什么是学习？

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來自 McMaster University 的課程

学会如何学习：帮助你掌握复杂学科的强大智力工具（Learning How to Learn）

742 個評分

McMaster University

学会如何学习：帮助你掌握复杂学科的强大智力工具（Learning How to Learn）

742 個評分

本课程将介绍各领域专家所使用的学习方法，他们包括艺术家、文学家、数学家、科学家、运动员和很多其他领域专家。我们将学习如何使用两种不同的大脑模式，以及大脑如何封装（“chunks”）信息。我们还将介绍能力错觉（illusions of learning），记忆技巧，对付拖延症的方法，以及研究表明能帮助我们掌握困难科目的方法。无论您在所学领域是专家还是菜鸟，您都可以使用这些方法，改变自己的思维模式，重塑自己的人生。如果您是所学领域的专家，通过学习大脑认知的底层知识，您可以进一步提高自己的学习能力，您将了解反直觉的考试技巧和见解，从而能够更高效地完成作业和习题。如果您在学习中遇到困难，系统有效的学习技巧将帮助您将走上正轨。无论您希望学习什么内容，这门课程都可以作为您的指南。

從本節課中

什么是学习？

尽管活体大脑相当复杂，但此单元将利用隐喻与类比帮助简化内容。你将发现几个完全不同的思维模式，并了解能怎样利用这些模式改进自己的学习。你还将接触到一项治疗拖延症的工具，获得一些有关记忆的实用信息，并意外地挖掘到一些有关学习与睡眠的实用见解。如果你希望作好更充分的准备，那么可以选读《数字思维》（非必修内容，但却是此MOOC的基础教材）。该书也已有华语简体版《学习之道》和华语繁体版《用對腦，從此不再怕數字：學會如何學習，以如何創意思考，解決(幾乎)所有的問題》，还将推出更多外语版本，敬请期待。这本书让你有机会巩固在本课程中学到的学习方法，你可以在空白处作笔记或以电子笔记的形式帮助进一步推动思维的“组块化”。

集中与发散思维概论4:40

Terrence Sejnowski与Barbara Oakley——课程结构介绍2:50

利用集中与发散思维，或者采用一点画家达利所用的方法也行4:02

什么是学习？5:40

與講師見面

Dr. Barbara Oakley
Ramón y Cajal Distinguished Scholar of Global Digital Learning, McMaster University
Professor of Engineering, Industrial & Systems Engineering, Oakland University
Dr. Terrence Sejnowski
Francis Crick Professor at the Salk Institute for Biological Studies
Computational Neurobiology Laboratory
Hong Chee Joo

Welcome to learning how to learn.

My name is Terry Sejnowski.

Let me introduce you to your brain.

First, some brain surgery.

We take off the skull and take out the brain.

This brain weighs three pounds, but it consumes ten times more

energy by weight than the rest of the body, a very expensive organ.

It is the most complex device in the known universe.

All of your thoughts, your hopes, your fears are in the neurons in this brain.

We prize our abilities to do chess and math, but

it takes years of practice to acquire these skills.

And digital computers are much better at it than we are.

It came as a surprise to discover that what we do so well and take for

granted, like seeing, hearing, reaching, running,

are all much more complex problems than we thought and

way beyond the capability of the world's fastest digital computers.

What this illustrates is that we are not consciously aware of how our brains work.

Brains evolved to help us navigate complex environments, and

most of the heavy lifting is done below our level of consciousness.

And we don't need to know how it's done in order to survive.

Psychologists who study the unconscious mind have found that influences

include thought processes, memory, emotions and motivation.

We are only aware of a very small fraction of all of the activity in the brain, so

we need to rely on brain imaging techniques to guide us.

Here is the activity map of someone's brain who was asked to lie still,

at rest, in a brain imaging scanner.

On the left is the side view of the brain and

on the right is the view from the midline.

The colors indicate brain areas whose activities were highly correlated,

as shown by the time courses below, color-coded to the brain areas.

The blue areas are highly active when the subject interacts with the world, but

turn off in a resting state.

The red-orange areas are most active in the resting state and

are called the default mode network.

Other brain areas are also more active when you are resting, and these areas can

be further divided into groups of areas that have common patterns of activity.

This is a new and intense area of research, and

it will take time to sort out all the resting states and their functions.

There are a million billion synapses in your brain where memories are stored.

The old view of the brain is that once it matures,

the strengths of synapses can be adjusted by learning, but

the pattern of connectivity does not change much unless there is brain damage.

But now we know that brain connectivity is dynamic and

remains so even after it matures.

With new optical techniques for

imaging single connections between neurons called synapses, we can see

constant turnover, with new synapses being formed and others disappearing.

This raises a puzzle.

In the face of so much turnover, how do memories stay stable over so many years?

This is a picture of one dendritic branch on a neuron which

receives inputs from other neurons.

The synapses are on the spiny knobs coming off the dendrite.

On the top, the dendrite was imaged before learning.

The same dendrite is shown below after learning and after sleep.

Multiple synapses that are newly formed

together on the same branch are indicated by the white arrowheads.

You are looking down into the brain of a live animal.

This is really a fantastic new technique.

Synapses are less than a micron in diameter.

In comparison, a human hair is around 20 microns in diameter.

This new technique allows us to see how learning changes the structure of

the brain with a resolution that is near the limit of light microscopy.

This illustrates that, intriguingly,

that you are not the same person you were after a night's sleep or even a nap.

It is if you went to bed with one brain and woke up with an upgrade.

This is a better deal than you can get from Microsoft.

Shakespeare, the great English poet, already knew this.

Here is Macbeth lamenting his insomnia.

Sleep that knits up the raveled sleeve of care, the death of each day's life,

sore labor's bath, balm of hurt minds,

great nature's second course, chief nourisher in life's feast.

Here Shakespeare is making an analogy between knitted clothes and

sleep that knits up the loose threads of experience and

concerns during the day and weaves them into the tapestry of your life story.

You will learn in this first week how to take advantage of your unconscious mind,

and also sleep, to make it easier to learn new things and solve problems.

During the lectures you may ask yourself, how does the brain do this?

A good place to find out more about your brain is the website brainfacts.org,

brainfacts, one word, .org.

You will find a wealth of interesting things about brains and behavior, and

in particular about learning and memory.

I am Terry Sejnowski.

Happy learning until we meet again.

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