Shadowing Practice: Trust the Process: How to Design Teams That Actually Work - Learn English Speaking with Video

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Swift trust can help your communication and your teams be more effective.

My name is Matt Abrahams, and I teach strategic communication at Stanford Graduate School of Business.

Welcome to Think Fast, Talk Smart, the podcast.

Today, I look forward to speaking with Melissa Valentine.

Melissa is an associate professor in the Management Science

and Engineering Department at Stanford and a senior fellow at the Stanford Institute for Human -Centered Artificial Intelligence.

Her research focuses on how emerging technologies, including artificial intelligence and algorithms, are fundamentally transforming work, organizational design, and team dynamics.

Melissa, along with her co -author Michael Bernstein, wrote the fascinating book, Flash Teams, leading the future of AI -enhanced on -demand work.

Well, welcome, Melissa.

I'm really excited to have you join us.

Thank you.

This show is so fun, and I love the guests you have, so I'm delighted to be here.

Well, thank you.

And thanks for being one of them.

Should we get started?

Let's do it.

Excellent.

I have to say, I really enjoyed your book, Flash Teams, very much.

Really, really interesting.

Can you define for all of us what a flash team is and explain what people, processes, and infrastructure enable flash teams to get aligned and execute quickly?

So my PhD is in organization science, basically.

So I got my PhD at a business school.

And then my collaborator is a computer science professor, and he was doing a lot of work on crowdsourcing

so what's cool about crowdsourcing is um like the crowd is like millions of people online right

and you can get things done quickly

because you just like put a task out

and then there's millions of people who are available to come work on the task

but what he was seeing at the time that he

and i started working together was crowdsourcing was sort of stuck

because they were doing like really they call them like micro tasks

but just really like small tasks and then i had this toolkit organization science

and my dissertation had been about how you can use basically like team scaffolds

or like sort of lightweight team structures

and then like you you populate the team structure with experts

and the team structure and the role structure helps them know how to work together

so we sort of were able to combine the logic of both of these

so you have these like lightweight structures

that allow people who are like relative strangers to come together

and to work together on really complex stuff this system

that we built with like a great team of like a

PhD student Daniella Ratelny she organized this great lab at the time we first did our flash teams

so we built a platform that basically like took all the logic of organization science

and team science and then the speed and scale of crowdsourcing

and then like put them together so the way the system works we have this platform

where like i'm somebody who like wants to get something done

so i go to the platform i like design the team

and then the platform integrates with something like we used upwork

so there's like 10 million freelancers who are on upwork and then so i'll say here's the task that I need done.

Here's the role I need filled.

And then the platform can integrate with Upwork.

And then it's open call to like the 10 million freelancers.

Who's got the right expertise?

They join the team.

So you can just convene teams really fast.

And what we showed with this research is that like you can get things done really quickly.

You can pull teams together.

They build really complex stuff really quickly.

And it was really inspiring.

I mean, it's even faster now with Gen AI.

So you set a framework and expectations and then leverage a tool

that pulls people in and then the Flash team is really the focused, concerted effort that it's all about.

Can you talk to us a little bit about the structures that you can set up for teaming?

It sounds like you've done some research in that.

Give me an example of what a structure for efficient teaming looks like.

There's like three structures that are very useful for a Flash team.

The first is the role structure.

So that's going to be our relative expertise.

So let's say that I am I'm a UI designer and you're a front -end developer, like we get together and we know, I know what I'm responsible for.

I know the skills I need, I know the tools, the platforms, and you know that too.

And since we're both so expert at what we do, we can kind of negotiate it fast.

I can say, how is the screen gonna work for you?

Or you can say like, where is this functionality gonna come from?

And we just like negotiate it quickly.

Because we know each other's role.

Exactly.

Yes, and because we know people of that role, somebody else could plug in if you get sick or move on.

Excellent, I really like that.

Yeah, so the role structure.

So the second one is the team structure.

And the team structures are like what help a group know that they are accountable to each other.

And so for example, one team structure could be like everyone being responsible together for something.

Like maybe there's a team rating instead of individual ratings.

So that's what you're going to be looking for.

Individual ratings, then everyone is going to be like every person for themselves.

If it's a team rating, like everyone pulls together and is like, we're all in this together.

So it's how we team and how we assess the teaming.

Very powerful.

Students don't like group projects, right?

Because being all in it together can either be the best thing or the worst thing.

So the team structure.

And then the last one actually is hierarchy.

And hierarchy as a structure is about who has the right to make decisions, right?

