How We Learn: The New Science of Education and the Brain
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- Create Date：2021-04-04 13:51:00
- Update Date：2025-09-07
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- Author：Stanislas Dehaene
- ISBN：0141989300
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Summary
'Absorbing， mind-enlarging， studded with insights 。。。 This could have significant real-world results' Sunday Times
Humanity's greatest feat is our incredible ability to learn。 Even in their first year， infants acquire language， visual and social knowledge at a rate that surpasses the best supercomputers。 But how， exactly， do our brains learn？
In How We Learn， leading neuroscientist Stanislas Dehaene delves into the psychological， neuronal， synaptic and molecular mechanisms of learning。 Drawing on case studies of children who learned despite huge difficulty and trauma， he explains why youth is such a sensitive period， during which brain plasticity is maximal， but also assures us that our abilities continue into adulthood。 We can all enhance our learning and memory at any age and 'learn to learn' by taking maximal advantage of the four pillars of the brain's learning algorithm: attention， active engagement， error feedback and consolidation。
The human brain is an extraordinary machine。 Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled， and it remains the best source of inspiration for recent developments in artificial intelligence。 How We Learn finds the boundary of computer science， neurobiology， cognitive psychology and education to explain how learning really works and how to make the best use of the brain's learning algorithms - and even improve them - in our schools and universities as well as in everyday life。
Humanity's greatest feat is our incredible ability to learn。 Even in their first year， infants acquire language， visual and social knowledge at a rate that surpasses the best supercomputers。 But how， exactly， do our brains learn？
In How We Learn， leading neuroscientist Stanislas Dehaene delves into the psychological， neuronal， synaptic and molecular mechanisms of learning。 Drawing on case studies of children who learned despite huge difficulty and trauma， he explains why youth is such a sensitive period， during which brain plasticity is maximal， but also assures us that our abilities continue into adulthood。 We can all enhance our learning and memory at any age and 'learn to learn' by taking maximal advantage of the four pillars of the brain's learning algorithm: attention， active engagement， error feedback and consolidation。
The human brain is an extraordinary machine。 Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled， and it remains the best source of inspiration for recent developments in artificial intelligence。 How We Learn finds the boundary of computer science， neurobiology， cognitive psychology and education to explain how learning really works and how to make the best use of the brain's learning algorithms - and even improve them - in our schools and universities as well as in everyday life。
Reviews
Kris Muir
，
Dehaene is a well-respected neuroscientist and his expertise is obvious from his intricate explanation of the neuronal scaffolding of the brain。 For my own personal teaching， I appreciated his framework around the 4 pillars of learning （attention， active engagement， error feedback， consolidation）。 I found his chapter on error feedback very interesting， particularly the research by Roediger on memory retention being stronger when students tested themselves （and studied less） vs the students that Dehaene is a well-respected neuroscientist and his expertise is obvious from his intricate explanation of the neuronal scaffolding of the brain。 For my own personal teaching， I appreciated his framework around the 4 pillars of learning （attention， active engagement， error feedback， consolidation）。 I found his chapter on error feedback very interesting， particularly the research by Roediger on memory retention being stronger when students tested themselves （and studied less） vs the students that actually spent more overall time studying。 I'm also very curious about the notion of the spacing effect and what an ideal timeline might look like for something you're trying to keep for a lifetime （e。g。 knowledge of neuroscience！）。 Dehaene references intervals of 20% of how long you want to remember something， but he doesn't give any specifics in terms of timeline。 If I want to learn X topic and still be able to remember it 5 years from now， how often do I need to schedule retrieval practice？ Is it every week， then every month， then every 6 months， etc。？ On balance， I liked the Dehane book but I felt that it lacked strong practical approaches to applying neuroscience in teaching and learning。 Advice for learners （and maybe teachers）:-build in more low-stakes tests （as simple as brain dumps on a white sheet of paper）-do the hard thinking involved in retrieval practice （set a timer and see how much you remember）-leverage the spacing effect （plan ahead and schedule study sessions over many days instead of cramming）-consider cascading your study sessions （20% reviewing old material， 40% new material）Inspired by this book， I attended a wonderful workshop on the neuroscience of learning given by neuroscientist Kristi Rudenga at Notre Dame。 Her main insights were:-“learning changes the physical structure of the brain”-“repetition strengthens synapses”-“richer networks = stronger learning”-“stress short-circuits the brain”Happy Reading！ 。。。more
