Stanislas Dehaene Demonstrates How We Learn

It was 23 years ago since philosopher of science, John T. Bruer, wrote his influential paper against the prospect of neuroscience as a guide for education. His paper was pushback in the middle of the decade of the brain, which saw a rise of interest in the possibility of building a bridge between neuroscience and education. Bruer wrote:

The brain does and should fascinate all of us, and we should find advances in neuroscience exciting. As educators, we should also be interested in how basic research might contribute to and improve educational practice. However, we should be wary of claims that neuroscience has much to tell us about education, particularly if those claims derive from the neuroscience and education argument. The neuroscience and education argument attempts to link learning, particularly early childhood learning, with what neuroscience has discovered about neural development and synaptic change. Neuroscience has discovered a great deal about neurons and synapses, but not nearly enough to guide educational practice. Currently, the span between brain and learning cannot support much of a load. Too many people marching in step across it could be dangerous.

In 1997, neuroscience was promoted as the next step for adapting educational policy in the classroom. Countries like the United States dumped millions of dollars to research the prospect of cognitive development and early education. As psychology and cognitive science did in the earlier decades, educators enthusiastic about the achievements of brain science wanted to implement the latest discoveries in the field. The case seemed simple: a cardiologist needs to understand the heart to be able to treat his patients; dentists need to understand teeth to be able to work on them; so, why don’t teachers understand the brain which, is the most important organ for learning.

Such thinking was too simple and misguided, and it started to attract critics, especially Bruer, and one of the fathers of cognitive science, Jerome S. Bruner. In an article for The New York Review of Books, Bruner alerted the readers of the growing interest of educators using discoveries of the brain to justify bad educational policies. One example was the use of the discoveries of Nobel Laureates, David Hubel, and Torsten Weisel. Some educational policies promoted early stimulation based on their findings on early deprivation in a cat’s eye – the cat becomes partly blind after suturing one eye, and the “neurons that might have served it either having died or been taken over by other brain functions.” Bruner, who reviewed the worked of Bruer at the time wrote on such policy:

But the brute fact of the matter is that very little else in the nervous system is anywhere near that specialized that early. Hubel and Wiesel’s findings simply cannot be generalized to apply to most other brain functions. And even early blindness with translucent cataracts that let through some light but no image has no such drastic effects. 5 Another bit of evidence that is often misinterpreted is from Peter Huttenlocher’s study of “synaptic density” cited by Bruer.6 The brain’s synaptic connections increase rapidly in the first three years and then begin to decline. Should you try to stimulate these connections? As Bruer points out, early growth is genetically programmed and not driven by stimulation at all.

Michael S. Gazzaniga, the father of cognitive neuroscience, following Bruer’s line, wrote in The Mind’s Past (The University of California Press, 2000),  that the bridge between neuroscience and education is a problem because some scientists might present their results “in a light pleasing to the political system they are beholden.”

Over the following years into the new century, even with the warnings from such luminaries in the field of cognitive science, many scientists and educators have tried to close the gap between neuroscience and education. Journals like Nature started to present articles on the topic, educators started to become even more interest, with new university departments popping up in prestigious institutions. Moreover, a brand-new journal, Mind, Brain & Education was founded, featuring an article by the renowned neurologist, Antonio Damasio. Still, many view the prospect of neuroeducation bleak. Many have criticized the use that neuroscience can have in education when there are more established disciplines like cognitive psychology and educational psychology.

How We Learn by Stanislas Dehaene

Greater than machines…

It is because of this historical background that one is pleased to read cognitive scientist, Stanislas Dehaene, in his new book, How We Learn: Why Brains Learn Better That Any Machine… for Now (Viking, 2020). Dehaene is a researcher in France, a well-renowned expert on the topic of consciousness. And yet, his contributions to brain science and education are equally impressive. Dehaene’s tall task to present contributions of brain science to the way we practice education is the gem of his newest book.

