This article was written for SecEd magazine and first published in September 2017. You can read the original version on the SecEd website here.
You can access the full archive of my columns for SecEd here.
This is part five of a 10-part series. Catch up with the series so far.
If I asked you to calculate 57 x 4,389 in your heads, no cheating, and in the space of a minute, I’m pretty confident most of you would fail. And in the process of failing, you’d likely do one of two things:
1. You’d decide the task was unachievable – especially with the time constraints attached – and therefore not attempt it, or…
2. You’d try to complete the task but fail because to succeed would involve processing too much information all at once. Your working memory wouldn’t be able to cope with the demands you’d placed upon it, in just 60 seconds, and you’d reach the point of cognitive overload.
Whichever of these two paths you took, you wouldn’t calculate the answer and wouldn’t, therefore, encode anything into long-term memory.
Put simply, you wouldn’t learn anything new or practise something you already knew. This complex thing called “learning” would not occur.
Now, if I were to ask you to calculate 2 x 10, once again in your heads and in the space of a minute, I’m confident all of you would succeed this time. And you wouldn’t need a full minute to do so either. In fact, you’d proffer your answer instantaneously.
But, and here’s the rub, you wouldn’t have calculated anything – you’d have given your answer automatically.
In other words, you wouldn’t have engaged the attention of your working memory, at least not in any meaningful sense, because you’ve practised your times tables to the point of automaticity whereby you can reel them off through habit, without thinking about them, just as you tie your shoe laces or button your shirt.
Most of the time, you drive your car without thinking about it, too; you’ve done it so many times that the task no longer needs to engage your active attention, which helps explain why you sometimes arrive at your destination with absolutely no memory of the journey.
And because you answered 2 x 10 without thinking about it, you didn’t learn anything new or practise something that you already knew, as was the case with the first sum.
In other words, this task – though ostensibly a success – was also pointless because learning did not occur.
The struggle zone
If we want our pupils to learn anything – by which I mean, encode information in their long-term memories – then we need to engage their active attention and get them thinking hard. We need to give them work to do that’s challenging but achievable because if the work’s too easy pupils will complete it through habit, if the work’s too hard pupils will be unable to complete it. In both cases, learning will fail.
So we need to pitch work in pupils’ “struggle zones” – what they can do with time, effort and support. This is sometimes referred to as the “zone of proximal development”, a term invented by the Russian psychologist Lev Vygotsky and defined by him in 1978 as “the distance between the actual developmental level as determined by independent problem-solving and the level of potential development as determined through problem-solving under adult guidance, or in collaboration with more capable peers”.
Working on problems that are too easy or too difficult is not enjoyable because there is no sense of progress, and thus we become frustrated. Working on problems that are pitched in our struggle zone, however, is rewarding.
This is why giving pupils work to do that is too easy for them and which they can therefore accomplish without thinking – in the misguided belief that it will give them a sense of success and thus motivate them – doesn’t work. Instead, we are motivated by thinking hard and overcoming difficulty; we are motivated by overcoming challenges.
There’s evidence from the field of neurochemistry to support this notion, too. When we solve a problem, we are rewarded with a small dose of dopamine which is a naturally occurring chemical that’s important to the brain’s pleasure system. Indeed, alongside serotonin, dopamine is one of only two things that – chemically speaking – give us pleasure.
So how can we ensure that our pupils are made to think hard? Sometimes, we need to place artificial barriers in the way of their initial encoding of information so that the information is stored more effectively and can more easily be retrieved later. These artificial barriers or road-blocks in our thinking are what Professor Robert Bjork called “desirable difficulties”.
Bjork, a cognitive psychologist at UCLA, coined the phrases “storage strength” (SS) and “retrieval strength” (RS) in order to help improve our understanding of how we learn (which is to say, how we commit things to long-term memory).
SS is the measure of how effectively we have encoded something. Studying something in greater detail increases the chance of us storing it in our long-term memory. The better it is learned, the higher the SS. If it has a high SS, it is more likely to be stored in our long-term memory (rather than remain in our working memory to be quickly forgotten) and more likely to be ready to be “retrieved” later.
Retrieval strength, meanwhile, is the measure of how easily we can access a memory of something we’ve learned. In other words, RS is our ability to recall information at a later date. RS decreases over time – which is why we forget things as we get older – and the lower the SS, the faster the RS will decrease.
Put simply, if we want to learn something well enough so that it will be accessible to us in the future (rather than quickly forgotten or hidden away in an impossible-to-reach location), then we need to learn it in greater depth, and we need to “over-learn” it.
Bjork identified a number of conditions which over time increase SS and RS and which therefore lead to information being retained for longer. These conditions, Bjork cautioned, “slow down the apparent learning, but under most circumstances help long-term retention, and help transfer of knowledge, from what you learnt to new situations”.
Bjork called these conditions “desirable difficulties” because they are ways of teaching which are intentionally challenging to pupils because difficulty and hard work are what assists their long-term learning.
