请双击下面的英文字幕来播放视频。
翻译人员: Shelly SUN
校对人员: Angelia King
00:15
We've got a real problem with math education right now.
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目前我们的数学教育面临着实际的问题。
00:19
Basically, no one's very happy.
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基本上,没有人感到很满意。
00:22
Those learning it
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那些学习数学的学生
00:24
think it's disconnected,
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觉得所学的知识与实际无关,
00:26
uninteresting and hard.
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无趣以及困难重重。
00:28
Those trying to employ them
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那些运用数学的人们
00:30
think they don't know enough.
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又觉得他们所学的知识不够。
00:32
Governments realize that it's a big deal for our economies,
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政府觉察到这是一个涉及到我们经济发展的大问题,
00:35
but don't know how to fix it.
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但他们却无从下手。
00:38
And teachers are also frustrated.
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而老师们也感到很沮丧。
00:40
Yet math is more important to the world
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但是现在的数学
00:43
than at any point in human history.
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比人类历史上任何时间都更为重要。
00:45
So at one end we've got falling interest
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一方面我们逐渐丧失
00:47
in education in math,
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对数学教学的兴趣,
00:49
and at the other end we've got a more mathematical world,
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另一方面,我们的世界却比以前
00:52
a more quantitative world than we ever have had.
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更加趋向于数学化、数量化的数形世界中。
00:56
So what's the problem, why has this chasm opened up,
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那么问题到底出在哪里,为什么产生了这样的分歧?
00:58
and what can we do to fix it?
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我们该怎么解决这个问题?
01:01
Well actually, I think the answer
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我想,答案就在
01:03
is staring us right in the face:
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我们眼前。
01:05
Use computers.
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使用计算机。
01:07
I believe
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我相信
01:09
that correctly using computers
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恰当地使用计算机
01:11
is the silver bullet
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是使数学教育变得有效的
01:13
for making math education work.
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一剂良方。
01:16
So to explain that,
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在解释之前,
01:18
let me first talk a bit about what math looks like in the real world
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让我简要对比一下我们现实世界中的数学
01:21
and what it looks like in education.
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和教学中的数学。
01:23
See, in the real world
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现实世界中
01:25
math isn't necessarily done by mathematicians.
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数学并不是数学家的专用品。
01:28
It's done by geologists,
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地质学家、
01:30
engineers, biologists,
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工程师、生物学家
01:32
all sorts of different people --
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等各行各业
01:34
modeling and simulation.
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都可能运用数学进行数模和模拟。
01:36
It's actually very popular.
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数学的应用实际上是非常广泛。
01:38
But in education it looks very different --
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然而,教学中的数学则完全不同--
01:41
dumbed-down problems, lots of calculating,
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它带有很多愚蠢的问题,大量的运算--
01:43
mostly by hand.
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还多数是人工笔头运算。
01:46
Lots of things that seem simple
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许多看起来很简单的,
01:48
and not difficult like in the real world,
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不及现实世界中复杂的问题,
01:50
except if you're learning it.
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在学习的过程中都变得很困难。
01:53
And another thing about math:
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关于数学的另一点就在于
01:55
math sometimes looks like math --
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数学有时看起来很“数学”
01:57
like in this example here --
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就像这个例子--
02:00
and sometimes it doesn't --
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不过有时又不像--
02:02
like "Am I drunk?"
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比如说“我醉了吗?”
02:07
And then you get an answer that's quantitative in the modern world.
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你会得到一个在现实世界中量化的答案。
02:10
You wouldn't have expected that a few years back.
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几年前,你并不能预期你会得到这样的答案。
02:13
But now you can find out all about --
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但是现在你可以了解到...
02:16
unfortunately, my weight is a little higher than that, but --
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抱歉其实我的体重比这个更重一点,但是--
02:19
all about what happens.
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了解到所发生的这一切。
02:21
So let's zoom out a bit and ask,
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我们退一步再来看看,
02:23
why are we teaching people math?
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我们为什么要教数学呢?
02:25
What's the point of teaching people math?
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教数学有什么意义呢?
02:28
And in particular, why are we teaching them math in general?
