How we learn: why brains learn better than any machine ... for now
(Book)
"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"--
Notes
Dehaene, S. (2020). How we learn: why brains learn better than any machine ... for now. First American edition. [New York, New York], Viking.
Chicago / Turabian - Author Date Citation (style guide)Dehaene, Stanislas. 2020. How We Learn: Why Brains Learn Better Than Any Machine ... for Now. [New York, New York], Viking.
Chicago / Turabian - Humanities Citation (style guide)Dehaene, Stanislas, How We Learn: Why Brains Learn Better Than Any Machine ... for Now. [New York, New York], Viking, 2020.
MLA Citation (style guide)Dehaene, Stanislas. How We Learn: Why Brains Learn Better Than Any Machine ... for Now. First American edition. [New York, New York], Viking, 2020.
Record Information
| Last Sierra Extract Time | Apr 12, 2024 05:24:18 PM |
|---|---|
| Last File Modification Time | Apr 12, 2024 05:24:41 PM |
| Last Grouped Work Modification Time | Apr 23, 2024 02:10:41 AM |
MARC Record
| LEADER | 03746pam a2200517 i 4500 | ||
|---|---|---|---|
| 001 | 2019036724 | ||
| 003 | DLC | ||
| 005 | 20200124125407.0 | ||
| 008 | 191229s2020 nyua b 001 0 eng | ||
| 010 | |a 2019036724 | ||
| 020 | |a 9780525559887 | ||
| 040 | |a LBSOR/DLC|b eng|e rda|c DLC|d NjBwBT | ||
| 041 | 1 | |a eng|h fre | |
| 042 | |a pcc | ||
| 049 | |a JRSA | ||
| 050 | 0 | 0 | |a BF318|b .D44 2020 |
| 082 | 0 | 0 | |a 153.1/5|2 23 |
| 099 | |a 612 D322 2020 | ||
| 100 | 1 | |a Dehaene, Stanislas,|e author. | |
| 240 | 1 | 0 | |a Apprendre!|l English |
| 245 | 1 | 0 | |a How we learn :|b why brains learn better than any machine ... for now /|c Stanislas Dehaene. |
| 250 | |a First American edition. | ||
| 264 | 1 | |a [New York, New York] :|b Viking,|c 2020. | |
| 300 | |a xviii, 319 pages :|b illustrations (some color) ;|c 24 cm | ||
| 336 | |a text|b txt|2 rdacontent | ||
| 337 | |a unmediated|b n|2 rdamedia | ||
| 338 | |a volume|b nc|2 rdacarrier | ||
| 500 | |a Translation of: Apprendre! : les talents du cerveau, le défi des machines. | ||
| 504 | |a Includes bibliographical references (pages 269-305) and index. | ||
| 505 | 0 | |a 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. | |
| 520 | |a "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"--|c Provided by publisher. | ||
| 650 | 0 | |a Learning, Psychology of. | |
| 650 | 0 | |a Cognitive psychology. | |
| 650 | 0 | |a Neuroplasticity. | |
| 650 | 0 | |a Cognitive science. | |
| 776 | 0 | 8 | |i Online version:|a Dehaene, Stanislas.|s Apprendre! English.|t How we learn|d [New York, New York] : Viking, 2020.|z 9780525559894|w (DLC) 2019036725 |
| 907 | |a .b26196049 | ||
| 945 | |y .i82617363|i 33029108006586|l cenag|s -|k |u 7|x 3|w 1|v 12|t 3|z 01-30-20|o - | ||
| 945 | |y .i82617387|i 33029108006602|l souag|s -|k 05-03-24|u 4|x 0|w 1|v 17|t 3|z 01-30-20|o - | ||
| 945 | |y .i82617399|i 33029108006610|l carag|s -|k |u 5|x 3|w 1|v 3|t 3|z 01-30-20|o - | ||
| 945 | |y .i82617405|i 33029108006628|l ranag|s -|k |u 7|x 2|w 1|v 15|t 3|z 01-30-20|o - | ||
| 945 | |y .i83468511|i 31652003270114|l wdpa|s -|k |u 3|x 1|w 0|v 4|t 0|z 07-29-20|o l|a 153.1 Deh 2020 | ||
| 995 | 0 | |a Loaded with m2btab.marciveb 2020-02 | |
| 995 | 0 | |a Loaded with m2btab.splbtbi 2020-01 | |
| 995 | 0 | |a Loaded with m2btab.ingra 2019-11 | |
| 998 | |e -|d a |f eng|a car|a cen|a ran|a sou|a wdp | ||
