Imagine the scene: you’ve gone to see your GP. You’re in a packed waiting room, when the receptionist makes an announcement: “The doctor will see you now… all of you.” Instinctively you and your fellow patients form a queue, but the doctor doesn’t want to see you one-by-one, but simultaneously. It’s chaos, of course – people with different needs trying to explain their various problems all at the same time. To make matters worse, the doctor prescribes the same treatment to everyone.
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What would be madness in healthcare is standard practice in education – one teacher teaching the same thing to a classroom full of children.
There are obvious reasons for the difference in approach. Above all, there’s the factor of time: for pupils, going to school is a full-time occupation; for all but the sickest patients, seeing a doctor isn’t. In contrast to the occasional ten minute slots that doctors can devote to individual patients, there aren’t remotely enough teacher-hours available to individually tutor every child.
But how much of a difference would it make if there were? In 1984, the educational psychologist Benjamin Bloom decided to find out. Studies were conducted comparing the performance of pupils who received personal tuition using ‘mastery learning’ techniques (i.e. totally nailing each bit of the curriculum before moving on to the next thing) with a control group receiving standard whole-class teaching.
The difference that the tuition made was huge – amounting to two standard deviations i.e. enough to take a mediocre pupil to the top of the class or thereabouts. The mathematical symbol for a standard deviation (a measure of how much variation there is from the average of a group of values) is the Greek letter sigma – hence the name for the phenomenon that Bloom discovered: the ‘2 sigma problem’.
It’s a ‘problem’ because it suggests that most children have the potential to do much, much better than most schools enable them to do.
This makes a lot of sense to me. When I doing my maths O-level, I just couldn’t get the hang of quadratic equations. My classmates seemed to have grasped the principle, so it wasn’t the teacher’s fault – just mine. At the time, I simply assumed that anything more than basic algebra was beyond me. Years later I came across a teach-yourself-maths book. Sitting down with it for half-an-hour, I found that could solve quadratic equations after all. That was thanks to a clear explanation (which I obviously hadn’t paid attention to in class, and which was missing from our useless school textbooks).
Think of anyone alive in the world today. Apart from the rest of humanity, what’s between their ears is the most complex object in the known universe. It’s almost certainly capable of things it’s never been adequately taught to do. Now multiply that up by all the other millions – indeed billions – of under-cultivated minds. What might we achieve if unlocked that latent potential?
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It’s all the more frustrating because, as Bloom demonstrated, we know how to do it – but can’t. Even if we could somehow find the money for a massive investment in one-on-one tuition, where would we find the tutors? There are ten million pupils in the UK – giving them just one day’s tuition a week would require two million tutors. Currently the UK has something like a half-a-million teachers – hence our dependence on whole class teaching.
But there is one way in which we could provide much wider access to personalised, responsive tuition – artificial intelligence. AI-powered teaching software promises something more than a mere electronic textbook. ‘Adaptive learning systems’ promise not only to monitor pupil progress – but to identify particular strengths and weaknesses and respond appropriately.
Karen Hao of MIT Technology Review has a must-read report on what AI educational software can already do:
“A student begins a course of study with a short diagnostic test to assess how well she understands key concepts. If she correctly answers an early question, the system will assume she knows related concepts and skip ahead. Within 10 questions, the system has a rough sketch of what she needs to work on, and uses it to build a curriculum…”
Major investments are being made in this rapidly advancing technology and one country in particular is taking a lead. Needless to say, it’s China:
“Experts agree AI will be important in 21st-century education—but how? While academics have puzzled over best practices, China hasn’t waited around. In the last few years, the country’s investment in AI-enabled teaching and learning has exploded. Tech giants, startups, and education incumbents have all jumped in. Tens of millions of students now use some form of AI to learn…”
One of the leading companies in the field is Squirrel AI – and it’s growing fast:
“In the five years since it was founded, the company has opened 2,000 learning centers in 200 cities and registered over a million students—equal to New York City’s entire public school system. It plans to expand to 2,000 more centers domestically within a year. To date, the company has also raised over $180 million in funding. At the end of last year, it gained unicorn status, surpassing $1 billion in valuation.”
It should be stressed this is not about replacing teachers with computers. Nor is about applying a technological gloss to failed theories of ‘child-centred learning’. Rather it’s about providing universal access to at least some of the benefits of personalised tuition that we can’t deliver any other way.
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No doubt, there could be some really bad ways of using AI in the classroom. But one way or another, we need to learn from what’s happening in China right now.
As in every other country, our future will depend on how successfully we use artificial intelligence to make the most of our human intelligence.