쉐도잉 연습: AI Destroyed My Profession - 영상으로 영어 말하기 배우기

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It's December 2013 and the President of the United States is looking straight into a camera talking to kids all over America.

He tells them to stop playing video games and instead to start making them.

And then he says a sentence

that ends up on classroom posters all over the country

and you know what a whole ass generation listened coding boot

camps popped up everywhere computer science became one of the most popular majors

and the phrase learn to code turned into the safest career advice on the planet it got

so popular that in 2019

when a bunch of journalists lost their jobs people online mocked them with just three words learn to code

now fast forward to 2026 in the first half of this

year alone tech companies announced almost 140 000 job cuts

and most of them say the reason is ai so is that it is the best job of the 21st century dead

Let me keep it real with you folk, I'm asking that question sincerely,

I'm a software engineer myself with a master's degree and everything so for me this isn't just another story from the news,

it's my industry and honestly that makes this video a little personal.

Here's the thing, companies thought that AI would be a cheap replacement for programmers

And now that they've actually tried it, three bills are starting to show up.

One for the AI itself, one for the code it writes, and a third one that almost nobody is talking about yet.

So let's open them up, one by one.

Okay, let's start with the layoffs, because they're very much real.

In January, Amazon cut 16 ,000 corporate jobs.

Oracle let go of around 21 ,000 people over the year,

Meta cut 8 ,000, and a payments company called Block laid off half of its entire workforce in one go.

And the people building AI didn't really help calm anyone down.

Back in 2025, the head of Anthropic, one of the biggest AI companies in the world said AI

could wipe out half of all entry -level office jobs within a few years.

So it's easy to look at all of this and think that it's over, that we lost.

But not everyone believes the companies are telling the whole truth.

Even Sam Altman, the guy who runs OpenAI, said that some companies are AI washing their layoffs.

In other words, They blame AI for cuts they were going to make anyway.

And you have to admit, it's a pretty convenient excuse, because saying we fired 4 ,000 people just sounds terrible.

But saying that AI changed our industry sounds like the future.

AI is the perfect excuse, because it makes the decisions look like it came from the technology and not from the company.

There's also one more thing a lot of headlines leave out.

Many of these companies are spending insane amounts of money on data centers and AI chips right now.

So sometimes when a company says AI took your job,

what it really means is we needed your salary to pay for AI.

But is programming actually dying?

Before we open any of those bills, let's check that first, because the answer is not exactly what the headlines say.

In 2025, one headline went all over the internet.

The number of programmers in the US had dropped to its lowest level since 1980.

That's a time when most people didn't even know what the internet was.

The numbers are correct, but there's a catch.

You see, in the official US statistics, a computer programmer is a pretty small category.

It's around 110 ,000 people whose job is mostly writing code based on someone else's plans.

Most of the people you'd call programmers are actually counted as software developers and that group has around 1 .9 million people.

The official forecast says it will grow by 10 % over the next 10 years.

So the headline wasn't exactly lying, it just compared one small room to the whole building.

It's the same story with the chart saying computer science graduates have one of the highest unemployment rates out of any major.

The sample behind it was very small, and when economists took a closer look,

it turned out that around 90 % of young people with that degree were actually working.

So no, programming is not dead.

But something is definitely wrong.

And you can see it the moment you follow the money.

Time to open the first envelope.

The bill for the AI itself.

First, a quick explanation.

AI tools charge by something called tokens.

A token is basically a small piece of a word

and you pay for every token the AI reads and every token it writes.

So, the more work you give it, the more it costs.

Now, here's the funny part.

Over the last few years the price per token has dropped like a rock

and the bills they actually went up how is

that possible AI coding tools don't just finish your line of code anymore

now they work on their own code for hours reading through huge amounts of code

and trying things again and again so even though every single token is cheap, they burn through an unbelievable amount of them.

It's like gas getting 10 times cheaper and then everyone going out and buying a private yacht.

And in 2026 companies started getting the bills.

In May, Uber's CEO admitted

that the entire company had burned through its entire yearly budget for AI coding tools in just four months.

He even said that the link between all that spending and any real benefit for a customer is not there yet.

Soon after, Uber put limits on how much each employee could spend.

Then in August it was Microsoft's turn.

It came out that one engineer had spent 28 ,000 dollars on AI in just 28 days.

That's a thousand dollars a day.

At that pace, one engineer's AI use would cost more throughout the year than paying three American software developers.

So Microsoft sent out an internal email with a sentence

that's honestly peak email said token maxing is not what we are optimizing for token maxing yep

that's an actual word in a real email in a trillion dollar company

and when your company has to put a word like

that in an official email just to tell you to stop spending money you know something went wrong

and it's not just uber

and microsoft gartner one of the biggest research firms in tech predicts

that by 2028 ai coding costs will be higher than the average developer's salary think about

that for a second the whole point was to replace expensive programmers with cheap AI,

and now the AI is on track to cost more than the programmer.

But hey, at least all that money bought a lot of code, right?

Well, that's exactly where the second bill comes in.

Envelope number two, the code.

