ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: Can This Vibe Coder Beat a Senior Developer?

กำลังสร้างบทเรียน...
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Can AI make a Vibe Coder beat a senior engineer?
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We locked a Vibe Coder, a junior dev, and a senior dev in one room.
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One challenge.
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Unlimited AI. Who wins?
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Hey everyone, I'm Sudarshan and I'm the Vibe Coder.
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Hi, my name is Ocean.
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I'm the junior developer for today.
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Hi everyone, my name is Ankush Dharkar.
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I'm a senior developer.
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For the past decade, I've been building high-scale systems.
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Build an AI agent that reads Hackerang support tickets and decides to reply.
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Or escalate it to a human.
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Do I get a job here if I build this?
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Can I build this for Claude instead?
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Because I think they need support more.
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I actually lucked out because Opus 4.8 launched last night.
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So I just used the best in class model.
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I never use Claude.
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I do not trust Claude.
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It's just too expensive.
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High maintenance is not for me.
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Sorry.
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I have Claude code and I have God, so that works.
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Time actually started.
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The second loop.
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This is the code base which has four things the hacker rank support tickets they need to sort, a help center they pull answers from for tickets,
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a starter file written in Python where they build the agent, and an agent's .md, a guide that gives the AI its rules.
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Right now, the scaffold has a Python file in it.
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I'm not really comfortable working with Python, so I'll probably move to JavaScript or TypeScript, TypeScript hopefully, so that I can also read the code in case I have to verify something.
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And then I have a bunch of things here in the GitHub repository, which let's be real, I don't think I'm going to read any of this.
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Time to put all of this directly into Claude.
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So definitely there has to be some P0s, like undeniable for the product.
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I want to make sure the AI gets that.
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If AI doesn't get that, we have a bigger problem.
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I am still nervous because it's again a huge project in such less time.
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And I also have to keep the UI in mind.
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I did test two different intras.
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One is where there would be multiple LLM calls for each ticket.
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But the other one would be where it would sort of upload in batches
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or it would process in batches and they would be async sort of processing.
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There's a whole listing of all these tickets that's been raised to the agent.
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I have a very extensive test suite.
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Also built, like I said, open routers because, you know, in early stage, we want to get feedback quickly, but at the same time, have something we can ship if we wanted to.
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I'm the most worried about the junior developer.
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Why?
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I think they bring the energy and so much experience with AI tools that they'll crush it.
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Only escalate 20% of the issues.
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I am now sort of doubting and figuring out if that actually the right implementation.
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Awesome.
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So we do have the first version ready here.
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It was able to index all of the support tickets we have.
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It's also able to retrieve it.
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But the UI is, at least as of now, looks like it's up and working without any errors.
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So I'll probably take that as a win because we only spent about 45 minutes.
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Every engineer was locked in until the product manager walked in with his ideas.
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Can you explain what you've made?
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So I essentially have a support rat agent.
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I'm calling it hand because it can go through a ticket batch.
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We should do a toggle, dark mode and light mode.
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Sure.
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Call it the colorblind mode.
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So the product manager was here a while ago
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and he asked me to build the dark mode
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and light mode toggle based on the time of the day and I tried building it.
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It sort of messed up my code altogether and now I'm just trying to like get it fixed.
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My infra just suddenly seems a bit flaky.
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So, look at that dude.
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Basically it creates wireframes.
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So right now I'm just building a few AI mockups so
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that I can refer to this like on a high level
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design how I should connect the data to the UI as well.
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Hello, what's up?
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What is Rag?
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Rag is the model that, you know, segregates whether the ticket should be assigned.
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I don't think you know what it means.
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I forgot the filter.
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I'm going to launch different sessions.
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One will build the UI which will have its own test.
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One can just be an agent that goes through, creates the RAD, creates the agent pipeline.
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And then one can be a simple backend server that connects those two.
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It's a flat architecture.
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You understand, right?
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What I'm talking about.
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Now, start it.
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Okay, now put all the same color together.
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You fended off a villain, a product manager, here's your reward, choose one lifeline.
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Phone a dev, 10 minutes on the phone with a DL engineer, I'd rather talk to Kursar.
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Borrowed time, plus 15 minutes at the end, a diet coke, you get one diet coke.
