Student Centered Data: Part I

Quant Junkies | Illustration by Eric Frommelt

A few posts back, I stated that I’d been wanting to write more on the topic of data gathering, specifically in the context of John Hagel’s advice to not be over consumed by data, with Nassim Taleb’s admonition that “the more data you get, the less you will know what’s going on” in mind. So let me dive on in to it.

First off, I’m no anti-empiricist. I know that careful tracking of information and testing out of hypotheses is essential to any endeavor, whether cage fighting, teaching, or productivity.

It is no surprise, then, that a major reform effort underway in education has been the drive to use data to greater effect.

I’m in full support of “data-driven” decision-making in classrooms and schools. My beef is not with the use of data per se, but rather the instruments that are used to collect and analyze that data, in addition to the intent and purpose for which the data is gathered in the first place.

I think we can all agree that the general intent and purpose for gathering data in a school would be to determine whether a given curriculum is effective, whether one’s teaching practices are effective, or what interventions or modifications may be needed, and thus change course as necessary in response to that data. In other words, data should be used to best meet student needs.

However, a report from the State Educational Technology Directors Association (SETDA) put it this way: “Most data currently being collected isn’t captured to inform instruction; it’s used for the purposes of state or federal accountability reporting.”

Exactly. While that accountability serves a necessary purpose, that purpose should not override a school’s ability to more effectively meet the needs of its students.
Allow me to digress for a minute in order to make an analogy. I’m a runner, and have been running since I was in high school. I don’t have much interest in running competitively; I do it for the simple reason that it makes me feel good. Recently, however, I considered whether I might start training for a race–just for the heck of it. So I bought a heart rate monitor, which requires that I put a strap around my chest and wear an oversized wristwatch. I began tracking my heart rate during each run, thinking that this could be useful for pushing myself harder.
After a while, I realized that this data wasn’t very relevant to me–I’m not a hardcore athlete and I’m not interested in micromanaging my workouts. I run harder when I feel like running harder, and I ease up when I feel like easing up, so paying attention to my heart rate just wasn’t very useful for me.
I put the heart rate monitor in a drawer and haven’t used it since. It didn’t align with my ultimate purpose in running, and it wasn’t making me a better runner. Plus, it was just too much of a pain to put on. And then having to enter the data into a spreadsheet after each run . . . 
But I have begun using a tool that has enhanced my running habits. I’ve been using Endomodo on my Android phone to track my speed and distance. This has required that I purchase a little belt (it hides itself well enough to not bug me) in order to carry my phone, but other than that, all I have to do is press a button when I start and a button when I finish. I then have a wealth of useful data to examine at the end, such as the distance I ran, coupled with the breakdown of my pace for each mile, as well as the route I took. In addition, I can share my run with my social networks–not that anyone gives a rat’s touchous about my run, but even the simple thought that someone might view it compels me to run farther and faster. It’s kind of like the impetus behind writing these blog posts! Not many people will read them, but the mere possibility of someone reading them causes me to exert greater effort.
So why am I bloviating about my running habits? I think the lessons that can be drawn from this account are applicable to the use of data in public education:
  • Instruments used for data collection must align with everyday practice and purpose
  • Data gathering and reporting must be as automated as possible
  • Data reports must be easily shared
In my next post, I will examine each of these points more closely. In the meantime, please share how you use data in your school or personal life, and whether you find the lessons above analogous to your experience.

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