The four pillars of learning
Cognitive science has identified four main factors for successful learning: attention, active engagement, feedback, and consolidation. Stanislas Dehaene, a graduate of the Ecole Normale Supérieure, cognitive psychologist and neuroscientist, presents these four pillars and explains why they are essential to help children learn better from a very young age.
1. Attention, a filter that must be captured and channelled.
Attention is the filtering mechanism that allows us to select information and modulate its processing. And by understanding that it eliminates to concentrate, we will suddenly realise the profound accuracy of the term concentration. The attention system is broken down into three attentional systems: alerting, orienting and executive control. Attention massively modulates brain activity: therefore, the essential challenge for the transmitter of knowledge, whether parent, teacher or trainer, is to draw attention to the "right level". The learner must be alert.
But there are limits to attention.
Firstly, filtering implies that doing two tasks simultaneously is very difficult - indeed, a bottleneck phenomenon has been observed in the prefrontal cortex. In reality, when we 'juggle', we are not doing two things at the same time, we are simply switching from one task to another, temporarily omitting the first, and at the expense of signal acquisition.
Then, when we are focused, stimuli that are not relevant to the task in question will simply become... invisible! This is best illustrated by a famous video in which the challenge is to count the exact number of passes made by players dressed in white. In the light of such an experiment, it is clear that attention, which is selective by nature, leads to overconfidence - we will be prepared to argue that what has passed 'under the radar' of our perception simply never existed. For the filter flap is in a sense one-way. A lesson that can be extrapolated to many areas of life. The challenge is therefore to direct attention properly, and in this respect, what has been called the "master effect" is crucial: one teacher will succeed in capturing attention where another will get bogged down, or even draw attention to irrelevant levels - and it may be noted that this is a pitfall into which many school or training manuals fall, where too many illustrations and colours are placed in an attractive but chaotic way. Far from this overdose of information, the aim is to channel attention.
Finally, executive control, the lever of attention, is essential: it involves inhibiting undesirable behaviour that would be "double duty": for example, not dispersing oneself by leaving the activity area to do something else, starting to talk to someone else, etc. In this respect, the progress is particularly visible in children from families where certain behaviours are not insisted upon - for example, staying at the table to eat. This teaching of cognitive sciences sheds new light on the issue of discipline, but also on inequalities between social backgrounds. It also gives tools to fight against these inequalities.
2. Active engagement.
The guiding principle is quite clear: a passive organisation does not learn. Active engagement is therefore sought. The teacher can only mobilise if the child or learner mobilises. However, without testing the reliability of a piece of knowledge, we will remain in an illusion of knowledge - it is moreover likely that everyone is concerned in this or that field. Children and learners must be able to test themselves. Making the conditions for learning (reasonably) more difficult will paradoxically lead to greater commitment and cognitive effort, which are synonymous with better attention.
3. Feedback.
Error is human but also... essential. While activity rather than passive listening is crucial, it is not enough. It is currently thought that the cortex is a kind of prediction-generating and error-integrating machine: it makes a prediction, receives sensory information in return, and a comparison is made between the two. The difference creates an error signal that will propagate in the brain and allow the next prediction to be corrected and improved. Feedback is therefore essential. The brain thus works by iterations, with cycles that can be broken down into four successive stages: prediction, feedback, correction, new prediction. This is known as the Bayesian brain - from the inference of the same name - or statistician. It organically internalizes statistics. It is simply a matter of continually correcting the shot thanks to feedback, which amounts to saying that... error is fundamental! Indeed, if error signals allow us, once again, to adjust our predictions, learning can only be triggered if there is an error signal, otherwise nothing changes.
Transposed to pedagogy, this implies that error is normal, inevitable and... fertile. On the condition that, on the one hand, it is actively noticed by the learner, who, far from ignoring it, must overcome it. On the other hand, in order to be fertile, it must not be overly sanctioned, stress being a learning inhibitor. Worse, a feeling of powerlessness would nip future efforts in the bud. So what is the best way to overcome mistakes and achieve success? Motivation through positive reinforcement and - immaterial - rewards should be preferred. Of course, it is not a question of 'monetising' success, or even paying children to get good grades. On the contrary, as humans are social animals, success should be concluded with social reinforcement: approval, validation, encouragement.
4. Consolidate what you have learned.
We only have to remember our first steps towards the driving licence to realise that at the beginning of this learning process, there is a conscious effort, and in front of the multitude of signals to be managed in real time, a feeling of not being able to do it, of being overwhelmed. It's terrifying! But this is a typical example of what we call explicit processing: a situation, or rather a stage, where the prefrontal cortex is strongly mobilised by executive attention. And, as a culmination of learning, the challenge will be to accomplish the transfer from the explicit to the implicit. In fact, by gradually transferring to non-conscious, faster, more efficient networks, the brain achieves automation. The prefrontal cortex system is freed up and becomes available again - not unlike the way in which system resources are freed up in a computer, which, instead of being saturated and performing its tasks with great difficulty, once freed up allows us to 'surf' without hindrance, without superfluous tasks in the background. We also find in our cortex the phenomenon of the bottleneck, which again evokes a computer RAM, a buffer memory that can only process a given volume of information at a time before moving on. Let us return to the primordial example of reading. At the beginning, the child must consciously retain each of the correspondences between letters and sounds, and apply them one by one, in the manner of our adults who had to learn an "alien" language. Learn that the round 'o' is pronounced 'water', and so on for each letter. And, as we see with children in this early literacy phase and also with dyslexics, the more letters we have stored up, the longer it takes. It's linear and serial! However, adults and children from the third year of school onwards no longer have this effect: an eight-letter word will be read as quickly as a three-letter word, because the processing is no longer serial, but massively parallel: all the letters are read at the same time! It is easy for an adult, a teacher, to forget this initial difficulty, and not to realise what is being asked of the child. And when the entire "resource percentage" of our "central unit" is called upon in decoding, we cannot concentrate on the meaning of the text.
The phenomenon of automation is therefore crucial because it releases high-level resources.
The role of sleep
A word before concluding about an unexpected element in the consolidation of learning, sleep. It was found that by allowing a person to sleep, even a simple nap, and without re-learning, the performance measure was improved. This is because the brain works during sleep: it "puts in order" the new things it has recorded, probably by replaying them at an accelerated speed. This accelerated speed enables it to detect regularities, to establish episodic memory (memory of past events) and, with algorithms, to establish generalisations and even to make discoveries. The scientific journal Nature devoted an article to this: many mathematicians report that in the morning they had the solution to a problem they were struggling with the day before - and by repeating the experiment in the laboratory, this phenomenon has been verified.