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How We Learn: Why Brains Learn Better Than Any Machine . . . for Now
(OverDrive MP3 Audiobook, OverDrive Listen)

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Author:
Dehaene, Stanislas
Narrator:
Griffith, Kaleo
Published:
Books on Tape 2020
Status:
Available from OverDrive
Description
“There are words that are so familiar they obscure rather than illuminate the thing they mean, and ‘learning’ is such a word. It seems so ordinary, everyone does it. Actually it’s more of a black box, which Dehaene cracks open to reveal the awesome secrets within.”—The New York Times Book Review
An illuminating dive into the latest science on our brain's remarkable learning abilities and the potential of the machines we program to imitate them
The human brain is an extraordinary learning machine. Its ability to reprogram itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. But how do we learn? What innate biological foundations underlie our ability to acquire new information, and what principles modulate their efficiency?
In How We Learn, Stanislas Dehaene 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 and at any age.
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Subjects
Subjects
Education
Science
Nonfiction
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Format:
OverDrive MP3 Audiobook, OverDrive Listen
Edition:
Unabridged
Street Date:
01/28/2020
Language:
English
ISBN:
9780593165898
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Citations
APA Citation (style guide)

Stanislas Dehaene. (2020). How We Learn: Why Brains Learn Better Than Any Machine . . . for Now. Unabridged Books on Tape.

Chicago / Turabian - Author Date Citation (style guide)

Stanislas Dehaene. 2020. How We Learn: Why Brains Learn Better Than Any Machine . . . for Now. Books on Tape.

Chicago / Turabian - Humanities Citation (style guide)

Stanislas Dehaene, How We Learn: Why Brains Learn Better Than Any Machine . . . for Now. Books on Tape, 2020.

MLA Citation (style guide)

Stanislas Dehaene. How We Learn: Why Brains Learn Better Than Any Machine . . . for Now. Unabridged Books on Tape, 2020.

Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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Grouped Work ID:
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Needs Update?:
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Date Added:
Jan 23, 2020 14:29:09
Date Updated:
Dec 08, 2020 00:39:23
Last Metadata Check:
Apr 15, 2024 08:07:01
Last Metadata Change:
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Last Availability Check:
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Last Grouped Work Modification Time:
Apr 20, 2024 02:11:00

OverDrive Product Record

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“There are words that are so familiar they obscure rather than illuminate the thing they mean, and ‘learning’ is such a word. It seems so ordinary, everyone does it. Actually it’s more of a black box, which Dehaene cracks open to reveal the awesome secrets within.”—The New York Times Book Review
An illuminating dive into the latest science on our brain's remarkable learning abilities and the potential of the machines we program to imitate them
The human brain is an extraordinary learning machine. Its ability to reprogram itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. But how do we learn? What innate biological foundations underlie our ability to acquire new information, and what principles modulate their efficiency?
In How We Learn, Stanislas Dehaene 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 and at any age.
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      • source: Publisher's Weekly
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        October 28, 2019
        Dehaene (Consciousness in the Brain), a professor of experimental psychology at the Collège de France, devotes this detailed, sometimes hard-going, but stimulating study to the science of learning. The first half largely concerns brain physiology, touching on, among other subjects, how learning can physically change the brain, such as by thickening the cortex. Dehaene also refutes the idea of the “blank slate” infant brain, noting that “even a baby... encodes the external world using abstract and systematic rules—an ability that eludes... conventional artificial neural networks.” The book’s second, less technical and more widely accessible half explores the “four pillars” of learning: attention, active engagement, error feedback, and consolidation of information (for which REM sleep is especially key) and discusses how enjoyment can assist learning—Dehaene notes that laughter seems to enhance curiosity and memory. While calling for more research into the field, he issues his most potentially controversial pronouncement, at least for neurodiversity advocates: “We all face similar hurdles in learning and the same teaching methods can surmount them.” At times not an easy book to comprehend, it will nonetheless be a richly instructive one for educators, parents, and others interested in how to most effectively foster the pursuit of knowledge. Agent: Max Brockman, Brockman, Inc.

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“There are words that are so familiar they obscure rather than illuminate the thing they mean, and ‘learning’ is such a word. It seems so ordinary, everyone does it. Actually it’s more of a black box, which Dehaene cracks open to reveal the awesome secrets within.”—The New York Times Book Review
An illuminating dive into the latest science on our brain's remarkable learning abilities and the potential of the machines we program to imitate them
The human brain is an extraordinary learning machine. Its ability to reprogram itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. But how do we learn? What innate biological foundations underlie our ability to acquire new information, and what principles modulate their efficiency?
In How We Learn, Stanislas Dehaene finds the boundary of computer science, neurobiology, and cognitive psychology to explain how...
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