In some ways, again, people don't necessarily think they like hierarchy, but hierarchy is so useful for coordination because you have...

you know five strangers show up together maybe everyone has a different idea of what should happen

but if you have this sense it's like another role structure

if you have a sense of who's the final decision maker

right a good enactment of hierarchy is they take in all the information they understand like what needs to happen

and they just communicate it clearly right

so like the coordination of the group happens through hierarchy that's fantastic

100

so so three primary roles that you just identified our role that is how we relate to each other in our expertise, the teaming, how we assess and work together and reward,

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get rewarded, and then hierarchy or decision -making, which really determines how we can actually move forward.

102

That's right.

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And I think all of us, regardless of if you're putting together a flash team or not, can think about those structures in your team that you currently have to help optimize it,

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or if you're forming a new team, to think about that.

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Thank you.

106

That's great.

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You know, one of the essential elements of any teaming or groups coming together is trust.

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What are some of the communication skills or other skills that people can deploy to establish trust quickly?

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I'm assuming part of what flash teams do besides accomplish their work is they're able to coordinate action, perhaps through building trust.

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Yeah, trust in flash teams is essential and complex, right?

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Because it is relative strangers.

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You get together and you work together really intensely and then you disassemble.

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So I think that there's this idea in the literature called like swift trust.

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And there's like an assumption that you just assume trust.

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Like you just meet somebody for the first time, you assume they're competent, you assume that they know how to do their role, you assume you're both there for the same reason, to like work hard, get it done.

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So that, yeah, the assumption of swift trust is really useful.

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It doesn't always work out.

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So I think it's, yeah.

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But the sort of like offering of swift trust is part of it.

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And then, yeah, paying attention to when it's not going right

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and like being willing and able to kind of repair quickly is also important.

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I love this idea of swift trust.

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So you approach from a place of trust, assuming that you are trustworthy and I will trust you and you will do the same,

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can expedite things because there's a lot of this testing that goes into trust and time.

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And if you start from that place, and obviously, you know, it might fail or people could take advantage of it.

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But the second part of what you said, I think really is the helpful part is to have

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that meta awareness and watching for it and then being willing to speak up and try to repair it.

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Yeah.

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So I think it's not only swift trust being open to trust, but being open to repair when it's not there.

130

Yeah, exactly.

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I really like that idea of swift trust.

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So much in my life I think would be better if we just approached everything with this notion of idea.

133

Yeah.

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I mean, there is a real difference because I think of the person I wrote the book with, Michael, he and I have worked together for 15 years now, and that is a different kind of trust than swift trust.

135

But swift trust is a tool that's useful.

136

Right.

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And it's a way to at least initiate, and then you can build deeper trust in a relationship.

138

That can only happen, I think, after repeated exposure and time.

139

Totally.

140

Yeah.

141

You talk about discursive diversity, and I had to practice saying that multiple times, by the way.

142

Can you share what you mean by discursive diversity?

143

And how can teams recognize when they need to shift their communication style from a more open -ended,

144

brainstorming ideating to a very highly coordinated approach yeah so

145

that is from the dissertation of one of my really brilliant PhD students

146

so her name is Katarina Licks and she kind of invented that measure

147

so what she was able to do she had all of

148

the sort of like slack transcripts of different flash teams

149

and she was able to she did this NLP processing

150

and NLP is natural language processing yeah yeah before it was cool she learned how to do it

151

and she was able to create this measure where she was looking at like the similarity of the language

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that people were using so you have all of the slack interactions

153

and you can basically compare people talking on the team

154

and how similar are the words

155

that they're using the sentence structure right are they using the same adverbs like adjectives sense of urgency gets encoded

156

and all of that

157

and what she was able to show is the the sort of similarity of the language

158

that people are using or the the difference

159

so this is where let's see right discursive diversity yeah

160

so like the diversity of discretion i guess like the diversity different types of words exactly yeah yeah

161

so that sort of would predict the team meeting a milestone in different ways

162

so there were times when you really want the language to diverge

163

so this is a moment of brainstorming ideation right you want

164

a lot of creativity you want a lot of divergence but then as you get closer to the deadline, you really, for the team to meet the deadline, then the language needs to converge.

165

Like people need to start sounding more like each other to hit the deadline.

166

So one, it's a measure really.

167

So you can, you can look at, you know, if I'm a manager or somebody looking back at doing a post -mortem or after a project is done, and I can look at the communication, be it Slack, JIRA, whatever the tool is.

168

And I can actually see the language might be a hint as to where we are.

169

Yeah, totally.

170

And as you're trying to get closer to the decision, more similar language is a sign.

171

What I'd be curious, and I don't know if there's any research on this, is can you actually use language to influence that?