Anne-Hélène
，
Quelques passages très intéressants dans la 3è partie， mais les deux premières sont longuettes。 Ce livre tente d'être à la fois solide scientifiquement （mais il est trop court pour cela） et vulgarisateur （il est alors trop long）。 Pour le public de non spécialistes qui me semble visé et que je suis， chaque chapitre pourrait tenir en 5 pages + 10 pages de bibliographie。Le propos reste intéressant， mais le faible apport de ce livre au peu （très peu ！） que j'avais lu auparavant explique ma déception Quelques passages très intéressants dans la 3è partie， mais les deux premières sont longuettes。 Ce livre tente d'être à la fois solide scientifiquement （mais il est trop court pour cela） et vulgarisateur （il est alors trop long）。 Pour le public de non spécialistes qui me semble visé et que je suis， chaque chapitre pourrait tenir en 5 pages + 10 pages de bibliographie。Le propos reste intéressant， mais le faible apport de ce livre au peu （très peu ！） que j'avais lu auparavant explique ma déception。 Foncez si vous n'y connaissez rien， ça me semble une très bonne introduction; trouvez plus technique si vous cherchez à creuser。 。。。more
Erin
，
Too technical for what I was looking for， and the print was very small （and I am very picky about font size）。
Hélder Filipe
，
Um dos melhores livros sobre aprendizagem。 Bastantes e convicentes evidências científicas apresentadas para reforçar os pontos defendidos pelo autor。
Paige McLoughlin
，
I read this in the early part of 2020。 I had been exploring concepts in machine learning and developments in Artificial intelligence and I have always had an interest in human cognition and learning。 This book combined both topics and compares and contrasts the functioning down to some real nuts and bolts of both human and machine learning。 Humans and machine learning via neural networks （which oddly enough are modeled somewhat on animal neural systems） have a lot of similarities。 It seems logic I read this in the early part of 2020。 I had been exploring concepts in machine learning and developments in Artificial intelligence and I have always had an interest in human cognition and learning。 This book combined both topics and compares and contrasts the functioning down to some real nuts and bolts of both human and machine learning。 Humans and machine learning via neural networks （which oddly enough are modeled somewhat on animal neural systems） have a lot of similarities。 It seems logical categorical processing systems are great expert systems and good algorithms for expert and bureaucratic decision-making bodies developed in the early days of AI research are very alien to the way humans think。 Do things precisely and efficiently way beyond human capacity but needed strict rules and had a hard time with novelty and ambiguity or not well-formed problems to tackle。 The newer neural nets took a long time to get off the ground but can do amazing things at visual or audio tasks of distinguishing objects that are novel and not labeled in a clear-cut manner。 It is also good at cluster messy data and fitting it into digestible graphical layouts and clusters。 It also much like people require large amounts of training sets and use feedback in performance to "learn" and be evaluate performance before it is unleashed on novel data。 The book gets down to the nuts and bolts of such systems and where they look like human learning and cognition and places where they diverge from it。 Definitely will hit this one again in the near future。3 likes · Like ∙ flagfollowing reviewsREADING PROGRESSFebruary 20， 2020 – Started ReadingFebruary 20， 2020 – Finished ReadingJanuary 26， 2021 – ShelvedJanuary 26， 2021 – Shelved as: american-historyJanuary 26， 2021 – Shelved as: biologyJanuary 26， 2021 – Shelved as: computer-scienceJanuary 26， 2021 – Shelved as: early-twentieth-centuryJanuary 26， 2021 – Shelved as: european-historyJanuary 26， 2021 – Shelved as: general-scienceJanuary 26， 2021 – Shelved as: mathematicsJanuary 26， 2021 – Shelved as: philosophyJanuary 26， 2021 – Shelved as: psychology 。。。more
Ha Trinh
，
I did learn a lot of new facts from reading this book but I found it kind of boring because there were few personal stories to "bring home" the scientific concepts。 I did learn a lot of new facts from reading this book but I found it kind of boring because there were few personal stories to "bring home" the scientific concepts。 。。。more
John Kissell
，
Stanislaus Dehaene's "How We Learn: Why Brains Learn Better than Any Machine 。。。 for Now" is an excellent overview of the human brain's mechanics in the learning process。 Some of this was familiar because I read his "Reading in the Brain" （also excellent）， some of this was new， and some went over my head （pun intended）。 You can't go wrong with a scientist who quotes Bob Dylan （"I think of a hero as someone who understands the degree of responsibility that comes with his freedom。"）。 And I will re Stanislaus Dehaene's "How We Learn: Why Brains Learn Better than Any Machine 。。。 for Now" is an excellent overview of the human brain's mechanics in the learning process。 Some of this was familiar because I read his "Reading in the Brain" （also excellent）， some of this was new， and some went over my head （pun intended）。 You can't go wrong with a scientist who quotes Bob Dylan （"I think of a hero as someone who understands the degree of responsibility that comes with his freedom。"）。 And I will repeat -- and sleep on -- the four pillars until they are automatic: attention （fully concentrate）; active engagement （participate in class）; error feedback （learn from your mistakes）; and consolidation （practice every day， take advantage of every night）。 。。。more