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I'll take the borrowed time, plus 15 minutes at the end.
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I think I don't need to phone a dev, I have Claude Code and I have God so I think I'll go with two, borrowed time.
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I think I'll phone a dev.
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Wait, I'm the only one who's gonna phone a dev?
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Yeah.
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I know.
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That's such a junior engineer thing to do.
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Meet Hank.
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Hank is Hackerank's support agent that would be able to cover any kind of support tasks by itself.
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You can either ask it a particular question that you have or you can also attach a CSV.
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I think on the longer run, Alvin, because they'll exhaust their tokens.
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Hello, yeah we have a problem.
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My tokens are over so I would need more.
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Yes, thank you.
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I'll have to lock in the last one hour.
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So what you do is whenever you want to repeat something right in your API, there are two ways to do it.
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Right, so what do you do?
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My whole approach is wrong, as usual.
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At this stage, this end of the competition, I think I'm expecting all of them to at least have finished a demonstrable product
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which at least starts processing the tickets and triages them.
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The quality of triage may not be great but that is always something that can be improved upon later.
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Hey, you have 10 minutes to go.
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Do you still want that extra 15?
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No, I think I'm good.
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I would rather take a 2 rupee office.
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Is that Picasso?
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Oh, that's one of the best paintings I've seen too.
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So, this is the basic UI of what we built
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so far in the last few hours gave it a pretty
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hacker ranky feel the same kind of theme same kind of colors
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and stuff as you can see we have a list of
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all the tickets here gave user a simple control to run
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it this can be automated as well it's a pretty simple
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fix we have a place where all the triage tickets go
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and i also created a stats for nerd kind of a page
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so that if you want to dive deeper into what caused certain answers to be escalated
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or to be replied you can take a look there let's see how it performs even
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if it fails that's okay i can live with it
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because i know the way this is built there will be
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minor tweaks to be done to raise it to the bar of a production application.
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The front end is pretty much just made out of HTML that is again like grabbed in a Python file, the main file of Python.
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You can search them up, you can see categorization based on the type of request it is or the outcome and then you can see the tickets,
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you can see all the categories again and once you click on
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that row you get into the ticket summary where you can see everything the UI
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and base this agent was completely working on the UI and fixing up cosmetic issues.
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The agent workspace is working completely on the agent, the rag model, the fast API, and also building that scaffold for LLM to answer the user.
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Today I've built Hank.
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Hank is an AI agent that goes through Hackerang support tickets
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and it would sort of come up with a grounded reply on any sort of support ticket
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if it can sort of resolve by itself.
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If not, it would immediately flag it for human review.
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You can ask Hank anything to begin with.
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Hank would be able to process all of them at once.
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Let's go ahead and maybe attach a CSV of a bunch of support tickets.
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And as you can see, Hank is able to essentially go through each of the support tickets
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and it sort of tests this with all the knowledge base articles that Hacker Hank already has.
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And it would just prioritize them and figure out whether each of the tickets needs human review or not.
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It would also categorize it based on whether it's a product issue, whether it's a bug.
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One thing that I can compete with in this case would be user experience
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and design and interaction and what are the different kinds of delight moments.
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Still, I'm still hoping I won't finish last.
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Now they defend their submission to an AI judge who has the full context of their code and prompts.
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Give me a quick two-minute pitch of what you built.
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Walk me through what happens from a support agent's point of view, start to finish.
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So this is what happens, right?
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The support agent essentially...
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And now, on to the results.
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I've read every line of code, every prompt, and every answer the three of you gave me today.
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Every one of you leaned on AI today, but the ones who did best understood what they shipped.
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Tonight, the person who balanced them best is Ankur.
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Congratulations.
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Any final thoughts?
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The biggest thing is I think the AI models have become
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really good where you can work on things you've never worked before.
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Like some of the things I've worked on today, I've never worked on in my life.
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I just barely knew some concepts and I was able to just use one model, ask it through and get things rolling and within the time frame got pieced together and it worked.
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So I think good fundamentals, good experience asking the right questions.
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We should be playing along with the model
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and being a good partner with the AI coding agents and build something out together.
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This was a lot of fun.
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Thank you HackerRank team for doing this and looking forward to more challenges and folks have fun with AI, build cool things and let's get cracking.