172

So can I, as a manager, encourage more diverse language through ideation?

173

But when I want us to start moving towards a decision, encourage people to start using similar language.

174

I wonder if it's causal in that way.

175

Right.

176

I think that's a great research question.

177

I think that's really interesting.

178

So I encourage everybody listening to think about the language you're using for the different tasks you have

179

and start to notice what that looks like.

180

And maybe you can run your own experiment and play with that.

181

I want to keep on flash teams and then I want to have a broader question.

182

But when flash teams hit a snag, for example, like a miscommunication,

183

what is the most effective way to fix that so they don't fraction and deal with too much friction in those situations?

184

I'm so glad you asked this question.

185

I have an unpublished paper.

186

So we ran three really complex flash teams one summer, and we had all of the DMs.

187

So we had all the Slack front stage and then all of the Slack DMs, the backstage.

188

And the thing that was really interesting in analyzing all of that data is a lot of repairs happen backstage.

189

So something would happen in the public Slack channel

190

and then a dyad would go to the back channel and they'd be like, what is this bug?

191

And they would like kind of sort it out and then come front stage with the solution.

192

Oh, interesting.

193

So it created a lot of like smooth operations.

194

Like the Flash teams, they all, you know, accomplished their goal.

195

There didn't seem to be a ton of conflict.

196

So, this pattern of backstage repair was really interesting to discover.

197

I think, I mean, like any human behavior, it's got different sides to it.

198

So I think it did support smooth operation.

199

But what I saw in the analysis that I have not yet published is

200

that the people who were more involved in backstage repair ended up with more influence over time.

201

So these are the workers and the managers who were really helping make the decisions.

202

So it's something about like access to where the real problems get solved was like creating a lot of influence for people.

203

And I think that I don't totally know what to do with

204

that as someone who is interested in flash teams going well.

205

I would maybe say you need like a postmortem on a flash team.

206

What were the problems?

207

Who helped solve them?

208

What do we learn about this together?

209

It's really, really intriguing that the people involved in that repair or that dealing with those problems end up being more influential.

210

Yeah.

211

Yeah, because it's like they had like the realer story of what was going on, and sometimes it was like in the backstage repair that decisions were made and then presented as if they were quite done,

212

if that makes sense.

213

That's really intriguing.

214

I'm putting on my manager hat and thinking if I were in the midst of any team, be it a flash team or a regular team,

215

how I could be aware that the folks who are involved in helping fix, repair, dive deep into problems,

216

what that means for them in terms of their currency and how we interact on the public stage.

217

And I just think it's interesting that we now have these two channels and ways of communicating that can be measured.

218

I know you think about storytelling and change.

219

How can everyday employees in an organization use storytelling to drive broader systemic change

220

and build coalitions to help achieve whatever it is they're trying to achieve?

221

Yeah.

222

So one of the studies that I did when I first got to Stanford was actually an academic Cancer Center.

223

And I saw stories be really influential in this study.

224

So it feels a little different than what we've been talking about with AI and algorithms and so forth.

225

But it still to me is a study of organizational design, which is what I'm really interested in.

226

So in this, what happened in this study, so I was studying as this cancer center was trying to do a transformation.

227

They were trying to kind of decrease the coordination burden on patients and their families.

228

And during During the study, there was a group of patient advocates

229

or activists who really wanted the Cancer Center to understand how much coordination they were having to do.

230

So the way that they made their case, this is why I'm thinking of it, is they had an initiative they called patient stories.

231

And so they collected, they went to great effort to collect a lot of patient

232

stories where patients just talked about like a family member had

233

to quit their job to become the full -time coordinator for the patient.

234

So they came up with dozens of patient stories.

235

And then in this paper that I have, I analyzed how they basically used the stories to make the case and to kind of spread the movement,

236

spread the message across the cancer center.

237

And at the end of the study, they had kind of convinced the cancer center to take on some of the coordination work.

238

So it ends up being this kind of end -to -end story of like patient stories, patient narratives, actually changing the organizational design, which is why I'm thinking about it.

239

It was like a very powerful thing that these patient activists did.

240

Stories can really resonate and motivate people.

241

Was there anything specific to the stories that you think were really important?

242

Was it the fact that the stories accounted for all the specific coordination events?

243

Or was it the emotionality?

244

Or was it the fact that these people just collected a bunch of stories and the Cancer Center was like, wow, there are all these stories, we should probably do something.

245

I think a lot of us interface with the healthcare system and we could just like see ourselves.

246

So the patient stories were just like, this is us, this is you and me.

247

So there's a connecting piece there.

