Data is a messy word. Some think it’s just numbers used to complicate education. Others think “I’m not a math person” and therefore avoid it. Others still cannot go without it because they’ve been taught “data-driven instruction” without ever being taught what that means.

In my time as a “data guy” for my school, I have seen many things [cue distant, melancholic stare into sunset]. I have seen a professional development session go awry because I mentioned “standard deviation” without any explanation. I have seen someone look at a 33-column spreadsheet and assume this was not going to help them. Most importantly, as was the case in my Impact Team work with teachers Ashley Gorgoglione, Frank Gambardella and William Gallagher, we have seen data tell us we needed to do better.

Here are five things I learned from this project that I always try to remember about data.

1. Data is not just numbers.

Not every teacher is trained in numbers, and certainly not trained to analyze data. Beyond basic mathematical functions, I am not trained in it either.

But one of the easiest ways to strip away the beauty of data is to reduce it to testing or assessment scores. “65% of students failed this test, so I need to redo it” is not a helpful way of thinking because it tells you nothing about why the students did how they did.

In our project, students had a choice of assignments; some were picked regularly and others were rather bluntly rejected. Had we gone simply with scores, we would have seen, “100% on Assignment A, 20% on assignment B. Clearly, they need more work on B.”

In our data collection, however, the plurality of students mentioned that they picked assignments from a menu because they thought the assignment would be interesting. Not easy or difficult, mind you; interesting.

This data was more relevant to our purposes than the students’ scores: students wanted assignments that were interesting. “More creative tasks,” or some variation of it, was the common theme. This meant that in our second attempt, we were required to think creatively and come up with things that might be fun. We even gave students the opportunity to make their own assignments so engagement would go up.

Had we looked only at assessment numbers, we would not learn why students picked some assignments and others had such atrocious results. We needed to go beyond the numbers and into the real data. And the real data was blunt: we were boring our students.

2. Data is not difficult to collect

As someone who has a fondness for educational technology, one big change that I hope survives our time in remote learning is the digitization of class materials. Even when we return to buildings, teachers should not forget that they have learned so much about technology and done so many wonderful things with it. And one of the best lessons that I hope teachers have taken is that technology is actually great for streamlining the process of collecting instructional data.

Google Forms is a great tool for quick student feedback. Assignments done in Forms come with detailed Sheets files for reference. Those files, in turn, can be sorted for data rather easily. Forms even has built-in graph and chart tools that automatically produce visuals that are immediately telling, like the ones below.

Even if you’re not comfortable with data software, there are tools that can help you get some really decent ideas immediately. This chart, for example, told us clearly that students were picking assignments based on interest. Had we collected this via paper, we would have had to do considerably more work to tally these results and make this chart; with Forms, this was generated automatically.

So, keep digitization alive, and the data will flow.

3. Data is readily available

Speaking of data: you do not need to rush into creating your own surveys. Most school districts actually keep data that is detailed beyond our wildest imaginations. Exam data? It’s there. IEP data? It’s there. Student satisfaction surveys? They’re there. You can even find how each student did on a state exam, down to percentages for every single question.

So, if you ever want to understand your students better, there are resources for you. With even a basic knowledge of data, there is much to look at.

4. Data is at the core for instruction

So, with all this in mind, it should become clear—data-driven instruction is the way to go. The only way your classroom can be engaging to a variety of students is if you actually listen to what they are telling you.

For example, in our most recent assignment, the plurality of our students said they wished for “clearer instructions” and “simplified tasks.” Therefore, our second draft needed to provide—shockingly—clearer instructions and simplified tasks.

With this information, our second draft’s entire layout changed, emphasizing readability and clarity in what choices students had. We even felt comfortable assigning far more challenging tasks because we now knew we were providing clearer instructions.

The clarity of precisely what you students need can come only when you look at the data that actually incorporates your students’ voice; it is the strongest metric that should drive your thinking.

5. Data needs to be made digestible—and then actionable

Some people “get” data. They can read numbers and make sense of them. They are not thrown off by multiple percentage points in the same sentence.

But not everyone is one of those people. That’s why everyone from multibillion dollar organizations to schools have “data people.” Not everyone “gets” data.

And that is why it is important that, as a data person, you know how to process your analysis in a way that is easily digestible and actionable for your colleagues.

Let’s look at this sentence: “74% of our students scored less than 65% on Standard 7A, with as many as 53% scoring below 50%, the latter of which is actually an increase of 5% from last year’s students on the same performance standard.”

This is the kind of statement that I generate in my first draft for a data report. And to anyone who will give me the time of day, I will gladly explain it to them. For the rest, I will condense it to: “most of our students are not doing well on standard 7A, so let’s brainstorm some strategies to teach it.” Not doing so would result in people completely zoning out when I’m explaining my rationale behind my suggestions.

Learn to simplify data, or you will lose people. If you want people to take action, make your data analyses easy to follow.

So that’s it. Hope you enjoyed my very quick introduction to lessons I took from my project and my time as the data guy. If you have any questions, feel free to reach out and I will help to the best of my ability.

And if you like this article, be sure to share it with your colleagues. Because more readers mean more hits on the website’s metrics page, which tells you how well I did on this blog post—-hey, wait a minute…see how easy it is to fall into this trap?!