Previously, Dehaene took the challenge of the detractors of educational neuroscience step by step. He’s part of a group of researchers, that include Argentinian scientist Mariano Sigman, brain imaging pioneer, Michael Posner, President of the James S. McDonnell Foundation Susan Fitzpatrick, and the man himself, John T. Bruer; trying to shed a light of the different cognitive processes of the brain and how they relate to education. Stanislas Dehaene previously published, The Reading Brain (Viking, 2009) and The Number Sense (Oxford University Press, 1999), but it’s in How We Learn that he finally puts the puzzle together; a clear-eye view of what neuroscience can contribute to education.

The strong point of Dehaene’s book is his willingness to dispel myths of the brain and present our innate ability to learn. In the first chapters, Dehaene makes it clear, no machine, for now, has the processing abilities of our brains. He describes the cognitive abilities that a newborn already has: “From birth, the child’s brain must already possess two key ingredients: all the machinery that makes it possible to generate a plethora of abstract formulas (a combinatorial language of thought) and the ability to choose from these formulas wisely, according to their plausibility given the data.” While machines, especially Artificial Intelligence, have the current problem of only focusing on one task (and learn such task), a baby’s brain of a few months of age “already encodes the external world using abstract and systematic rules – and the ability that completely eludes both conventional artificial neural networks and other primate species.”

Dehaene dispels the old and tire debates of nature vs. nurture. He presents that, it is the combination of both visions that really make the brain such a complex organ. The child’s mind cannot be a blank slate, the ability to get new information, do trial and errors with his surroundings, is innate – with most of the neural development genetically predisposed. Still, not everything is predisposed in the child’s minds, and it’s the interactions with family members, social surroundings, and even physical space that helps to develop the mind. For Dehaene:

This division of labor puts the classic ‘nature versus nurture’ debate to rest: our brain organization provides us with both a powerful start-up kit and an equally powerful learning machine. All knowledge must be based on these two components: first a set of prior assumptions, prior to any interaction with the environment, and second, the capacity to sort them out according to their posterior plausibility, once we have encountered some real data.

How the Brain Develops

In the second part of the book, Dehaene dedicates himself to explain how the brain learns since early development. Dehaene demonstrates how to really use the tools of neuroscience to further our understanding of the child’s mind; the disciplines of cognitive neuroscience, neurodevelopment, and even pedagogy, help illuminate his premise. Once again, it’s the combination of predisposed cognitive abilities, for numbers, words, and even to learn well after the sensitive period (thanks to brain plasticity), that make learning deeply enriched in humans. What Dehaene demonstrates is that everybody comes with the capability to learn, from toddler to adulthood. The neural development is designed to create a sense of numbers, a sense of space, of words, even to understand the child’s own native language, even before learning to speak.

To any expert in the field of psychology or brain science, what Dehaene presents is plainly obvious. And yet, it is in these types of facts that many educators get lost when trying to bridge neuroscience with educational practice. Other researchers, like Paul A. Howard-Jones, demonstrate that is in this web of knowledge on neural development, brain capability, and approach to learning, that many teachers start to believe in the wrong facts about the brain, creating the famous phenomenon of neuromyths.

Neuromyths “are often associated with ineffective or unevaluated approaches to teaching in the classroom, thereby affecting children’s learning in subject areas beyond science. Misunderstanding about brain function and development also relates to teachers’ opinions on issues such as learning disorders and so, in turn, may influence the outcomes of students with these disorders,” writes Howard-Jones in Nature Reviews Neuroscience. These neuromyths can range from inoffensive ones like, “drinking less than 6 to 8 glasses of water a day can cause the brain to shrink” to more serious ones like “individuals learn better when they receive information in their preferred learning style (for example, visual, auditory or kinaesthetic).” The bigger problem with them is that many educational policies might use these myths to guide curriculums and educational practices. As Howard-Jones explains:

Neuromyths are misconceptions about the brain that flourish when cultural conditions protect them from scrutiny. Their form is influenced by a range of biases in how we think about the brain. Some long-standing neuromyths are present in products for educators and this has helped them to spread in classrooms across the world. Genuine communication between neuroscience and education has developed considerably in recent years, but many of the biases and conditions responsible for neuromyths still remain and can be observed hampering efforts to introduce ideas about the brain into educational thinking. We see new neuromyths on the horizon and old neuromyths arising in new forms, we see ‘boiled-down’ messages from neuroscience revealing themselves as inadequate, and we see confusions about the mind-brain relationship and neural plasticity in discussions about educational investment and learning disorders.