To understand this one, you need to know a term programmers use all the time and that's technical debt.

It works exactly like a credit card.

When you write code very quickly it gets a bit messy.

You get something that works today and it feels amazing just like swiping a credit card.

But every change you make after that gets slower and more expensive because you keep paying interest on that mess.

And eventually, someone has to pay off the whole thing.

So what happens to that debt, when AI writes a big part of the code?

A company called GitClear has been tracking exactly that.

They looked at more than 600 million code changes from 2023 to 2026, and they found two things moving in the opposite directions.

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Copying and pasting code went way up.

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Meanwhile, the work of cleaning up and reorganizing old code,

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which programmers call refactoring has collapsed in 2022

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it made about 21 % of all changed code by 2026

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it was under 4 % in other words AI is really good at adding new code

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and really bad at tidying up the code that's already there

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so the mess keeps growing and then there's security A company called Veracode tested more than 150 AI models,

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and when nobody specifically told them to be careful,

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about 45 % of the code they wrote had a known security hole hiding in there.

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And you know what's the worst part?

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That number has barely moved in two years.

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The models got much better at writing code that works, but they didn't improve much at writing code that's safe.

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Another big study looked at more than 300 ,000 changes made by AI tools on GitHub.

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Almost a quarter of the problems the AI introduced were still sitting there in the latest version of the code.

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Nobody had gone back to fix them.

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AI really does make a lot of programmers faster, and that's a big deal.

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And nobody has a reliable estimation of how much all of this debt will cost in dollars.

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The bill simply hasn't arrived yet.

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So yeah, AI is writing code faster than ever, but a lot of it is the kind of code

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that someone some day has to come back and fix

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which raises another question who's gonna fix it because that's the third bill

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and it's the one no one is ready to pay

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welcome to the third envelope and this one isn't about money or code it's about people.

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In 2025 a team from Stanford started tracking payroll data for millions of American workers and they've kept updating it ever since.

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What they found is

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that young people aged 22 to 25 in jobs where AI can do a lot of the work

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now have about 19 % fewer jobs than they should have compared to young people in other jobs.

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But get this, experienced worker in the exact same jobs are doing fine.

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Companies are not firing their seniors, they've actually quietly stopped hiring juniors.

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And if you think about it, That makes sense.

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The tasks companies used to give to juniors, for example, building simple features, writing tests, and fixing small bugs,

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are exactly the tasks that the AI is best used for.

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Researchers in South Korea talked to developers about this, and one senior engineer said something pretty chilling.

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Their company let a lot of junior engineers go,

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and there was, quote, no impact whatsoever.

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Then the researchers talked to juniors who are still learning, and one of them said this.

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I don't know what not to do, I've only seen the good examples.

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See that right there?

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That's the problem.

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Juniors used to learn by writing bad code, breaking things and then getting roasted in code reviews.

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Now the AI hands them the code that works and they never find out why it works.

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Anthropic, one of the companies that actually makes these AI tools, tested this in early 2026.

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They had 52, mostly junior developers, learn a new coding tool.

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Half of them could use AI and the other half had to figure it out on their own.

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Then everyone took a test to see how much they actually understood.

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The group with AI scored 17 points lower and they weren't even noticeably faster.

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Now think about where this goes.

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Every senior developer on the planet started as a junior, who at first broke something, he made a mistake.

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That's how you learn and right now we're building a system where nobody gets to break anything.

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It's like a restaurant where the head chef gets an amazing machine that does all the chopping,

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so the restaurant stops hiring kitchen staff.

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It works great, right up until the day the head chef retires

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and nobody in the building knows how to cook

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so in 10 years who's gonna be the senior developer who

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checks what the AI wrote who's gonna find those security holes

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and clean up all the copied code from the bill number two put it all together

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and you get something like this the AI writes the code then the code needs fixing

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but the people who could fix it are never getting hired.

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You can stop thinking of this third thing as a bill, instead think of it as an actual time bomb.

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You know, there are people at the very top that can see it coming.

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Amazon cut 16 ,000 corporate jobs in January 2026.

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But that same year, the boss of Amazon's cloud business said that Amazon is hiring 11 ,000 interns and new graduates.

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And when people asked him about replacing juniors with AI, he called it one of the dumbest things I've ever heard.

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Say what you want about Amazon, but here, that's a good call.

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So, what does all of this mean for you?

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If you're a student, or you're thinking about learning to code, that same antropic study has some good news.

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Not everyone in the AI group did badly.

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The people who asked AI why something works, instead of just asking to do all the work for them

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learned almost as well as the people who didn't use AI at all.

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AI isn't your enemy, it's just a really bad teacher if you only ask it for answers.

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Instead you should question everything and the most important question to ask is why?

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Why is it making those specific decisions?

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Use it for brainstorming and understanding

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And suddenly, it might become one of the best teachers you'll ever have

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The job itself is changing also

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The time of manually typing out all of your code line by line is over You shouldn't do that

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Unless you want to look like a Neanderthal to your own colleagues

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Instead, you should focus a lot more on understanding what needs to be built, and checking whether the AI actually built it correctly,

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which, if you've been paying attention, is exactly the skill that companies are running out of.