สิ่งที่คุณจะได้เรียนรู้

ในวิดีโอนี้คุณจะได้เรียนรู้ทักษะการพูดที่สำคัญ เช่น การตั้งคำถามและการแสดงความคิดเห็นเกี่ยวกับการพัฒนาเทคโนโลยีใหม่ๆ นอกจากนี้ยังมีการสื่อสารเกี่ยวกับความกังวลและการทำงานร่วมกับทีมที่มีประสบการณ์ที่แตกต่างกัน ซึ่งจะช่วยเสริมสร้างทักษะการสนทนาของคุณให้เข้มแข็งขึ้น

ฟังเสียงเหล่านี้

ในวิดีโอนี้มีการพูดที่เชื่อมโยงกันและการลดเสียงที่น่าสนใจ การเรียนรู้วิธีการเชื่อมเสียง เช่น การพูด “I want to make sure” ที่ฟังดูเร็วและไหลลื่น จะช่วยให้คุณฝึกฝนการฟังและการพูดในแง่ของการเชื่อมโยงคำและประโยค คุณจะได้ยินการใช้เสียงที่ลดลง เช่น “gonna” แทน “going to” และการพูดเร็วที่ทำให้ประโยคดูมีชีวิตชีวา

พูดเหมือนเจ้าของภาษา

เมื่อคุณฟังการสนทนาในวิดีโอนี้ ให้ลองสังเกตถึงจังหวะและการเน้นเสียงที่ผู้พูดใช้ การเลียนแบบจังหวะการพูดและการเน้นเสียงจะช่วยให้คุณพูดได้อย่างไหลลื่นและเป็นธรรมชาติมากขึ้น ลองทำการฝึกชาโดว์อิ้งภาษาอังกฤษด้วยการฟังและพูดตามเสียงในวิดีโอ การฝึกแบบนี้เป็นวิธีที่ดีในการปรับปรุงความสามารถในการพูดของคุณ คุณอาจเริ่มต้นด้วยการเลือกประโยคสั้นๆ แล้วค่อยๆ ขยายไปยังส่วนที่ยาวขึ้น

การใช้ shadowing site และ shadowspeak จะช่วยให้คุณเข้าถึงทรัพยากรที่มีคุณภาพในการเรียนภาษาอังกฤษจากวิดีโอได้มากขึ้น ทำให้การฝึกพูดภาษาอังกฤษของคุณมีประสิทธิภาพและสนุกสนานยิ่งขึ้น

เทคนิค Shadowing คืออะไร?

Shadowing เป็นเทคนิคการเรียนรู้ภาษาที่ได้รับการรับรองทางวิทยาศาสตร์ พัฒนาขึ้นสำหรับการฝึกนักแปลมืออาชีพ วิธีการนี้เรียบง่ายแต่ทรงพลัง: คุณฟังเสียงภาษาอังกฤษจากเจ้าของภาษาและพูดตามทันที — เหมือนเงาที่ตามผู้พูดด้วยช่วงเวลาห่าง 1-2 วินาที การวิจัยแสดงว่าเทคนิคนี้ปรับปรุงความแม่นยำในการออกเสียง ทำนองเสียง จังหวะ การเชื่อมเสียง การฟังเข้าใจ และความคล่องแคล่วในการพูดได้อย่างมีนัยสำคัญ

เทคนิค shadowing: อ่านคู่มือฉบับเต็มทีละขั้นตอน →