248

Yeah, really connecting piece.

249

And then it illustrated the problem really specifically.

250

So like somebody is like, you know, sitting in a wheelchair in a hallway cause they'd sort of been dropped or something like that.

251

And so it's like, wait, like I think the cancer center is so full of people who care

252

and then hearing like the specific instance in a really relatable story, they were just like, oh, that's a problem that I can help with.

253

I think you hit on it.

254

It's relatable and real.

255

Yeah.

256

And we can connect.

257

Thank you.

258

Can you take what you've learned about Flash Teams

259

and give us any insight that we can just apply to a normal team?

260

So I've got a team that's been around for a while and we meet regularly.

261

Is there any insight from your work on Flash Teams that could perhaps help my team be more efficient, feel more connected, ideate better?

262

One thing that Michael and I used to say when we were writing the book, we were trying to think of, like, what's the mindset here that, like, any manager would find empowering?

263

And the phrase we came up with is experts everywhere all the time.

264

So you've got your, like, trusted team.

265

Great.

266

You know, keep working together, taking good care of each other, working hard.

267

But, like, really recognize that your organization, the world, the Internet, your friends,

268

like, the world is just full of experts who can help and people like helping and bringing their expertise to something.

269

So it's just like having a mindset of like recognizing how much collaboration is available, how much expertise is available. And yeah,

270

so maybe it like invites you to kind of like think of the boundaries of the team a little more porously.

271

Yeah, exactly.

272

That's funny you said that, because that was exactly the word I was thinking is porous is

273

that it can be very easy to insulate a team and say, this is the team, but being a little more open and pulling in expertise.

274

When I was managing a team, I ran a learning and development group, and we had this very tricky thing we had to train people on,

275

and it turned out that somebody in the company who was an admin was using our tool,

276

and they actually knew how to do things that we were trying to figure out how to train people on better.

277

That person was an expert, and by just dumb luck, we figured that out and incorporated them into the team.

278

and I like that idea.

279

I think that there are a lot of tools that can be very helpful to managers

280

in terms of how the team like works together, coordinates and stuff like that.

281

So, you know, like having an eye towards, the other thing we said in the book is like AI driven team design.

282

So just making use of the tools to be very thoughtful in how you're structuring your team.

283

So AI can help us structure the team and maybe even identify who some of the experts are that we might know.

284

I love that.

285

Melissa, this has been great.

286

Before we end, you know, I like to ask three questions when I make up just for you.

287

And two, I've been asking everybody, are you up for that?

288

Yeah, let's do it.

289

Beyond the academic research you do, you're also a creator and you study the algorithms that serve up information on social media.

290

What advice do you have for others who are creators?

291

Okay.

292

So I love Instagram and TikTok.

293

Like I have, I think it's people have like complicated relationships with social media.

294

So the attention stuff is real.

295

My attention span is shot.

296

But I have learned so much from content creators.

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I am such a fan.

298

My advice is keep going.

299

If you're an expert, put it out in the world.

300

People will find it.

301

I mean, different life transitions I've gone through, different health stuff, different fitness stuff, different hobbies.

302

I have learned so much from the internet.

303

So thank you, content creators.

304

You know, as a creator myself, and it took me a while to identify as a creator, But, you know, I think many of us are motivated to help people

305

and it's that motivation that actually helps us get through.

306

I mean, it's hard to put out the content and the algorithm can sometimes help you and sometimes not.

307

So it's that passion and that desire to learn and to help, I think, that really motivate.

308

And I can hear that in your voice and see it in the things that you post and create.

309

Question number two, who is a communicator that you admire and why?

310

So I'm at a moment where I'm thinking a lot about communication, where we like really like take each other in, in like a really deep way.

311

So I have a friend who is a therapist and a Buddhist, and she just like, she has like a quality of like listening and expression that,

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that allows for like.. true communication.

313

So I would say I'm going to nominate her.

314

Excellent.

315

And it's really that presence and listening and being there.

316

It's a fascinating thing about being very aware of yourself that allows you to be very aware of others.

317

It is a lot of presence, as you're saying, a lot of presence and connection.

318

I like that self -awareness and other awareness.

319

Thank you.

320

Final question.

321

What are the first three ingredients that go into a successful communication recipe?

322

Something that I've come to appreciate is how useful a deep awareness of your own experience is, because then you're even more able to take in another's and all of its complexity.

323

So yeah, self -awareness, other awareness, and then working from there, I think what's possible between you is new.

324

It's something that neither of you would have done without that kind of connection.

325

I sort of bristle at the word synergy, but in this case, that's exactly what you're talking about is the power of the two is greater than either individually.