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尤其是,为什么我们要将数学作为通识基础教育呢?
02:31
Why is it such an important part of education
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为什么数学是教育的一个重要组成部分呢?
02:34
as a sort of compulsory subject?
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为什么要作为必修课呢?
02:36
Well, I think there are about three reasons:
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我想,这大概有以下三个理由:
02:39
technical jobs
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一是完成技术工作。
02:41
so critical to the development of our economies,
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这对我们经济的发展至关重要,
02:44
what I call "everyday living" --
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就是我所说的日常生活。
02:48
to function in the world today,
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二,要在今天的世界运作,
02:50
you've got to be pretty quantitative,
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你就必须比几年前掌握
02:52
much more so than a few years ago:
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更多数学知识。
02:54
figure out your mortgages,
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你需要去算你的房贷,
02:56
being skeptical of government statistics, those kinds of things --
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对政府的数据等种种数字保持怀疑。
03:00
and thirdly, what I would call something like
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第三,我把它称作
03:03
logical mind training, logical thinking.
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逻辑思维训练,逻辑思维。
03:06
Over the years
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这几年
03:08
we've put so much in society
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我们努力使社会运作和思维
03:10
into being able to process and think logically. It's part of human society.
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都变得符合逻辑,并将这做为人类社会的一部分。
03:13
It's very important to learn that
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必须要指出
03:15
math is a great way to do that.
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数学正是实现这种构想的重要工具。
03:17
So let's ask another question.
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现在让我们考虑另一个问题。
03:19
What is math?
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数学是什么?
03:21
What do we mean when we say we're doing math,
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当我们说我们在做数学,
03:23
or educating people to do math?
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或者说在教数学的时候我们指的是什么呢?
03:25
Well, I think it's about four steps, roughly speaking,
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总体来说,我觉得有四个步骤,
03:28
starting with posing the right question.
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正确地提问是第一步。
03:30
What is it that we want to ask? What is it we're trying to find out here?
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我们想问的到底是什么问题?我们想了解的是什么?
03:33
And this is the thing most screwed up in the outside world,
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这步是在外部世界相比做数学的其他任何步骤中
03:35
beyond virtually any other part of doing math.
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最容易搞砸的一步。
03:38
People ask the wrong question,
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如果人们问错了问题,
03:40
and surprisingly enough, they get the wrong answer,
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毫无疑问,他们会因此而得出错误的结果,
03:42
for that reason, if not for others.
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如果运算没有错误的话。
03:44
So the next thing is take that problem
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接下来就是根据正确的问题。
03:46
and turn it from a real world problem
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将它从现实世界的问题
03:48
into a math problem.
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转化成一个数学问题。
03:50
That's stage two.
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这就是第二步。
03:52
Once you've done that, then there's the computation step.
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这样做之后我们就进入了运算的第三步骤。
03:55
Turn it from that into some answer
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求出某个
03:57
in a mathematical form.
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数学形式的答案。
04:00
And of course, math is very powerful at doing that.
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当然,数学在这一方面非常有用。
04:02
And then finally, turn it back to the real world.
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最后,将解答转换成现实世界的问题。
04:04
Did it answer the question?
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这个答案有没有解决现实社会的问题呢?
04:06
And also verify it -- crucial step.
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当然事实证明这也是关键一步。
04:10
Now here's the crazy thing right now.
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现在,疯狂的事情就是
04:12
In math education,
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在数学教育中,
04:14
we're spending about perhaps 80 percent of the time
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我们或许花了八成的时间
04:17
teaching people to do step three by hand.
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教人们用笔头计算解决第三个步骤。
04:20
Yet, that's the one step computers can do
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然而,这恰恰是计算机
04:22
better than any human after years of practice.
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比任何经过多年运算训练的人都做得更好地一步。
04:25
Instead, we ought to be using computers
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换言之,我们本应该用计算机
04:28
to do step three
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去完成上述步骤三,
04:30
and using the students to spend much more effort
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而让学生花更多的精力
04:33
on learning how to do steps one, two and four --
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去学好上述步骤一、二和四;
04:35
conceptualizing problems, applying them,
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将问题概念化,并且运用它们,
04:38
getting the teacher to run them through how to do that.
