跟读练习: The best way to become good at something might surprise you - David Epstein - 通过YouTube学习英语口语
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Many of you here have probably heard of the 10,000 hours rule.
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Many of you here have probably heard of the 10,000 hours rule.
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It’s the idea that to become great in anything takes 10,000 hours of focused practice.
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So you’d better get started as early as possible.
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The poster child for this story is Tiger Woods.
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His father famously gave him a putter when he was seven months old.
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Fast forward to the age of 21— he’s the greatest golfer in the world.
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Quintessential 10,000 hours story.
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Another is that of the three Polgar sisters, whose father decided to teach them chess in a very technical manner from a very early age.
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Two of his daughters went on to become grandmaster chess players I got curious: if this 10,000 hours rule is correct, then we should see that elite athletes get a head start in so-called deliberate practice.
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And in fact, when scientists study elite athletes, they see that they spend more time in deliberate practice.
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Not a big surprise.
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When they actually track athletes over the course of their development, the pattern looks like this: the future elites tend to have what scientists call a sampling period, where they try a variety of physical activities.
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They gain broad general skills and delay specializing until later than peers who plateau at lower levels.
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That doesn’t really comport with the 10,000 hours rule, does it?
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So I started to wonder about other domains that we associate with obligatory early specialization, like music.
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Turns out the pattern is often similar.
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The exceptional musicians didn’t start spending more time in deliberate practice than the average musicians until their third instrument.
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They too tended to have a sampling period.
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Even musicians we think of as famously precocious, like Yo-Yo Ma.
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So this got me interested in exploring the developmental backgrounds of people whose work I had long admired.
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Duke Ellington shunned music lessons as a kid to focus on baseball and painting and drawing.
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Mariam Mirzakhani wasn’t interested in math as a girl, dreamed of becoming a novelist, and went on to become the first and so far only woman to win the Fields Medal, the most prestigious prize in the world in math.
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Vincent van Gogh had five different careers before flaming out spectacularly, and, in his late 20s, picked up a book called “The Guide to the ABCs of Drawing.” Claude Shannon was an electrical engineer at the University of Michigan who took a philosophy course just to fulfill a requirement.
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And in it he learned about a near century-old system of logic by which true and false statements could be coded as ones and zeros and solved like math problems.
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This led to the development of binary code, which underlies all of our digital computers today.
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Frances Hesselbein took her first professional job at the age of 54, and went on to become the CEO of the Girl Scouts.
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Here’s an athlete I’ve followed.
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He tried some tennis, some skiing, wrestling.
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His mother was actually a tennis coach, but she declined to coach him because he wouldn’t return balls normally.
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And he kept trying more sports: handball, volleyball, soccer, badminton, skateboarding.
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So who is this dabbler?
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This is Roger Federer.
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Every bit as famous as an adult as Tiger Woods.
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And yet even tennis enthusiasts don't usually know anything about his developmental story.
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Why is that?
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I think it’s partly because the Tiger story is very dramatic, but also because it seems like this tidy narrative that we can extrapolate to anything that we want to be good at in our own lives.
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But it turns out that in many ways, golf is a uniquely horrible model of almost everything that humans want to learn.
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Golf is the epitome of what the psychologist Robin Hogarth called a kind learning environment.
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Next steps and goals are clear; rules that are clear and never change.
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When you do something, you get feedback that is quick and accurate.
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Chess, also a kind learning environment.
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On the other end of the spectrum are wicked learning environments where next steps and goals may not be clear— rules may change.
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You may or may not get feedback when you do something, it may be delayed, it may be inaccurate.
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Which one of these sounds like the world we're increasingly living in?
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So if hyper-specialization isn’t always the trick in a wicked world, what is?
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That can be difficult to talk about, because sometimes it looks like meandering or zigzagging or keeping a broader view.
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It can look like getting behind.
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But if we look at research on technological innovation, it shows that increasingly the most impactful patents are authored by teams that include individuals who have worked across a large number of different technology classes and often merge things from different domains.
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Someone whose work I've admired, who was sort of on the forefront of this, is a Japanese man named Junpei Yokoi.
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Yokoi didn't score well in his electronics exams at school, so he had to settle for a low-tier job as a machine maintenance worker at a playing card company in Kyoto.
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He combined some well-known technology from the calculator industry, with some well-known technology from the credit card industry, and made handheld games.
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And it turned this playing card company, which was founded in a wooden storefront in the 19th century, into a toy and game operation.
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You may have heard of it, it’s called Nintendo.
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His magnum opus was the Game Boy.
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We probably don't make as many of those people as we could, because we don't tend to incentivize anything that doesn't look like a head start or specialization.
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And naturally, I think there are as many ways to succeed as there are people, but I think we tend only to incentivize and encourage the Tiger path, when increasingly, in a wicked world, we need people who travel the Roger path as well.
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Or as the eminent physicist and mathematician and writer Freeman Dyson put it: “For a healthy ecosystem, we need both birds and frogs.
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Frogs are down in the mud seeing all the granular details.
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The birds are soaring up above, not seeing those details, but integrating the knowledge of the frogs.” And we need both.
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The problem, Dyson said, is that we’re telling everyone to become frogs.
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And I think in a wicked world, that's increasingly shortsighted.
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在这段视频中，讲者大卫·埃普斯坦探讨了成功与专注实践之间的关系，尤其是所谓的“1万小时法则”。许多人可能听说过这一概念，认为要在某个领域出类拔萃，需要付出1万小时的专注练习。然而，根据埃普斯坦的研究，许多精英运动员和音乐家的成长经历往往与这一规则不尽相同。他们在很早的阶段进行多种领域的尝试，积累广泛的技能，而非简单地追求早期的专业化。这一观点对学习英语的同学们尤为重要，因为它提醒我们要在语言学习中保持多样性与实践。
日常交流的五个常用短语
- 专注于练习 - Focus on practice
- 保持多样性 - Keep diversity
- 技能积累 - Skill accumulation
- 回馈与学习 - Feedback and learning
- 探索不同领域 - Explore different fields
逐步影子跟读指南
为了有效提高英语口语能力，建议利用视频的内容进行影子跟读练习。这不仅能帮助你熟悉发音，还能增强对短语的理解和运用：
- 观看视频：首次观看时，专注于内容理解，注意讲者的语调和重音。
- 逐句跟读：选择一小段进行影子跟读，初次尝试时可以暂停视频，模仿讲者的发音和语速。使用 英语影子跟读 技巧，反复练习帮助记忆。
- 记录语音：尝试录下自己的声音并与原视频进行比较，找到需要改进的地方。
- 重复练习：反复进行跟读和录音，不断提升流利度，并增加对短语的熟悉程度。
- 互动学习：与学习伙伴一起练习，或是加入 雅思口语练习 小组，通过交流进一步提高口语能力。
在学习过程中，鼓励自己将 看YouTube学英语 的内容与实际对话结合，从而在真实环境中应用这些技能。
什么是跟读法？
跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。