Tag Archives: data

What Happened?

The question “What happened?” is so basic that it’s easy to forget its importance.  It’s one of the first phrases we learn– if you don’t believe me, read for a while with a two-year old.  And like many simple but important questions, it can be difficult  to find a satisfactory answer.

But “What happened?” is really two parts– the “what” and then, separately, the “happening” that brought about the what.  If you walked to a parade and saw, for instance, this:

…you’d be able to say, probably right away, a few things:

1) There is a gorilla carrying a woman in a cage, parading down the street.

2) This town really knows how to celebrate July 4th.

You could then go on to make some observations about the cage, the woman’s clothes, the fact that this is probably a person in a gorilla suit, etc…. But you wouldn’t as yet, be able to tell why this spectacular scene is before you.  It is a political statement?  Modern Art?  A revolt at the zoo?  David Lynch’s retelling of Goodnight Gorilla?

In other words, you’d know the what, but not the what happened.

With schools and data, it’s easy to get lost in the what.  Take, for example, this graph:

Observations, Unit 1

If we take a look at this performance of, say, all the science teachers in a school over a 6-8 week period, there’s no shortage of “what” to dissect.  You can pull out some conclusions of your own, but here are some highlights:

– the teachers tend to plan lessons well

– teachers walk around a lot and have good rapport with kids

– everything looks safe and well-organized

At the same time, however…

– formative assessment doesn’t seem to be happening much at all

– assessment in general, but especially higher-order and self-directed           assessments, seems to be a weak area

And this is all good.  We’ve successfully identified that whats.  We know there’s a gorilla and a lady in a cage, and we know what these teachers have and have not been observed doing.  But what we don’t know is the whywhy are we seeing the things we’re seeing?

This is where story comes in.  To be a good storyteller, you have to know what happened.  You have to know, for instance, that this is a school where there were rampant discipline problems 10 years ago, and the most important thing was for teachers to get control of their classrooms– more important than performance on any assessment.  And the school hired supervisors who cracked down in specific ways– teachers who had their plans in on time were rewarded, and those who could demonstrate the easy stuff– like walking around the room and being nice to the kids– were left alone.  No one cared about “messy” formative assessment and checking for student understanding because the administrators believed that the more work the teacher gave to kids, the busier they’d be and the better they’d behave.  And now, 10 years later, the teachers still show these behaviors, even though the school has changed a great deal, but they’re still teaching the kids from 10 years ago.

A graph like the one above is like a movie still.  If I see this picture, for instance:

… I think that this is a movie about a prince and princess falling in love.  But if I don’t see this, too:

… I’m missing a lot of the story.  And that’s not even to mention all the stuff with the dancing cups and candles and stuff.  We’ll leave that out for now.

To use data effectively, we need to know what happened.  And that involves digger much deeper than we’re accustomed to.  It’s not enough to look at presented data, make some observations about what we’re seeing, pat ourselves on the back, and say “Let’s stop doing that!”  Knowing why we’re seeing certain data– what happened to make the data even be there is the most important part of telling stories with data.  Only then can we begin to use data to change the way things are, and write the story of what will happen from that point onward.

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The Reflex

“The reflex is in charge of finding treasure in the dark
And watching over lucky clover isn’t that bizarre
Every little thing the reflex does
Leaves you answered with a question mark”

– Duran Duran

That’s right.  I opened this post with a quote from Duran Duran.  Breathe it in.

I won’t pretend that I often seek the wisdom of the sage and stylish Simon LeBon. But in this case, the lyrics point to a larger truth– white jeans and mime shirts are hot   reflexive actions have the the potential for significant impact.  At least I think that’s what he’s trying to say.  Although I’m not sure about the lucky clover… I think that’s just the 80s talking.

The title of my position is “data specialist.”  That’s the kind of title that leads people to ask exactly what you do, given that I don’t have a formal IT background and I’m an English teacher at heart.  I tell people that my job is all about getting teachers and schools leaders past “We have data and don’t know what to do with it,” and closer to “We know what to do with it.”  But that path is something that I had to conceptualize in a way that made sense to people.  The educators I worked with understood that the most effective thing they could do with data was analyze it, present it in ways that made sense, then find ways to act on it within the confines of their school– and, if necessary, work to loosen those same confines if they could.

I often discuss the concept of becoming data reflexive.  Too often, “data” is something done in bursts, on special days, when the consultant comes in, or when someone’s looking.  It usually involves consulting binders full of charts, making teachers fill out data protocols and hand them in to supervisors, and arguing about having too many or not enough tests.  When data is something that’s done in discrete chunks like this, it’s like p.d. that you go to for one day and then go back to your classroom and never use– without sustained interaction and reflection, it’s never gonna work.

Data reflexivity, though, represents the idea that, when making a decision, an educator reflexively turns to data in order to inform that decision.  Data isn’t an awkward appendage; it’s the source code, so to speak, of what’s happening in the life of a classroom, a school, and a district.  A programmer knows that when software isn’t working, go to the code and de-bug.  That’s a reflex– the same can be said for a teacher re-stating directions when a students says he doesn’t understand or a counselor closing the door and offering a tissue when a student comes in crying.  Those actions are reflexes, for the most part– that behavior isn’t so much learned like you learn how to solve polynomials.  In the same way, teachers that use data reflexively always think of what’s happening in class as an endless source of data to be taken, and can switfly and fluently collect and analyze data and use it to inform what they do next.

Of course, data isn’t just numbers or performance on a test.  “Constantly collecting data” doesn’t mean over-testing, and it doesn’t mean becoming a robot about students’ lives.  We collect data all the time without being conscious of it– when we meet someone, we feel out their mood, their trustworthiness, their personality; all of these things are sources of data.  That’s important to remember since too often, “data” only means performance, and only on certain tests, at that.

Ultimately it’s the reflex to turn to data to inform fundamental questions like “What do my students already know,” “What things that I do resonate with my students most,” or “What do students of difference ethnic groups think of their school experience” that marks true data reflexivity.  Using data can be as much a behavior to shape as it is a concept to understand– my hope is that thinking about it as such can remove some of its mystery.


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