Юра Мельник
，
Приділено дуже багато уваги когнітивним дослідженням із навчання у немовлят і дітей до 6 років。 Ця книжка дуже корисна для батьків і педагогів
Goodstorylover
，
What a wonderful book！ I cannot truly say I have finished it， because I am definitely going to go back to it many times。 It is my great pleasure to read about the new research in the brain ability field。 My mathematician friends argue that it is endless task becuase the brain cannot get to know itself fully - well， that does not take the interesting part of it away， does it :o） Learning is very interesting subject to me in particular - I am working in education and there is an abundance of the n What a wonderful book！ I cannot truly say I have finished it， because I am definitely going to go back to it many times。 It is my great pleasure to read about the new research in the brain ability field。 My mathematician friends argue that it is endless task becuase the brain cannot get to know itself fully - well， that does not take the interesting part of it away， does it :o） Learning is very interesting subject to me in particular - I am working in education and there is an abundance of the new methods and approaches to it。 I feel that this has helped me to understand better some things （the structure and hierarchy of the responses for one）， it has also answered some of the questions I had about the left and right brain approach to teaching。 The outcomes - The 13 Take Home Messages To Optimize Children´s Potential - may not seem like groundbreaking news， but I for one am glad that some of the traditional ways have been confirmed。 Also， I shall be trying to stick to four ways how to improve in my work - fully concentrate （easier said than done， right :o）？）， take active part， learn from your mistakes （some teachers could really use some training on how to "give quick， detailed， but stress - free feedback"）， practice every day， take advantage of every night （so no miracle no effort methods， right？ just plain work :o）） I really like this author´s style - clear， concise， there is not many embellishments， but for someone who wants to know more about this field （even a layman like me） interesting and informative。 Will definitely be wanting to read his other books。 。。。more
Iris Schrijver
，
Dit is hoe een populair-wetenschappelijk boek geschreven moet worden。 Toegankelijk， onderhoudend， voldoende gestoffeerd met bronnen， data en figuren。 De schrijfstijl is - via de structurering van het boek， de parafraseringen， de gekozen voorbeelden， de korte syntheses op het einde van de hoofdstukken- een concrete toepassing van de vier pilaren van het leerproces die Dehaene onderscheidt: attention， active engagement， error feedback， consolidation。 Mooie symbiose van inhoud en vorm。 Must-read vo Dit is hoe een populair-wetenschappelijk boek geschreven moet worden。 Toegankelijk， onderhoudend， voldoende gestoffeerd met bronnen， data en figuren。 De schrijfstijl is - via de structurering van het boek， de parafraseringen， de gekozen voorbeelden， de korte syntheses op het einde van de hoofdstukken- een concrete toepassing van de vier pilaren van het leerproces die Dehaene onderscheidt: attention， active engagement， error feedback， consolidation。 Mooie symbiose van inhoud en vorm。 Must-read voor mensen werkzaam in het onderwijs， aanrader voor eenieder。 。。。more
Scott Wozniak
，
This book started very technical on the biology of brains。 Learning isn't just a metaphysical process， a physical brain change occurs every time。 I like learning the neuroscience， but it did drag a little at first。 Then he began to unpack the different theories of learning from history and work our way up to what we currently understand。 So the book got better and better as we went along。 The ending was worth the entire book。 Some great ideas in there， including:Attention is required for learnin This book started very technical on the biology of brains。 Learning isn't just a metaphysical process， a physical brain change occurs every time。 I like learning the neuroscience， but it did drag a little at first。 Then he began to unpack the different theories of learning from history and work our way up to what we currently understand。 So the book got better and better as we went along。 The ending was worth the entire book。 Some great ideas in there， including:Attention is required for learning。 To increase every other part of the learning process， find out how to capture （and keep） the attention of the learners。 The human brain is hard-wired to learn certain things （languages） and to respond to certain stimuli （eye contact from another human face）。 We learn from other humans interacting with us， far better than we learn from any other source saying the same info。Spreading out your learning into multiple sessions is much better for recall than one big chunk。 Testing yourself all the time is really good for recall。 However， we have to avoid shaming people for failure。 It turns out that all learning comes after we realize we have made an error。 Making mistakes is the learning process， not a failure of the process。 。。。more