Put simply, then, Bjork argued that teachers should spend longer teaching fewer things but in greater detail. In other words, our pupils should cover less curriculum content but what they do cover should be in much greater depth.
I’ll give you an example of desirable difficulties but, before I do so, quickly answer this question: How many animals of each kind did Moses take onto the Ark?
The more quick-witted, eagle-eyed among you will have spotted the deliberate mistake and answered “none”. But I bet some of you said “two”. I’ve asked this question at several conferences and INSET events and a healthy proportion of the audience always insist the answer’s “two”.
If you said “two” then you fell into the trap of skimming the question too quickly and offering the obvious answer. The fact is, the question asks you how many animals Moses took onto the Ark when, in fact, Moses didn’t build an ark, it was Noah.
That question was a perfect example of work that is too simple, too easy, too obvious. Because it has all the hallmarks of a straightforward question, some of you put two and two together and made five. You skimmed over the words and filled in the gaps then offered an answer out of habit. That answer happened to be wrong but you were convinced of its accuracy. You simply didn’t think hard enough.
There are several ways to help pupils avoid falling into this trap – each of which is an example of a desirable difficulty, a barrier that slows down the initial encoding of information so that it is stored better and more easily retrieved from long-term memory.
First, we can use more complex language constructions. For example, instead of asking a question worded as a simple sentence (“How many animals of each kind did Moses take onto the Ark?’), we could ask it using a complex sentence (“In the biblical story, to save them from the flood, how many animals of each kind did Moses take onto the Ark?”).
Second, we could put a deliberate block in the way – something incongruous that stops pupils in their tracks (“How many animals of each kind did Donald Trump take onto the Ark?”).
Third, and this is rather counter-intuitive, we could use a hard-to-decipher font for written information on the board or in handouts. To prove the effectiveness of this strategy, consider Professor Shane Frederick’s Cognitive Reflection Test involving 40 Princeton students (search online for more about this).
Half of the students saw a puzzle in a small font in washed-out grey print. The puzzle was legible, but the font induced cognitive strain. The other half saw the puzzle in a normal font. The results told a clear story: 90 per cent of the students who saw the puzzle in a normal font made at least one mistake in the test, but the proportion dropped to just 35 per cent when the font was barely legible. In short, performance was better with the hard-to-decipher font.
Cognitive strain, whatever its source, mobilised what Professor Daniel Kahneman – in Thinking Fast and Slow – calls System 2 (System 2 thinks slow – it works rationally and methodically; it can assess and analyse choices in a sophisticated and analytical way) which meant the participant was more likely to reject the intuitive answer suggested by System 1 (System 1 thinks fast – it’s instinctive and intuitive. It can react more quickly than conscious thought. But it is also prone to error).
The difficult font slowed down thinking and helped participants in the test to avoid mistakes.
Professor John Hattie echoed Bjork’s belief that teachers should slow down learning and set challenging work. He said that the best way for pupils to learn is not always pleasurable for them: “Learning is not always easy; it requires over-learning at certain points, spiralling up and down the knowledge continuum, building a working relationship with others in grappling with challenging tasks.” (Hattie, 2012)
Hattie went on to say that the most “accomplished teachers set tasks that (have) a greater degree of challenge”.
Don’t dumb down
Therefore, we “dumb down” at our peril. Setting work that’s too easy and placing artificial limits on what we expect our pupils to achieve is not the best way to help them learn. Instead, we should model high expectations for all our pupils, no matter their starting points and their most recent performance. We should teach to the top, not the middle, and ensure our classrooms provide challenge for all.
Of course, some pupils fear challenge. We need to eliminate – or at least mitigate – pupils’ feelings of fear and hesitation by creating a classroom environment which encourages the making of mistakes as a sign of learning, and which explicitly says (through our choice of language, our modelling and thinking aloud, and the routines we engage in) that there is nothing to fear by trying your best and pushing yourself to do hard work.
After all, challenge is innate
In their lives outside the school gates, pupils are always seeking hard things to do such as computer games. They are the YouTube generation who spend hours watching video tutorials, looking at graphic organisers on Pinterest or reading articles on Buzzfeed so they can learn by increments and improve their performance in, say, Minecraft, baking, football, make-up and nail art, hair design, and so on.
They love challenge when it is private because, in the safety of their bedrooms, there isn’t the fear of humiliation or peer pressure.
In order to promote challenge in the classroom, therefore, we need to reduce the threat level, we need to ensure no-one feels humiliated if they fall short of a challenge. Rather, they need to know they will learn from the experience and perform better next time. They will learn by increments.
In conclusion, in order to ensure pupils engage the attention of their working memories effectively and therefore encode information into long-term memory, they need to think hard and accept challenging work.
However, because space in working memory is very limited, we need to help pupils to use that space efficiently. As such, next week we will look at ways of cheating working memory.
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