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让老师示范怎么去做。
04:41
See, crucial point here:
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看到了吗?这里的重点就是:
04:43
math is not equal to calculating.
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数学并不等同于计算。
04:45
Math is a much broader subject than calculating.
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数学是比计算更广泛的一门学科。
04:48
Now it's understandable that this has all got intertwined
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现在我们不难理解出现这种将计算和数学混淆在一起的原因了。
04:51
over hundreds of years.
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几百年来,
04:53
There was only one way to do calculating and that was by hand.
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我们进行计算的唯一方法就是笔算。
04:56
But in the last few decades
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仅仅是近几十年
04:58
that has totally changed.
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这种情况才出现根本性的变化。
05:00
We've had the biggest transformation of any ancient subject
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计算机的运用使任何古老学科
05:03
that I could ever imagine with computers.
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产生最大的变革成为了可能。
05:07
Calculating was typically the limiting step,
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计算通常是有限步骤的,
05:09
and now often it isn't.
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无限步骤的并不常见。
05:11
So I think in terms of the fact that math
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因此,我觉得,虽然就事实而言,数学
05:13
has been liberated from calculating.
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已经从计算中解放出来。
05:16
But that math liberation didn't get into education yet.
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但是数学的解放却仍没有被引入到教学之中。
05:19
See, I think of calculating, in a sense,
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我认为,在某种程度上,计算
05:21
as the machinery of math.
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只是机械化的数学。
05:23
It's the chore.
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计算是一种杂活,
05:25
It's the thing you'd like to avoid if you can, like to get a machine to do.
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就是那种你想尽量避免,可以的话让机器来完成的工作。
05:29
It's a means to an end, not an end in itself,
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仅仅作为得出目的的手段,而不是目的本身。
05:34
and automation allows us
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而自动化允许我们
05:36
to have that machinery.
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享用这种计算机器。
05:38
Computers allow us to do that --
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计算机允许我们这样做。
05:40
and this is not a small problem by any means.
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而这无论从何种角度看都不是一个小问题。
05:43
I estimated that, just today, across the world,
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我估计,仅仅是今天世界范围之内,
05:46
we spent about 106 average world lifetimes
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我们就平均用了大约106年生命时间
05:49
teaching people how to calculate by hand.
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去教人们做人工运算。
05:52
That's an amazing amount of human endeavor.
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这是巨大的人类劳动。
05:55
So we better be damn sure --
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因此我们最好可以非常确定——
05:57
and by the way, they didn't even have fun doing it, most of them --
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顺便提一下,绝大多数人做人工运算时没有感到任何乐趣。
06:00
so we better be damn sure
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因此,我们最好可以非常确定
06:02
that we know why we're doing that
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我们知道这样做的原因,
06:04
and it has a real purpose.
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这样做有一个真正的目的。
06:06
I think we should be assuming computers
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我认为我们应该预计计算机
06:08
for doing the calculating
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可以完成运算,
06:10
and only doing hand calculations where it really makes sense to teach people that.
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仅仅在必要时才教人们人工笔头运算。
06:13
And I think there are some cases.
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当然我觉得某些情况下
06:15
For example: mental arithmetic.
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比如说,心算。
06:17
I still do a lot of that, mainly for estimating.
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我现在仍然经常运用心算,通常是用来预估。
06:20
People say, "Is such and such true?"
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当别人说,答案是这样的,
06:22
And I'll say, "Hmm, not sure." I'll think about it roughly.
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我会说,嗯,不确定。 我认为答案大概是这样吧。
06:24
It's still quicker to do that and more practical.
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心算在这方面仍然是比较快速而且有用的。
06:26
So I think practicality is one case
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因此我认为实用性是
06:28
where it's worth teaching people by hand.
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其中一种值得教授人工运算的情况。
06:30
And then there are certain conceptual things
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另外还有一些
06:32
that can also benefit from hand calculating,
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同样得益于人工运算的概念,
06:34
but I think they're relatively small in number.
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但我认为这种情况相对来说比较少。
06:36
One thing I often ask about
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比如说,我经常会问起
06:38
is ancient Greek and how this relates.