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I can't promise anyone a job, and honestly, nobody can right now.

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but if the data is right the companies

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that fired everyone to save money are gonna need people who really understand code

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and there's a real chance those people will be very very expensive okay remember

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that sentence from 2013 back then it was the best career advice in the world

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In 2026 it might need a small update.

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Don't just let AI write your code.

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Understand it.

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Because programming is not dead.

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But somebody is gonna have to pay these three bills.

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And my guess is that it won't be the AI.

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Unless of course the AI gets so good that it can clean up its own mess.

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And to be fair, that's the one big question nobody can really answer just yet.

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AI is getting better at coding pretty much every month.

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Maybe one day it really will be able to do all of this on its own or maybe

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today's AI is gonna hit a ceiling and will end up needing people who understand code more than ever.

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Honestly, nobody knows, but that's a story for another video.

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이 레슨의 어휘와 말하기 포인트

이 말하기 레슨은 영상 “AI Destroyed My Profession”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: code, companies, bill. 이 영상에는 섀도잉할 문장 195개와 단어 2476개가 있습니다. 말하는 구간의 길이는 20:17입니다. 화자는 분당 약 122단어의 일정한 속도로 말해서 섀도잉하기에 편한 속도입니다. 단어의 87%가 영어에서 가장 많이 쓰이는 3,000단어에 속해 어휘가 쉬운 편입니다.

이 영상의 핵심 어휘

영상에 나오는 익혀 둘 만한 단어 15개를 발음, 뜻과 함께 정리했습니다.

단어	발음	뜻
programmer 명사	/ˈpɹoʊɡɹæmɚ/	프로그래머
token 명사	/ˈtoʊkən/	토큰
hire 동사	/ˈhaɪɹ/	고용하다
headline 명사	/ˈhɛd.laɪn/	표제, 헤드라인
envelope 명사	/ˈɛnvə(ˌ)loʊp/	봉투
salary 명사	/ˈsæləɹi/	급료, 봉급
chef 명사	/ʃɛf/	요리사, 료리사
researcher 명사	/ˈɹiˌsɝ.t͡ʃɚ/	연구원, 연구자
chart 명사	/t͡ʃɑɹt/	차트, 도표
cloud 명사	/ˈklaʊ̯d/	구름
wash 동사	/wɑʃ/	씻다
badly 부사	/ˈbæd.li/	나쁘게, 서투르게
explanation 명사	/ˌɛkspləˈneɪʃən/	설명
worker 명사	/ˈwɝ.kɚ/	노동자, 로동자
skill 명사	/skɪl/	기술, 스킬

영상에 나오는 구동사

단어	발음	뜻
come back 동사		돌아오다
come out 동사	/ˌkʌm ˈaʊt/	나오다
go out 동사		나가다
go up 동사		올라가다
wipe out 동사		무찌르다

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
현재완료진행 have/has been + -ing — 전에 시작해 지금도 계속되는 동작	has been tracking · you've been paying
“used to” used to + 동사 — 지금은 아닌 과거의 습관이나 상태	used to give · used to learn
현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때	they've actually tried · has dropped · has collapsed
관계절 who / which + 절 — 사람이나 사물에 대한 추가 정보	guy who runs · people who could · people who asked

주의할 발음

화자는 gonna, didn't, don't 같은 축약형과 약화된 형태를 36번 사용합니다. 들리는 대로 짧게 발음하세요.

“sh”와 “zh” 소리: chef /ʃɛf/, wash /wɑʃ/, explanation /ˌɛkspləˈneɪʃən/, estimation /ˌɛs.təˈmeɪ.ʃən/
긴 단어 — 강세 위치에 주의: developer /dɪˈvɛləpɚ/, explanation /ˌɛkspləˈneɪʃən/, unemployment /ʌn.ɪmˈplɔɪ.mənt/, unbelievable /ˌʌnbɪˈliːvəbl̩/, whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/

한국어 화자가 어려워하는 소리:

/f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: chef /ʃɛf/, fixing /ˈfɪksɪŋ/, fewer /ˈfjuː.ɚ/, phrase /ˈfɹeɪ̯z/, folk /foʊk/
/v/ — ㅂ(/b/)과 구별하기: developer /dɪˈvɛləpɚ/, envelope /ˈɛnvə(ˌ)loʊp/, convenient /kənˈviː.niənt/, unbelievable /ˌʌnbɪˈliːvəbl̩/, whatsoever /ˌ(h)wʌtsoʊˈɛvɚ/
/z/ — ㅈ이 아니라 성대를 울리는 /s/: phrase /ˈfɹeɪ̯z/, optimize /ˈɑptɪmaɪz/

이 영상으로 연습하는 방법

먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
보통 속도로 한 문장씩 섀도잉하고, 화자의 리듬과 맞을 때까지 반복합니다.
자신의 목소리를 녹음해 원본과 비교하고, programmer, token, hire 같은 단어에 특히 주의합니다.

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

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