Stanislas Dehaene and the Prospect of Educational Neuroscience

Dehaene’s third part of the book is a potent antidote against the threat of neuromyths. In it, he explains the proven educational practices that are effective in the classroom, taking into consideration how we learn. Four pillars of learning shape the effective learning that Stanislas Dehaene presents throughout the book: attention, active engagement, error feedback, and consolidation. Dehaene explains: “Far from being unique to humans, these functions shared with many other species. However, due to our social brain and language skills, we exploit, them more effectively than any other animal – especially in our families, schools, and universities.”  The earlier neuroscience background that Dehaene displayed throughout the book gets mixed with earlier studies of psychology, cognitive science, and education.

Attention is a well-explained concept in cognitive science, yet, for Dehaene, is a concept that teachers tend to ignore in their classroom. He points out the obvious, “A teacher’s greatest talent consists of constantly channeling and capturing children’s attention in order to properly guide them.” But, he goes further to dispel a misunderstanding of the concept, pointing out that attention consists of “suppressing the unwanted information” and that videogames, in reality, don’t reduce a child’s ability to concentrate; to the contrary, videogames “actually increase it.” For Dehaene, understating the evolutionary origins of attention, and how it’s processed in the brain presents an understanding of its importance.

The same happens with active engagement and error feedback. In the former, Dehaene misspells the old myth of body movement in the classroom being a result of active engagement. “Being active and engaged does not mean that the body must move. Active engagement takes place in our brains, not our feet. The brain learns efficiently only if it is attentive, focused, and active in generating mental models,” writes Dehaene. “Brain imaging is beginning to clarify the origins of this processing depth effect. Deeper processing leaves a stronger mark in memory because it activates areas of the prefrontal cortex that are associated with conscious word processing and because these areas form powerful loops with the hippocampus, which stores information in the form of explicit episodic memories.” Dehaene brings a simple tool for this knowledge of active engagement: teachers must present topics in which they can create curiosity in their children. “To maintain curiosity, schools must therefore continually provide children’s supercomputing brains with stimulants that match their intelligence.”

The latter, error feedback, Dehaene presents a simpler view of why it matters in the classroom: “Learning is active and depends on the degree of surprise linked to the violation of our expectations.” For Dehaene, committing violations to pursue knowledge is no a problem, rather, it’s the educator’s task to provide “explicit feedback that reduces the learner’s uncertainty.” This of course is, as Dehaene demonstrates, because our brains are “prediction-error system,” which “govern learning from the very beginning of life.” Of course, is not just supplying the feedback, but how the educator provides it. Dehaene makes the comparison with machine learning: “We do not punish artificial neural network; we simply tell it about the responses that it got wrong. We provide it with a maximally informative signal that notifies it, bit by bit, of the nature and sign of its errors.”

A key point on error feedback is the way educators test in school, for Dehaene, testing shouldn’t be at the end of the topic or in a month, but, in little fragments, per week. These little intervals create opportunities to consolidate information and test what is the real knowledge of the students. Dehaene explains that this is impossible without the opportunity of a good night’s sleep. The world of sleep provides the best opportunity to take the new information in the day and consolidate it with the previous information. The last 10 years have seen an interest in sleep, with interesting research pointing out that while asleep, our brains remain active, creating new ways to remember the information, and, on some occasions, utilizing the new information in creative ways. Matthew Walker, arguably the biographer of modern sleep, has demonstrated that sleep helps to regulate emotions, consolidate memories, and enhance the brain’s plasticity.

How We Learn is the best presentation card that the field of educational neuroscience currently has. Dehaene does not fall in the old traps of over-promising with the current research in neuroscience. Furthermore, he topples neuromyths and educational myths throughout the text. He believes in “reconciling education with neuroscience,” creating a “new alliance” in which teachers can really in the latest evidence-based research by scientists and put in it to the test in the classroom. It seems that the chief column of the bridge between neuroscience and education is Dehaene’s work.

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Review of How We Learn: Why Brains Learn Better Than Any Machine…for Now by Stanislas Dehaene (Viking, 2020, pp. 3520)

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