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以古希腊教学数学来做一个类比。
06:41
See, the thing we're doing right now
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我们现在的教学
06:43
is we're forcing people to learn mathematics.
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总是强迫学生去学习数学。
06:45
It's a major subject.
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它是一个主科。
06:47
I'm not for one minute suggesting that, if people are interested in hand calculating
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注意的是,我从来没有刻意暗示说如果有人对人工运算感兴趣
06:50
or in following their own interests
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或者按照他们自己的意愿
06:52
in any subject however bizarre --
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学习任何哪怕是毫无意义的学科;
06:54
they should do that.
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相反,他们应当这样做。
06:56
That's absolutely the right thing,
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因为让人们发展自己的兴趣爱好,
06:58
for people to follow their self-interest.
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完全就是一件正确的事。
07:00
I was somewhat interested in ancient Greek,
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我个人对古希腊怀有某种特殊的情结,
07:02
but I don't think that we should force the entire population
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但我不认为我们应该逼迫全体人民
07:05
to learn a subject like ancient Greek.
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都像古希腊学习数学的方法。
07:07
I don't think it's warranted.
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我不认为这样是值得的。
07:09
So I have this distinction between what we're making people do
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因此我知道我们应该区分迫使人们学习
07:12
and the subject that's sort of mainstream
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或是作为某种主流的学科
07:14
and the subject that, in a sense, people might follow with their own interest
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与人们在某种程度上自觉按照自己意愿学习的
07:17
and perhaps even be spiked into doing that.
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或甚至是钟情于此的学科。
07:19
So what are the issues people bring up with this?
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那人们为什么提出这一点呢?
07:22
Well one of them is, they say, you need to get the basics first.
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其中一点,他们会说,你必须先打好基础。
07:25
You shouldn't use the machine
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你在完全掌握学科的基础之前
07:27
until you get the basics of the subject.
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不许用机器。
07:29
So my usual question is, what do you mean by "basics?"
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那我通常的疑问就是,你所说的“基础”指的什么?
07:32
Basics of what?
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什么的基础?
07:34
Are the basics of driving a car
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这样说来,请问驾车的基础
07:36
learning how to service it, or design it for that matter?
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是否是怎样修车或者设计车模?
07:39
Are the basics of writing learning how to sharpen a quill?
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而写作的基础是否又是要学习如何削鹅毛笔?
07:43
I don't think so.
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我认为不是这样的。
07:45
I think you need to separate the basics of what you're trying to do
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我认为你需要将你所要做的事情的基础
07:48
from how it gets done
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理解成两部分如何得出结果
07:50
and the machinery of how it gets done
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与用机器如何得出结果区分开来。
07:54
and automation allows you to make that separation.
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自动化允许你作出如此的理解。
07:57
A hundred years ago, it's certainly true that to drive a car
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一百多年前,如果要学车你无疑是需要
08:00
you kind of needed to know a lot about the mechanics of the car
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知道某些汽车机械原理的
08:02
and how the ignition timing worked and all sorts of things.
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以及定时打火器等各零部件的工作原理。
08:06
But automation in cars
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但是汽车的自动化
08:08
allowed that to separate,
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实现两类学问的划分,
08:10
so driving is now a quite separate subject, so to speak,
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也就是说驾车现在与汽车工程学
08:13
from engineering of the car
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是相对独立的两个学科,
08:16
or learning how to service it.
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修车又是另外一回事。
08:20
So automation allows this separation
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正是自动化实现了这种区分,
08:22
and also allows -- in the case of driving,
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不仅在驾车的例子中是这样的自动化,
08:24
and I believe also in the future case of maths --
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因为我相信自动计算化也会在未来的数学中起同样的作用,
08:26
a democratized way of doing that.
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我们可以自主地选择怎样去做。
08:28
It can be spread across a much larger number of people
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数学可以向更多实际运用的人
08:30
who can really work with that.
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去传播。
08:33
So there's another thing that comes up with basics.
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关于基本技能又有另外一个观点。
08:35
People confuse, in my view,
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我认为,人们混淆
08:37
the order of the invention of the tools
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发明工具的次序
08:40
with the order in which they should use them for teaching.
