Data: almost useless as an agent of change?

The comedian Mae Martin makes a great point in her BBC Radio 4 NOW show routine on addiction (30/03/2018).

“Give me a cheer if you’ve ever read how your smartphone might be bad for you.”

And of course the audience cheers

“We know, we’ve read the articles, we know there’s potentially harmful radiation, our attention spans are getting shorter, social media is a parody of human connection, we’re all getting lonelier. We know, but we’re like “my friends live in my phone”. And the colours are so bright and the sound’s so nice in my ear. I’m very bad, if I had 8% battery in my phone … if I needed a charge, I would unplug someone’s life support machine.” 

Brilliant gag, but perhaps like all good comedy, it’s essentially true. Why the hell can’t human beings use data and connect it to change?

  • Obesity: There’s really clear data on obesity. If you eat more more calories than you burn off you put on weight. Okay there are arguments about stuff around the edges, but this is a truth. I think it actually takes effort to not know this. You have to make a special effort to not know this.
  • Smoking: In June 2016, the journalist Michael Deacon asked the then leader of UKIP Nigel Farage why he’d taken up smoking again. Farage apparently said “I think the doctors have got it wrong on smoking”. Again, given the overwhelming evidence to the contrary, you have to work hard to hold a line like this. Something else might be going on with Farage, he’s spent his life arguing against experts/ evidence, perhaps there’s something special about his default settings. But I don’t think so.
  • Climate Change: Climate change is not a vague thing that’s going to happen in the future. It’s happening now. I don’t wish to be uncharitable, but I feel strongly that those arguing against it are extremists, have been conned, or are working cynically in the pay of big oil/coal/ pick your hydro-carbon.
  • And once we get to politics, with politicians cynically selecting the data to prove a point or using any number of rhetorical techniques to rubbish the other side’s evidence data as an agent of change is dead in the water. I think in the post-BREXIT analysis the consensus appears to be that the heart (blue passports/ no foreigners/ any trade deal we want) case won out against the head (leaving the EU will trash the economy/ leave no money for the NHS).

I think my thesis is this.

Data is rubbish for making you change behaviour.

Eating cake is bad for you. We know this. Yet we cannot connect one slice of chocolate cake with being overweight, type two diabetes or heart attacks.

Leaving the EU is likely to be an economic catastrophe, but blue passports.

When we abstract it out to climate change, where our impact is individually tiny, we are even worse at seeing cause and effect and changing.

So how does this relate to learning analytics and education?

Many years ago, I watched a lecturer deliver a first year induction talk to a group of new economics students. He literally said to the group “One in three of you are going to fail the first year.” He paused for effect and I watched 150 students turn and look at their peers. I could see that they were all thinking the same thing. They looked around, selected someone and thought “I think it’s him/her”.

One in three of you will fail. We’re almost in the realms of coin tossing for whether or not you’re going to pass the year. And yet, almost everyone in that room decided “Nah mate. I’m fine.”

Even better, my colleague Tinne De Laet, from KU Leuven ran a pre-entry test for engineering students over a few years. She would present the results from the previous year along with the outcomes to the next cohort. She made the point that only a tiny proportion of students who failed the test actually passed the year (from memory it was about 4%). And yet when she presented this data to new engineering students at the start of the year, those students who had failed the pre-entry test decided that they would be in the 4%, and would not need to change their fundamental approach to studying. Even though in reality, only about one in 20 of them would pass the year, it wasn’t strong enough to change their behaviour.

I work in learning analytics. I work to present data to students and staff to bring about change. Worryingly, even though objectively data may be very weak as an agent of change.

So what do we need to add to the mix to make it work?

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