How we learn : why brains learn better than any machine ... for now / Stanislas Dehaene.

By:

Dehaene, Stanislas [Author]

Material type: Text

TextLanguage: English Original language: French Publication details: New York, New York : Viking, (c)2020.Edition: First American editionDescription: xxviii, 319 pages, 16 unnumbered pages of plates : illustrations ; 24 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780525559887
9780525559894

Subject(s):

Neuroplasticity

LOC classification:

BF318 .H699 2020
BF318

Available additional physical forms:

Contents:

Why our brain learns better than current machines -- Babies' invisible knowledge -- The birth of a brain -- Nurture's share -- Recycle your brain -- Attention -- Active engagement -- Error feedback -- Consolidation -- Conclusion. Reconciling education with neuroscience.

Subject: "In today's technological society, with an unprecedented amount of information at our fingertips, learning plays a more central role than ever. In How We Learn, Stanislas Dehaene decodes its biological mechanisms, delving into the neuronal, synaptic, and molecular processes taking place in the brain. 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, and that we can enhance our learning and memory at any age. We can all '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. The exciting advancements in A.I. of the last twenty years reveal just as much about our remarkable abilities as they do about the potential of machines. How We Learn finds the boundary of computer science, neurobiology, and cognitive psychology to explain how learning really works and how to make the best use of the brain's learning algorithms, in our schools and universities as well as in everyday life"--

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Circulating Book (checkout times vary with patron status)	G. Allen Fleece Library CIRCULATING COLLECTION	Non-fiction	BF318.D322.H699 2020 (Browse shelf(Opens below))	Available		31923001904784

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Previous	BF295.R45 2014 The relation of childhood physical activity to brain health, cognition, and scholastic achievement /edited by Charles H. Hillman, Darla M. Castelli, Laura Chaddock-Heyman, Neal J. Cohen, Katelin da Cruz, Sharon M. Donovan, Ellen M. Evans, Jodene G. Fine, Ken A Frank, Bonnie Hemrick, Keita Kamijo, Naiman A. Khan, Arthur F. Kramer, Edward McAuley, Andrew C. Parks, Matthew B. Pontifex, Lauren B. Raine, Mark R. Scudder, Alan L. Smith, Thomas R. Wojcicki ; with commentary by Carol L. Cheatham.	BF311.F743 2012 Cognitive science : an introduction to the study of mind /	BF311.W5D4 2011 The development of ambiguous figure perception /Marina C. Wimmer and Martin J. Doherty.	BF318.D322.H699 2020 How we learn : why brains learn better than any machine ... for now /	BF318.G34 1981 The learning theory of Piaget and Inhelder /	BF318.S93 Theories of learning : traditional perspectives/contemporary developments /	BF318.W35 1996 The psychology of learning : principles and processes /	Next

Based in part on: Apprendre! : les talents du cerveau, le defi des machines.

Seven definitions of learning -- Why our brain learns better than current machines -- Babies' invisible knowledge -- The birth of a brain -- Nurture's share -- Recycle your brain -- Attention -- Active engagement -- Error feedback -- Consolidation -- Conclusion. Reconciling education with neuroscience.

"In today's technological society, with an unprecedented amount of information at our fingertips, learning plays a more central role than ever. In How We Learn, Stanislas Dehaene decodes its biological mechanisms, delving into the neuronal, synaptic, and molecular processes taking place in the brain. 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, and that we can enhance our learning and memory at any age. We can all '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. The exciting advancements in A.I. of the last twenty years reveal just as much about our remarkable abilities as they do about the potential of machines. How We Learn finds the boundary of computer science, neurobiology, and cognitive psychology to explain how learning really works and how to make the best use of the brain's learning algorithms, in our schools and universities as well as in everyday life"--

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