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与在教学中应当运用这些工具的次序。
08:43
So just because paper was invented before computers,
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不能因为纸比计算机先被发明,而人们就应该先在教学中运用纸张,
08:46
it doesn't necessarily mean you get more to the basics of the subject
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用纸张教数学不一定代表
08:49
by using paper instead of a computer
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你会比用计算机
08:51
to teach mathematics.
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更了解数学的基础。
08:55
My daughter gave me a rather nice anecdote on this.
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我女儿的一则轶事为这一点做了生动地说明。
08:58
She enjoys making what she calls "paper laptops."
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她很喜欢制作她所说的“纸制笔记本电脑”。
09:01
(Laughter)
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(笑声)
09:03
So I asked her one day, "You know, when I was your age,
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有一天,我问她:“我在你这个年纪的时候,
09:05
I didn't make these.
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我都不会做这些。
09:07
Why do you think that was?"
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你觉得是为什么呢?”
09:09
And after a second or two, carefully reflecting,
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她很仔细地想了一两秒,
09:11
she said, "No paper?"
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然后她说,“没有纸吗?”
09:13
(Laughter)
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(笑声)
09:19
If you were born after computers and paper,
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如果你在计算机和纸张的发明之后出生,
09:21
it doesn't really matter which order you're taught with them in,
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你学习数学究竟是先用纸张学习还是先用计算机学习其实并不重要,
09:24
you just want to have the best tool.
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你仅仅需要用最佳的工具来学习数学。
09:26
So another one that comes up is "Computers dumb math down."
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那另一个观点就是“计算机使数学变蠢。”
09:29
That somehow, if you use a computer,
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在一定程度上的确如此,如果你用计算机,
09:31
it's all mindless button-pushing,
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这仅仅是无需思考的按键操作,
09:33
but if you do it by hand,
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但如果你进行人工笔头运算,
09:35
it's all intellectual.
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这完全又是智力训练。
09:37
This one kind of annoys me, I must say.
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我要说,这一点很困扰我。
09:40
Do we really believe
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我们难道真的以为
09:42
that the math that most people are doing in school
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现在通常人们在学校里
09:44
practically today
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学习的数学
09:46
is more than applying procedures
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真的比按照解题步骤做题学得多吗?
09:48
to problems they don't really understand, for reasons they don't get?
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他们大都还在用不理解的原理去解答他们不明白的问题。
09:51
I don't think so.
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至少我认为如此。
09:53
And what's worse, what they're learning there isn't even practically useful anymore.
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更严重的是,他们在学校所学的知识根本已经不再实用。
09:56
Might have been 50 years ago, but it isn't anymore.
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或许50年前还在用,但现在已经不再使用了。
09:59
When they're out of education, they do it on a computer.
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除了教育之外,他们都用计算机来完成。
10:02
Just to be clear, I think computers can really help with this problem,
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要清醒地知道,计算机已经完全解决了这一问题,
10:05
actually make it more conceptual.
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事实上使它更容易理解。
10:07
Now, of course, like any great tool,
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而如今,像任何伟大的工具一样,
10:09
they can be used completely mindlessly,
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它们可以彻底无须动脑筋地操作,
10:11
like turning everything into a multimedia show,
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就像将任何东西都变成一场多媒体的盛宴一样,
10:14
like the example I was shown of solving an equation by hand,
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就像这个解方程的例子,
10:17
where the computer was the teacher --
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计算机就好比是老师--
10:19
show the student how to manipulate and solve it by hand.
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它给学生演示如何现在用笔头进行运算和解题。
10:22
This is just nuts.
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这其实很荒谬。
10:24
Why are we using computers to show a student how to solve a problem by hand
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为什么我们要用计算机来演示如何用笔算解题呢?
10:27
that the computer should be doing anyway?
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明明计算机可以自行计算来解题。
10:29
All backwards.
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完全是倒退了。
10:31
Let me show you
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下面让我为你演示
10:33
that you can also make problems harder to calculate.
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计算机如何运算出更复杂的题目。
10:36
See, normally in school,
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通常在学校里,
10:38
you do things like solve quadratic equations.
