A few weeks into my first year as a teacher, my colleagues and I met for our first “data team” meeting of the year.
Our principal had printed results from the previous year’s standardized tests and given a copy to each of us.
“Take a few minutes to look at the data, and then we’ll decide what inferences we can make from it,” he instructed.
He had a book with him – something with “data coaches” in the title – and was following a protocol laid out within.
I looked at the graphs, then – smiling – at my principal.
Surely he was joking.
At that point in the year, I had only five students – four third graders and one fifth grader – in a self-contained special ed classroom for kids with severe emotional disturbances. They were children who had experienced extreme trauma and abuse, and who struggled to get through a day at school without an attack of panic, rage, or violence.
All five had gotten one’s – the lowest possible score – on the previous year’s math and reading tests.
“Ms. Kennedy,” our principal said flatly, “what inferences can you make from this data? This is how we will be planning our instruction for the year.”
It was my first time experiencing the absurdity of data-driven education, but far from my last.
Several years later, I made the terrible mistake of taking a position at a newly formed charter school in Brooklyn that modeled itself on the “no excuses” design of Success Academy and Achievement First.
The school was eerily silent – the kids stiff and expressionless – and this was because according to the data, there was no time for the “scholars” to talk.
We had only a few short months to get them to score 3’s and 4’s on the state test – our goal was 90%, because that’s what other charters were doing, and anything less would be excuse-making – and so we shut them up while showing them tricks to getting the problems right on the test – snapping at times to get responses and demonstrate their obedience when our superiors walked by, and “rewarding” them with chants when they were especially compliant.
A few years later, I found myself, at the school I now work at in Maine, swimming in assessment data about my students, and was so tired of looking at crude, commercial graphs from Pearson and McGraw Hill that never told me anything I didn’t already know about my students, that I decided to take the data and enter it into a statistical software program that I’d acquired during my short time as a research analyst.
I was – somehow – still under the impression that all of this data was actually meant for me.
And so I played with it for hours, searching for some kind of worthwhile insight that might actually help me in my classroom.
And – for a moment – I thought I’d found one.
There was, I discovered, an unmistakably strong correlation between my students’ performance on one of the “math probes” we gave them periodically with how they performed on the “NWEA” exam.
I showed one of my self-made graphs to a colleague and joked that I could use it to place bets on which kids would meet their “target” on the NWEA and which wouldn’t.
Maybe, I thought, I should spend more time prepping for those probes. We had a grant for merit-pay that year, and more kids meeting their NWEA target would translate into a bigger bonus for me.
The idea, of course, was foolish – a stupid and selfish way to use data that made my blood go cold with memories from my time at the charter school.
Eventually I put the statistical software away.
A few years later, after hours upon hours spent searching for answers, I know that the data was never really meant for me.
That brief aha moment, where I discovered the correlation between two assessments, is precisely the type of “insight” that our Wall Street overlords are searching for: the programs and assessments that are most likely to generate the “outcomes” that will get them paid for their investments.
Their blood doesn’t run cold at the thought of placing bets on kids, or rigging the game to generate profitable outcomes.
For whatever reason – maybe because they are too far away from actual children – investors and their policy-makers don’t seem to see the wickedness of reducing a human child in all his wonder and complexity to a matrix of skills, each rated 1, 2, 3 or 4.
And so now, we must not only be teachers, but pretend that we are trained psychologists as well – collecting not only academic data, but data on students thoughts, feelings, emotions, beliefs.
“Social-emotional” data is rapidly becoming the new holy grail – worth millions? Maybe billions?
There are teachers who will read this and think I am wrong. They have heard the drum-beat of data-driven education since they first decided to become teachers, and they – like me, a few years back – still believe that the data is meant for them.
Data is destroying education, and we need to stop it before it is too late.