Based in part on: Apprendre! : les talents du cerveau, le défi des machines. Includes bibliographical references and index.
Contents:
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.
Summary:
"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"-- Provided by publisher.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.