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你会学习像解二次方程式这类题目。
10:41
But you see, when you're using a computer,
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但如果你用计算机来做,
10:44
you can just substitute.
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你仅需要做代换。
10:48
You can make it a quartic equation. Make it kind of harder, calculating-wise.
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就可以将它变成四次方程,运算上更复杂。
10:50
Same principles applied --
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同样的原理仍然适用,
10:52
calculations, harder.
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只是运算上更复杂。
10:54
And problems in the real world
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而现实世界里的问题
10:56
look nutty and horrible like this.
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的确就像这样复杂和难懂的,
10:58
They've got hair all over them.
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甚至更加棘手的问题。
11:00
They're not just simple, dumbed-down things that we see in school math.
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它们都不是我们学校数学中学的那些简单愚蠢的东西。
11:04
And think of the outside world.
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让我们想想外面的世界。
11:06
Do we really believe that engineering and biology
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难道我们真的以为工程学和生物学
11:08
and all of these other things
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等其他
11:10
that have so benefited from computers and maths
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得益于计算机和数学的学问
11:12
have somehow conceptually gotten reduced by using computers?
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会由于应用计算机而在某种程度上被明显削弱吗?
11:15
I don't think so -- quite the opposite.
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我认为,恰恰相反。
11:18
So the problem we've really got in math education
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我们在数学教育中的真正问题
11:21
is not that computers might dumb it down,
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并不是计算机使数学变得愚蠢,
11:24
but that we have dumbed-down problems right now.
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而是我们现在的教学使问题变得愚蠢。
11:27
Well, another issue people bring up
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好,那人们提到的另一点
11:29
is somehow that hand calculating procedures
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就是笔头运算的步骤在一定程度上
11:31
teach understanding.
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可以教导学生理解数学。
11:33
So if you go through lots of examples,
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因此如果你做过很多例题,
11:35
you can get the answer,
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你就可以算出答案,
11:37
you can understand how the basics of the system work better.
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你也可以更好地理解数学系统的基础。
11:40
I think there is one thing that I think very valid here,
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我认为,这个观点里有一点是我非常认同的,
11:43
which is that I think understanding procedures and processes is important.
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那就是我认为步骤和运算过程很重要。
11:47
But there's a fantastic way to do that in the modern world.
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但是在现代社会我们有一个绝佳的途径去这样做,
11:50
It's called programming.
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那就是编程。
11:53
Programming is how most procedures and processes
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现在多数程序和编码过程
11:55
get written down these days,
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大都以编程的方式写下来,
11:57
and it's also a great way
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而这也是一种很好的方式
11:59
to engage students much more
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去鼓励学生更多的参与,
12:01
and to check they really understand.
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检验他们是否真正理解数学问题。
12:03
If you really want to check you understand math
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如果你真的想检验你是否理解数学
12:05
then write a program to do it.
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就尝试编写一条程序。
12:08
So programming is the way I think we should be doing that.
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因此我认为编程就是我们应该做的方向。
12:11
So to be clear, what I really am suggesting here
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一言以蔽之,在此我想说的是
12:13
is we have a unique opportunity
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编程为我们提供了一个独特的机会:
12:15
to make maths both more practical
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一方面使数学更实用,
12:17
and more conceptual, simultaneously.
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同时另一方面又更加理论化。
12:20
I can't think of any other subject where that's recently been possible.
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我想,这种在数学教学的新局面在其他任何学科都还没有出现。
12:23
It's usually some kind of choice
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这通常像是一种
12:25
between the vocational and the intellectual.
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在职业规划或者是智力培养之间的两难选择。
12:27
But I think we can do both at the same time here.
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但我想运用计算机我们可以两方面同时实现。
12:32
And we open up so many more possibilities.
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还为我们又打开了许多可能性。
12:35
You can do so many more problems.
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我们可以解决更多的实际问题。
12:37
What I really think we gain from this
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我真切地感觉到这种教育的改革
12:39
is students getting intuition and experience
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可以让学生获得很多的知识和经验
12:42
in far greater quantities than they've ever got before.