Emre Sevinç
，
This book strikes a special chord with me: I started my formal cognitive science training and research activities almost 20 years ago， and reading the cognition-related developments in brain sciences that occurred in the last 20-25 years brings a unique type of excitement。 I haven't been involved with academic research for a long time， alas， but professionally I'm under daily pressure to learn new aspects of technology and apply them in various settings， and on top of that， I'm trying to teach s This book strikes a special chord with me: I started my formal cognitive science training and research activities almost 20 years ago， and reading the cognition-related developments in brain sciences that occurred in the last 20-25 years brings a unique type of excitement。 I haven't been involved with academic research for a long time， alas， but professionally I'm under daily pressure to learn new aspects of technology and apply them in various settings， and on top of that， I'm trying to teach some of the things I know to my two sons， while observing some of their developmental struggle with the complexities of our world。 Therefore， reading this book was a delight， because it not only summarizes the state-of-the-art of learning and teaching， but also sets the evidence-based path for future learners and teachers， that is， us。Even if you're not into the scientific aspects of developmental neuropsychology， or how some of the cutting-edge research in machine learning and artificial intelligence are inspired by the neurological mechanisms in the brain， you'll probably get something useful and practical out of this book because some sections will force you to think very consciously about the basic and critical mechanisms of attention， memory， engagement with a topic， giving and receiving feedback during learning something new， and other relevant aspects of your life。 Needless to say， the message of the book is even more important for actual teachers， trainers and young pupils， as well as the administrators responsible for shaping the future of education， and I strongly recommend reading this book with a critical perspective if you're professionally involved with such activities。I take 1 star， and give it 4 stars， because of the author's over-enthusiasm and exaggerated analogies with modern， artificial deep-learning systems。 This topic deserves more nuance， and subtlety， not TED-like simplification and sometimes outright misleading phrases。 I'm sure Prof。 Dehaene is very well aware of dangers of forcing such analogies， and I don't think he'd be keen on claiming strong correspondence between the intricacies of human minds/brains and over-hyped AI systems （yes， that attitude gets a little bit on my nerves， not only emotionally but also philosophically）。Long story short， if you want to learn about our best and current understanding of learning mechanisms that happen in the brain， especially starting from birth， and scientifically validated ways of learning and teaching better， you can't go wrong with this highly readable book。 。。。more
Kenny Lomas
，
Dehaene succinctly consolidates his findings on education and clears the air on popular misinterpretations of his work。This was the first book selected for our book club and has proved to be a handy toolkit and benchmark for future books and topics。 In particular， I will hold onto the four pillars of learning。
Jerrid Kruse
，
An excellent book exploring related fields of psychology， neuroscience， AI， and learning。 The book provides a thorough discussion of learning from these perspectives， provides useful anecdotes and examples that translate well to teaching about these topics。 The book would make an excellent addition to any Educational Psychology course and would be useful for teachers as they reflect on how to improve their teaching。
Chris
，
I have mixed feelings about this book。 On one hand， it's a very engaging synthesis of the cognitive science of learning， in a general sense。 Dehaene dispels the myth of tabula rasa by showing that babies come into the world with pre-wired expectations and learning algorithms （and this is why machine learning has a lot to live up to， and there is a lot of comparison with artificial intelligence）。 A good example of this is Chomsky's idea of the language acquisition device and how infants engage in I have mixed feelings about this book。 On one hand， it's a very engaging synthesis of the cognitive science of learning， in a general sense。 Dehaene dispels the myth of tabula rasa by showing that babies come into the world with pre-wired expectations and learning algorithms （and this is why machine learning has a lot to live up to， and there is a lot of comparison with artificial intelligence）。 A good example of this is Chomsky's idea of the language acquisition device and how infants engage in shared attention。 