your working memory uses at one time," cognitive load plays a significant role in our capacity as humans to operate.
A former co-worker was acutely attuned to his cognitive load. For example, he lived less than one mile from the interstate highway. It was a right turn out of his driveway, a left turn onto the next road, and then there was the interstate.
No matter where he was going, no matter how many times he had been there before, he programmed his destination into his GPS.
To be honest, as a person with a map in my head, this made no sense to me.
His argument: "why waste cognitive load on things tools can do for us."
There's something there. Can we reduce the cognitive load it takes to go from data to insight to action?
The scarce resource isn't data. It's educator attention. Current systems consume attention to produce insight. The next generation should consume data to produce insight, preserving educator attention for action.
Phase Shift
As the next generation of student data tools emerge, it's important that you ask yourself "are the tools I am using helping to reduce the cognitive load of my staff, or adding to it?"
At ion, we're laying the groundwork for a fundamental shift in how educators consume data. And that shift leads us back to emails.
Yes, emails.
Imagine a Monday morning, you've got your cup of coffee, and are about to settle into your routine. You open your inbox, and see an email from ion, titled "Attendance Brief". You click on the email and immediately see the attendance data that's important to you, along with summaries and suggestions for what to do about it.
Almost zero cognitive load. You don't have to log into a dashboard to see the data, you don't have to draw conclusions, you don't have to dig in the research to find best practices - they are delivered to you.
That's ion briefs.
In our next post, we will explore briefs more fully.
Measuring Success
For decades, we've measured success by how much data we could collect and how many dashboards we could build.
The next era won't be defined by access to information.
It will be defined by how effectively we reduce the cognitive load required to turn information into action.
Because the goal was never to create better data users—it was to create better outcomes for students.
Every improvement that reduces cognitive load returns a teacher's most valuable resource: attention.
And when educators spend less attention interpreting data, they can spend more attention changing lives.