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比之前多得多的直观的认识和经验的累积。
12:45
And experience of harder problems --
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和接触更加复杂的题目——
12:47
being able to play with the math, interact with it,
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畅游于数学的乐园,与数学沟通,
12:49
feel it.
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感受数学之美。
12:51
We want people who can feel the math instinctively.
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我们希望学生可以本能地感受数学。
12:54
That's what computers allow us to do.
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而这恰恰是计算机使这成为可能。
12:57
Another thing it allows us to do is reorder the curriculum.
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另一点是计算机使我们得以对教学课程重新排序。
13:00
Traditionally it's been by how difficult it is to calculate,
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以前是按照计算的难度编排课程教学的顺序,
13:02
but now we can reorder it
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但现在我们可以重新排序,
13:04
by how difficult it is to understand the concepts,
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按照概念理念的难度,
13:06
however hard the calculating.
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而不管计算的难度。
13:08
So calculus has traditionally been taught very late.
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因此微积分传统上是很晚才能教授的项目。
13:11
Why is this?
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原因是什么呢?
13:13
Well, it's damn hard doing the calculations, that's the problem.
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问题就在于微积分的计算相当困难。
13:17
But actually many of the concepts
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但事实上许多概念
13:19
are amenable to a much younger age group.
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是可以向更低年级的学生传授的。
13:22
This was an example I built for my daughter.
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这就是一个我为女儿所建的模型例子。
13:25
And very, very simple.
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而且非常简单易懂。
13:28
We were talking about what happens
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这个模型是用于理解
13:30
when you increase the number of sides of a polygon
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当多边形的边数增加时,图形的变化随之改变。
13:32
to a very large number.
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当边数增加到非常大的时候,
13:36
And of course, it turns into a circle.
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当然,多边形变成一个圆。
13:38
And by the way, she was also very insistent
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顺便一提,她对可以转换颜色这一点
13:40
on being able to change the color,
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特别乐此不疲,
13:42
an important feature for this demonstration.
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这也是这个展示的一个重要的特征。
13:46
You can see that this is a very early step
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你可以看到这是一个
13:49
into limits and differential calculus
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对极限和微积分非常初步的启蒙,
13:51
and what happens when you take things to an extreme --
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也可以让你直观地看到趋于极限时所发生的变化,
13:54
and very small sides and a very large number of sides.
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无限小边数的情况和无限多边数的情况。
13:56
Very simple example.
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非常浅显的例子。
13:58
That's a view of the world
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这是对世界的一种观察方式,
14:00
that we don't usually give people for many, many years after this.
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我们通常是很久很久之后才会教给学生这些。
14:03
And yet, that's a really important practical view of the world.
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但它却是对世界的一种非常重要且实用的观察。
14:06
So one of the roadblocks we have
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那现在我们要改革
14:09
in moving this agenda forward
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推进这个进程的路障
14:12
is exams.
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就在于考试。
14:14
In the end, if we test everyone by hand in exams,
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最后,假如我们考试的方式是人工笔算,
14:17
it's kind of hard to get the curricula changed
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就难以将目前的课程设计
14:20
to a point where they can use computers
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改革成
14:22
during the semesters.
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在教学中可以使用计算机。
14:25
And one of the reasons it's so important --
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而既然作为一个如此重要的原因
14:27
so it's very important to get computers in exams.
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在考试中使用计算机也是非常重要的。
14:30
And then we can ask questions, real questions,
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如此以来,我们就可以设置实际的问题,
14:33
questions like, what's the best life insurance policy to get? --
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比如说,“哪一种人寿保险的险种更适合我们?”
14:36
real questions that people have in their everyday lives.
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人们实际生活中遇到诸如此类的问题。
14:40
And you see, this isn't some dumbed-down model here.
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你可以看到,这就不是那些愚蠢的问题模型。
14:42
This is an actual model where we can be asked to optimize what happens.
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这是一个我们优化选择时可以用到的实际模型。
14:45
How many years of protection do I need?
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我需要多少年的险期?
14:47
What does that do to the payments
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这对保险费有什么影响?
14:49
and to the interest rates and so forth?
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对利率等其他的影响呢?