Dehaene also deals with the nurture side of the debate， discussing brain plasticity， sensitive periods， and his neuronal recycling hypothesis in reading development。 All fascinating stuff。 On the other hand， I feel that the book's subtitle （'the new science of education'） is misleading; much of the work discussed here isn't strictly 'new'， and much of it isn't directly relevant to education。 For instance， the final section discussing the 'four pillars of learning'， much of the work relates to animal studies or infants， with only a few light pepperings of education research。 To some extent this reflects the dearth of scientific education research， something Dehaene acknowledges in the conclusion， but I wonder how some teachers would react to his 13 key take away messages such as 'enrich the environment'， 'accept and correct mistakes'， and 'set clear learning objectives'。 Not exactly revolutionary。 （I note how this subtitle has been changed from 'why brains learn better than any machine， for now' in the hardback edition - much more appropriate）。 In conclusion， I think this book is best enjoyed with its original subtitle。 Don't expect in-depth application of cognitive science to education， and just enjoy the neuroscience！ 。。。more
Paige McLoughlin
，
I read this in the early part of 2020。 I had been exploring concepts in machine learning and developments in Artificial intelligence and I have always had an interest in human cognition and learning。 This book combined both topics and compares and contrasts the functioning down to some real nuts and bolts of both human and machine learning。 Humans and machine learning via neural networks （which oddly enough are modeled somewhat on animal neural systems） have a lot of similarities。 It seems logic I read this in the early part of 2020。 I had been exploring concepts in machine learning and developments in Artificial intelligence and I have always had an interest in human cognition and learning。 This book combined both topics and compares and contrasts the functioning down to some real nuts and bolts of both human and machine learning。 Humans and machine learning via neural networks （which oddly enough are modeled somewhat on animal neural systems） have a lot of similarities。 It seems logical categorical processing systems are great expert systems and good algorithms for expert and bureaucratic decision-making bodies developed in the early days of AI research are very alien to the way humans think。 Do things precisely and efficiently way beyond human capacity but needed strict rules and had a hard time with novelty and ambiguity or not well-formed problems to tackle。 The newer neural nets took a long time to get off the ground but can do amazing things at visual or audio tasks of distinguishing objects that are novel and not labeled in a clear-cut manner。 It is also good at cluster messy data and fitting it into digestible graphical layouts and clusters。 It also much like people require large amounts of training sets and use feedback in performance to "learn" and be evaluate performance before it is unleashed on novel data。 The book gets down to the nuts and bolts of such systems and where they look like human learning and cognition and places where they diverge from it。 Definitely will hit this one again in the near future。 。。。more
Sofia
，
Dios， no hay palabras para describir este libro， es la perfección en cada pagina descubría cosas tan sorprendentes。 Realmente me sorprendió
Marcelo Galuppo
，
As ciências cognitivas viveram sua pré-história， com Pavlov， Piaget， Vygotsky。 Agora， parece que chegamos à fase científica da Psicologia Cognitiva， com os avanço do conhecimento do cérebro adquirido com a Ressonância Magnética。 Esse é um pressuposto que está por trás do novo trabalho do neurocientista e psicólogo cognitivo Stanislas Dehaene， How We Learn （New York: Viking， 2020）。Dehaene define a aprendizagem como a formulação de um modelo cerebral preditivo e auto-ajustável do mundo externo （es As ciências cognitivas viveram sua pré-história， com Pavlov， Piaget， Vygotsky。 Agora， parece que chegamos à fase científica da Psicologia Cognitiva， com os avanço do conhecimento do cérebro adquirido com a Ressonância Magnética。 Esse é um pressuposto que está por trás do novo trabalho do neurocientista e psicólogo cognitivo Stanislas Dehaene， How We Learn （New York: Viking， 2020）。Dehaene define a aprendizagem como a formulação de um modelo cerebral preditivo e auto-ajustável do mundo externo （esta definição não aparece nesses exatos termos， mas creio ser bem fiel à ideia do autor）， mecanismo altamente vantajoso do ponto de vista evolutivo que pressupõe que alguns parâmetros estão inseridos geneticamente desde sempre em nosso cérebro， enquanto outros são desenvolvidos a partir do influxo do ambiente。 Aprender （de uma maneira muito mais elaborada que qualquer animal ou máquina pode fazer） é a característica que nos define como espécie， a ponto de a transformarmos em uma experiência coletiva nas salas de aula， o que faz da metacognição （aprender a aprender） a característica mais importante para nossa existência enquanto seres humanos。Dehaene afasta a ideia empirista de que o cérebro é uma folha de papel em branco sobre o qual se inscrevem os dados da realidade。 