Big Brother is Judging: The Insidious Effect of Big Data & Learning Analytics in Education


I know, let’s gather all the information we can about our students.

We’ll tell people we’re using it to personalize and enhance kids’ learning experience. We’ll call it Educational Data Mining. No wait, the acronym for that would sound like someone battling to say the word ‘idiom’ – and the ‘mining’ bit sounds vaguely insidious and exploitative. How about ‘Big Data’ – that’s got a cool ring to it doesn’t it? Sounds a bit like something that you’d get up-sized with onion rings and a shake. Although maybe some astute souls might see a reference to Big Brother in there. So no, let’s keep it sober and safely euphemistic: Learning Analytics.

Here’s what we’ll do:

We’ll use Learning Analytics to gather all the data we possibly can about classrooms, students, teachers – heck even the food they eat at school and what the weather’s up to. And why not delve a little into their psyches and their experiences at home while we’re at it? And then we’ll compare this to… wait for it… standardized test and exam results. That’s the only freaking neat, quantifiable thing about education, isn’t it? Yes. Let’s do that.

Okay. Good plan so far. So what do we do with all of this information? Well, we crunch the data and use the trends we find to adapt and custom-fit instruction and learning to each individual child. That’s a good thing that. And then we use it to predict and anticipate and perhaps even control future student behavior.

More than this, we can use all of this information to diagnose kids who are at risk – academically and psychologically.

We have the computing power, the algorithms and the data – why not use them? It can only be good for education.

Except…

We’ve done this sort of thing before – albeit in less sophisticated forms. Since the Middle Ages, a host of dangerous idiots have sought to judge a person’s inner workings by external ‘data’. Witches were drowned to see of they could perform witchcraft to save themselves, the ‘science’ of ‘phrenology’ measured skull proportions to gauge intelligence, the Nazis measured the dimensions of people’s noses to judge their Jewishness and the Apartheid government stuck a pencil in the hair of people they suspected were of mixed race – if it stuck, they failed the test.

IQ tests were all the rage for a long time in education – and still are in many schools. Like Learning Analytics, they were also used to ‘customize’ education: lower IQ kids received special help, and those with higher scores we knew were capable of more if nurtured appropriately. All of which we now know, is absolute rubbish predicated on thinly disguised Social Darwinism. IQ tests cannot reliably predict intelligence, and were never intended to. Yet so many educationalists to this day persist in believing that intelligence is hereditary and can be measured objectively. Worse, this static view of genetically encoded intelligence has meant that millions of young people have internalized their IQ score and allowed it to stunt their future prospects, their station in society and the scope of their dreams.

Learning Analytics is just a more sophisticated form of trying to assess a young person’s inner workings by means of superficial, extrinsic data. The fact that they still use standardized test scores as a benchmark confirms this.

But of most concern is something that hasn’t changed since the eugenists first seized on this idea in the early part of the last century: that the intelligence (and by implication the ‘worth’) of a person is encoded in their genes. As much as proponents of Learning Analytics might tell you they want to build a more personalized model of education by measuring and analyzing everything they can, the fact that they still believe that external data can tell you about the inner workings of a young person smacks of pernicious, toxic behaviorism.

The way to improve education isn’t to measure all the possible variables more widely or more deeply. Kids are not data sets, and young minds are not easily quantifiable. If we want to improve education, we need to teach kids that they are not born with a predefined set of abilities, and that intelligence in particular is malleable and can be exercised like a muscle. We need to teach young people to reflect and learn from their experiences and show them the value of grit and determination. Instead of controlling and managing and ‘predicting’ them more closely, why can’t we make nurturing personal responsibility and intrinsic motivation a priority?

The principles behind Learning Analytics might work in business to grow markets, customize marketing campaigns and ultimately improve profits, but it has no place in schools. Education is about growing young hearts and minds, and not about stunting their growth and subtly pigeon-holing their dreams by trying to correlate external data with what’s going on inside. Learning Analytics doesn’t know kids like kids know themselves. And it never will. If we want to truly make an impact and raise confident, independent and happy young people, let’s stop trying to quantify and label them, and start empowering them to be who they want to be.

 

 

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About Sean Hampton-Cole

Fascinated by thinking & why it goes wrong➫ (Un)teacher ➫iPadologist ➫Humanist ➫Stirrer ➫Edupunk ➫Synthesist ➫Introvert ➫Blogger ➫Null Hypothesist.
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4 Responses to Big Brother is Judging: The Insidious Effect of Big Data & Learning Analytics in Education

  1. Liv says:

    But what would teachers have to *do*, then? Surely not get to know students as individual people?

  2. Michael says:

    So just to remix a little here:

    “…gather all the data we possibly can about classrooms, students, teachers – heck even the food they eat at school and what the weather’s up to. And why not delve a little into their psyches and their experiences at home…”

    “Well, we crunch the data and use the trends we find to adapt and custom-fit instruction and learning to each individual child. That’s a good thing that. And then we use it to predict and anticipate and perhaps even control future student behavior.”

    Isn’t this what teachers already do? This is the real work of teachers that you are describing, so how can it be innovative, right? 😉

    Computer algorithm just sometimes lack that human touch…

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