14:52
Now I'm not for one minute suggesting it's the only kind of question
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这里我没有刻意在暗示
14:55
that should be asked in exams,
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这是考试中应该考的唯一类型的问题,
14:57
but I think it's a very important type
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但是我认为至少这是非常重要的一类型,
14:59
that right now just gets completely ignored
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也是目前的教育完全忽视的,
15:02
and is critical for people's real understanding.
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这对人们的实际理解也是至关重要的。
15:05
So I believe [there is] critical reform
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因此我相信
15:08
we have to do in computer-based math.
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我们需要一场以计算机作为数学教学工具的改革。
15:10
We have got to make sure
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我们务必确保
15:12
that we can move our economies forward,
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通过让人们可以切实感受数学,
15:15
and also our societies,
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我们才可以推进经济发展和
15:17
based on the idea that people can really feel mathematics.
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社会进步。
15:22
This isn't some optional extra.
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这绝不是可有可无的一环。
15:25
And the country that does this first
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而我认为首先这样做的国家
15:27
will, in my view, leapfrog others
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一定会鹤立鸡群,
15:30
in achieving a new economy even,
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甚至取得更大的经济成就,
15:33
an improved economy,
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更完善的经济体系,
15:35
an improved outlook.
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和更卓越的国家面貌。
15:37
In fact, I even talk about us moving
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事实上,我甚至会说我们正在
15:39
from what we often call now the "knowledge economy"
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从我们现在经常提到的“知识经济”时代迈向
15:42
to what we might call a "computational knowledge economy,"
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可能被称作“计算机知识经济”的时代,
15:45
where high-level math is integral to what everyone does
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高端的数学知识对每个人
15:48
in the way that knowledge currently is.
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应用现代知识来说都不可或缺。
15:50
We can engage so many more students with this,
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我们可以让更多学生加入到这个改革,
15:53
and they can have a better time doing it.
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让他们在最佳的时机得到这样的教育。
15:56
And let's understand:
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我们要明白
15:58
this is not an incremental sort of change.
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这不是一场渐进式的改革。
16:02
We're trying to cross the chasm here
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我们要试图跨越
16:04
between school math and the real-world math.
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学校数学和实际数学之间的鸿沟。
16:06
And you know if you walk across a chasm,
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你可以看到如果我们是走过这个鸿沟的话,
16:08
you end up making it worse than if you didn't start at all --
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我们一定会跌得粉身碎骨,
16:11
bigger disaster.
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甚至比没有开始改革更糟糕。
16:13
No, what I'm suggesting
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这不是我想要的局面,
16:15
is that we should leap off,
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我想说,我们应该跳跃,
16:17
we should increase our velocity
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我们必须加快我们的起跳速度,
16:19
so it's high,
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这样我们就可以跳得高,
16:21
and we should leap off one side and go the other --
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我们应该从鸿沟的一头跳到另外一头,
16:24
of course, having calculated our differential equation very carefully.
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当然要准确地计算这里微分方程。
16:27
(Laughter)
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(笑声)
16:29
So I want to see
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因此我想看到的是
16:31
a completely renewed, changed math curriculum
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一套全新的、经过改良的数学教学课程
16:33
built from the ground up,
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在应用计算机的基础上
16:35
based on computers being there,
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架构而起,
16:37
computers that are now ubiquitous almost.
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目前计算机已经是在各地非常普遍的
16:39
Calculating machines are everywhere
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运算工具,
16:41
and will be completely everywhere in a small number of years.
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相信在不久的将来它会彻底覆盖每一个地方。
16:44
Now I'm not even sure if we should brand the subject as math,
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现在我还不确定我们是否应该仍然沿用“数学”作为这个学科的名字,
16:48
but what I am sure is
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但我确信
16:50
it's the mainstream subject of the future.
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这门课将是未来学科的主流。
16:53
Let's go for it,
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让我们共同努力吧。
16:56
and while we're about it,
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并且在学习它的过程中
16:58
let's have a bit of fun,
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让大家
17:00
for us, for the students and for TED here.
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所有人,广大的学生以及TED这里的观众享受一些乐趣!
17:03
Thanks.
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谢谢
17:05
(Applause)
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(掌声)
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