Na verdade， nosso cérebro foi se desenvolvendo para estabelecer， desde o nascimento， alguns padrões prévios ao contato com o mundo externo que nos permitem organizar e manejar os dados da experiência （como o conceito de objeto， o senso de número， a intuição de probabilidades， a percepção de rostos como um objeto específico， a tendência ao desenvolvimento de uma linguagem， um certo GPS que nos permite localizarmo-nos no espaço）。Para aprender， o cérebro vai criando experimentos randomizados que permitem levar a uma generalização probabilística dos dados da consciência， mais ou menos como faz a Inteligência Artificial。 Ao formular modelos que melhor correspondem à realidade， o cérebro vai produzindo um processo de recompensa por meio do sistema de dopamina， o que torna altamente prazeroso descobrir como a realidade funciona。 No entanto， o cérebro consegue fazer isso de maneira muito mais eficiente， como muito menos dados， que a Inteligência artificial。 Não se trata apenas de reconhecer um padrão nos dados （que é o que a Inteligência Artificial atualmente faz）， mas de formular um modelo mental explicativo para a realidade por meio dos dados。 Na evolução desse modelo， novos dados （convergentes） vão aumentando a amplitude e aplicabilidade do modelo， enquanto dados divergentes vão corrigindo o modelo （o que faz do erro algo fundamental ao processo de aprendizagem）。Durante a infância （especialmente nos dois primeiros anos de vida， mas até o final da adolescência， o que me lembrou muito o livro de Frances E。 Jensen， O Cérebro Adolescente）， uma incrível plasticidade faz com que as sinapses se tornem mais eficientes para que o cérebro seja apto a elaborar tais modelos cognitivos， sob a influência da genética e do ambiente ao mesmo tempo （por isso um ambiente rico é fundamental para o desenvolvimento das suas potencialidades）。 Existem “períodos sensíveis” em que determinadas habilidades se desenvolvem， o que é determinado pela maturação biológica do cérebro， universalmente idêntica nos seres humanos， mas é possível “reciclar” as regiões do cérebro （durante os períodos sensitivos） para que uma parte do cérebro se especialize em uma função （ou assuma a função de outra parte do cérebro）， aumentando sua eficiência。 Isso não acontece apenas com o cérebro que possui uma lesão， mas em toda maturação normal do cérebro humano （por exemplo， no processo de aprender a ler ou a calcular， à medida que automatizamos o processo， regiões distintas das iniciais se ocupam da tarefa）。 Dehaene afasta a ideia que cada pessoa tem um modo diferente de aprender。 Dito de uma maneira melhor: a técnica de ressonância magnética mostra que todos aprendem do mesmo modo， apesar de a velocidade com que isso ocorra seja altamente variável， sobretudo por causa do ambiente。 A notícia ruim é que a ideia de um período sensitivo indica que há um período ótimo para que isso ocorra （por exemplo， pessoas que aprendem a ler quando adultas， ou que têm que reaprender a ler por causa de um AVC， nunca serão leitores tão competentes quanto crianças que aprenderam a ler na idade correta porque a transferência do processo para regiões do cérebro em que isso ocorre automaticamente não ocorre mais）。 Toda a pesquisa de Dehaene mostra que há equívocos nas teorias comportamentais da aprendizagem （como Pavlov e Skinner， que erraram ao pensar que o estímulo fosse o elemento causalmente determinante na aprendizagem）， mas também nas cognitivistas （como Piaget， que errou ao afirmar que noções como o número e a permanência de objetos físicos são desenvolvidas pela experiência）。Como sabemos que o meio ambiente interfere no processo， há quatro pontos （chamados de “pilares da aprendizagem”） em que se pode intervir para se aumentar a eficiência da aprendizagem: a） atenção （o professor ou quem ensina precisa chamar atenção do aluno para que ele saiba quando prestar atenção e sobre o que， para que ele possa selecionar na multiplicidade de dados a informação relevante， evitando a saturação de informação， – que é exatamente o que a Inteligência Artificial ainda não consegue fazer）; b） levar o aluno a se engajar ativamente （ao performar a ação， ainda que apenas mentalmente， o cérebro não apenas a memoriza， mas testa modelos alternativos pouco eficientes）; c） dar feedback do erro （quanto mais próximo temporalmente do erro e quanto mais preciso o feedback， maior a capacidade de a criança descartar o motivo do erro）; d） fornecer consolidação （o cérebro continua testando hipóteses e modelos durante o sono， inconscientemente， e agora de modo exclusivo， sem se preocupar com outros estímulos， e é por isso que o sono auxilia na fixação do conhecimento e na resolução de problemas）。Por isso ensinar é prestar atenção ao conhecimento de outra pessoa。 Isso explica porque a aula expositiva é tão bem sucedida se bem realizada （se conseguir provocar a atenção， o engajamento e se produzir o feedback do erro – cuja melhor forma de se realizar é através de testes não punitivos， ou seja， sem atribuição de nota）， mais do que uma perspectiva radicalmente construtivista。 Por isso o espaçamento da aprendizagem （como preconizada por Ebbinghaus e Leitner， ainda que com algumas críticas a eles） se revela a melhor estratégia para prolongar a permanência da memória do que foi aprendido （por causa， dentre outras coisas， da intervenção do sono no processo de aprendizagem）。Trata-se de um livro importante para educadores e pais， a que eu daria uma nota 04 （em 05）。 。。。more
Ankit
，
"A child's brain is NOT a blank slate"。Using our current （2020） knowledge and understanding from Neuroscience， Cognitive Psychology， Computer Science， Educational， and Sleep research fields， Dehaene draws the architecture of the brain's learning algorithm， and provides approaches that seem to maximise learning process based on the available data。Answering the "Nature vs Nurture" argument， he states how all human brains （and the inspired AI algorithms） are born with a "natural" innate knowledge - "A child's brain is NOT a blank slate"。Using our current （2020） knowledge and understanding from Neuroscience， Cognitive Psychology， Computer Science， Educational， and Sleep research fields， Dehaene draws the architecture of the brain's learning algorithm， and provides approaches that seem to maximise learning process based on the available data。Answering the "Nature vs Nurture" argument， he states how all human brains （and the inspired AI algorithms） are born with a "natural" innate knowledge - a start-up kit of sorts i。e。 Nature; and， how we then use this start-up kit to further build up （grow into） an advanced learning tool （the educated brain） which constantly learns and readjusts according to the environment it finds itself in - Nurture。 Drawing on research on human learning and development of the Machine Learning algorithms， he describes four components of learning as:1。 Attention2。 Active Participation3。 Error Feedback4。 Consolidation。An informative read， and more so for （planning-to-be）parents and teachers， if you've not been caught up with our latest understanding of how we learn。 。。。more
Atila Iamarino
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Temos uma discussão sobre aprendizagem enorme no Brasil， mas pouco da nossa educação leva em conta experimentos controlados que comparam como as pessoas aprendem。 Só este passo já é o que faz livros sobre como aprendemos como o ótimo How We Learn: The Surprising Truth About When， Where， and Why It Happens e este livro do Dehaene acrescentarem muito。Mas Dehaene vai além。 Ele aproveita o avanço da inteligência artificial até aqui para comparar como modelos de aprendizagem de máquina funcionam e on Temos uma discussão sobre aprendizagem enorme no Brasil， mas pouco da nossa educação leva em conta experimentos controlados que comparam como as pessoas aprendem。 Só este passo já é o que faz livros sobre como aprendemos como o ótimo How We Learn: The Surprising Truth About When， Where， and Why It Happens e este livro do Dehaene acrescentarem muito。Mas Dehaene vai além。 Ele aproveita o avanço da inteligência artificial até aqui para comparar como modelos de aprendizagem de máquina funcionam e onde falham， e o que nós fazemos de diferente。 Isso é muito bom para avançar a computação e nosso entendimento do cérebro também。 Um dos maiores saltos que a computação ainda precisa fazer e nosso cérebro dá conta muito bem é de quão pouca informação precisamos para aprender。 Nós extrapolamos muito com bem pouco。 O Google Translate precisou de milhares de livros e documentos， anos e treino de pessoas para chegar em um modelo de tradução parecido com o que uma pessoa pode aprender por conta própria e muito menos leitura。 Dehaene vai fazendo esse tipo de comparação， decomposição e explicação o longo do livro todo mostrando como derivamos informação， a importância de outras pessoas para podermos aprender e como funcionam modelos de aprendizagem com recompensa （como nossa curiosidade satisfeita）。 Tudo isso dando extrapolações de como o ensino pode aproveitar essas habilidades。 。。。more
Barbara
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This book was both fabulous and frustrating to me， mostly because of my personal viewpoints。 I am a reading specialist at a Christian school with extensive experience as a second grade teacher before that。 The author’s account of how our brain learns seems credible; his conclusions are research based and partially proven through brain imaging。 I found the information very useful and informative。 He came from an evolutionary viewpoint many times， and at one point seemed to refer to all religious This book was both fabulous and frustrating to me， mostly because of my personal viewpoints。 I am a reading specialist at a Christian school with extensive experience as a second grade teacher before that。 The author’s account of how our brain learns seems credible; his conclusions are research based and partially proven through brain imaging。 I found the information very useful and informative。 He came from an evolutionary viewpoint many times， and at one point seemed to refer to all religious thought as myths that were not intellectually examined enough。 These are the points I took exception to and personally would refute。 I am a Christian， and I feel intelligent design fits perfectly with what he said and fills in gaps evolution couldn’t fully explain。 Also， especially in recent years， archeologists have found excellent evidence that the Bible is historically accurate。 This did not prevent me from getting lots of useful ideas on how to help my students retain more。 。。。more
Matthieu Nicolle
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Amazing
Matt Hutson
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How We Learn by Stanislas Dehaene is one of the best books about learning that I have read。 I imagine， as a teacher myself， that this book is most helpful for those in the education industry。 However， if you are an entreprenuer， business owner， or any conceivable field of work， if you want to become better at learning this book can help you to do that。 The core of the book is based on The Four Pillars of Learning:1。 Attention 2。 Active Engagement 3。 Error Feedback 4。 ConsolidationThese four pill How We Learn by Stanislas Dehaene is one of the best books about learning that I have read。 I imagine， as a teacher myself， that this book is most helpful for those in the education industry。 However， if you are an entreprenuer， business owner， or any conceivable field of work， if you want to become better at learning this book can help you to do that。 The core of the book is based on The Four Pillars of Learning:1。 Attention 2。 Active Engagement 3。 Error Feedback 4。 ConsolidationThese four pillars can be used both in child learning and adult learning。As a creator of an online course about how to become a better reader having a framework like the one above turns out to be extremely useful。 And you， the reader of this review， can use this framework in your own learning。I would highly recommend this book to anyone who is looking to improve the way they learn and to understand how they can teach others how to learn better as well。 。。。more
Apoorv Mathur
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This book had a good way to connect what we know about human learning to AI/neural networks。
Naeem Ilyas
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This book is very interesting， accessible to general audience and there are a lot of insights to gain from it。 A few interesting points:The brain of a baby is not like a blank slate， they already possess a vast set of knowledge which is a result of evolution。 Human babies come into this world with an innate knowledge of objects， numbers and physics （it’s demonstrated in lab experiments that babies show surprise if they see some laws of physics， arithmetic， psychology being violated）， these are t This book is very interesting， accessible to general audience and there are a lot of insights to gain from it。 A few interesting points:The brain of a baby is not like a blank slate， they already possess a vast set of knowledge which is a result of evolution。 Human babies come into this world with an innate knowledge of objects， numbers and physics （it’s demonstrated in lab experiments that babies show surprise if they see some laws of physics， arithmetic， psychology being violated）， these are the concepts AI systems struggle to learn Current learning algorithms capture only a fraction of the abilities of human brain The human brain’s plasticity is limited in space and time。 Some areas simply freeze after a certain age e。g。; if you want to speak in the accent of the native speakers you got to learn that language before age 10！ Nature and nurture both play the part。 35-50% of our traits are hereditary During sleep our brain replays the events of the day multiple time & at a faster speed。 So for example if you learned to drive during the day， your brain will repeat that during sleep which helps consolidate the learning 。。。more
Derek Henderson
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Nothing groundbreaking。 Dehaene treads familiar ground， is himself befuddled in certain points， and thus confuses the reader。
Megan S
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Wordy and sometimes just plain inaccurate。 You can just read the conclusion to get all the important information from this book and none of it was new to me。
McNeil Higgins
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An excellent summary of the current science around learning。 I'm a graduate student in educational psychology and still picked up some very key concepts。 An excellent summary of the current science around learning。 I'm a graduate student in educational psychology and still picked up some very key concepts。 。。。more
Riccardo
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Just four out of five stars because， even if the book is really well written， interesting and inspirational I don't understand how this research could already be so mature to address children education and teacher training。 Either I am missing some important link or it seems to me that the research reported is still too basics to really be used to address education problems with confidence。Furthermore， the answer to the title of the book is not actually answered which， however， was kind of expec Just four out of five stars because， even if the book is really well written， interesting and inspirational I don't understand how this research could already be so mature to address children education and teacher training。 Either I am missing some important link or it seems to me that the research reported is still too basics to really be used to address education problems with confidence。Furthermore， the answer to the title of the book is not actually answered which， however， was kind of expected considering that he's a neuroscientist and not a programmer。 But still。。。the title is misleading。 。。。more
Daniele Di Mitri
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