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But that comes, as you said, from a self -awareness and then another awareness.

327

Well, thank you.

328

Thank you for the three ingredients and thank you for the conversation.

329

Your work to me is really intriguing because it focuses both on technology, but the human aspect of people coming together and the fact

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that there are structures that we can rely on to help expedite and make things more efficient.

331

Melissa, this has been fantastic.

332

Thank you.

333

And thank you for the work you do totally really fun

334

for me too thank you thank you for joining us for

335

another episode of think fast talk smart the podcast to learn

336

more about groups listen in to our episode 241 with colin fisher

337

and to learn more about social media algorithms please check out episode 268 with angelie christine

338

this episode was produced by katherine reed ryan campos

339

and me matt abrahams our music is from floyd wonder with

340

special thanks to podium podcast company please find us on youtube and wherever you get your podcasts.

341

Be sure to subscribe and rate us.

342

Also, follow us on LinkedIn, TikTok, and Instagram.

343

And check out fastersmarter .io for deep dive videos, English language learning content, and our newsletter.

344

Please join us for our Think Fast Talk Smart Learning Community at fastersmarter .io slash learning.

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You'll find video lessons, learning quests, discussion boards, an AI coach, and book club opportunities.

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Again, that's fastersmarter .io slash learning to become part of our ThinkFast, TalkSmart learning community.

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אוצר מילים והערות הגייה לשיעור הזה

שיעור הדיבור הזה ברמה C1 מבוסס על הסרטון “Trust the Process: How to Design Teams That Actually Work”. המילים שחוזרות הכי הרבה: flash, structure, trust. בסרטון הזה יש 346 משפטים ו-4419 מילים לתרגול Shadowing. הדיבור נמשך 22:06. הדובר מדבר מהר, כ-200 מילים בדקה, אז צפו לצלילים מחוברים ומקוצרים. 85% מהמילים נמצאות בין 3,000 המילים הנפוצות ביותר באנגלית; כדאי ללמוד את השאר לפני שמתחילים.

אוצר מילים מרכזי בסרטון הזה

15 המילים המתקדמות ביותר בסרטון, עם ההגייה והמשמעות שלהן:

מילה	הגייה	משמעות
hierarchy שם עצם	/ˈhaɪ.ə.ɹɑː(ɹ).ki/	הִיֵרַרכִיָה \ הייררכיה
coordination שם עצם	/kəʊˌɔːdɪˈneɪʃən/	תיאום
algorithm שם עצם	/ˈælɡəɹɪðm̩/	אַלגוֹרִיתְם
motivate פועל	/ˈmoʊ.tɪ.veɪt/	דרבן
brainstorming שם עצם		סִעוּר מֹחוֹת
similarity שם עצם	/ˌsɪm.ɪˈlæɹ.ɪ.ti/	דִּמְיוֹן
dissertation שם עצם	/ˌdɪsəˈteɪʃən/	תזה, דיסרטציה
ingredient שם עצם	/ɪnˈɡɹiːdi.ənt/	מרכיב, מצרך
accomplish פועל	/əˈkɑm.plɪʃ/	בִּצֵּעַ
assumption שם עצם	/əˈsʌm(p).ʃ(ə)n/	השערה hash'ará, הנחה hanakhá
milestone שם עצם	/ˈmaɪlˌstoʊn/	אבן מיל, אבן דרך
illustrate פועל	/ˈɪl.əˌstɹeɪt/	הִמְחִישׁ
fundamentally תואר הפועל		עֶקְרוֹנִית
microwave שם עצם	/ˈmaɪkɹoʊˌweɪv/	מִיקְרוֹגַל
wheelchair שם עצם	/ˈ(h)wilt͡ʃɛɹ/	כִּסֵּא גַּלְגַּלִּים, כיסא גלגלים

Phrasal verbs שתשמעו

מילה	משמעות
check out פועל	בדק
figure out פועל	הֵבִין, מצא תשובה

משפטים שכדאי לחזור עליהם

משפטים קצרים ושלמים מהסרטון שאפשר להשתמש בהם בשיחה יומיומית:

I'm really excited to have you join us.
Should we get started?
Here's the role I need filled.
Can you share what you mean by discursive diversity?
What do we learn about this together?

דקדוק בסרטון הזה

המבנים שהדובר משתמש בהם הכי הרבה, עם המילים המדויקות מהסרטון:

מבנה	בסרטון
הווה מושלם ממושך (Present perfect continuous) have/has been + -ing — פעולה שהתחילה בעבר ועדיין נמשכת עכשיו	we've been talking · I've been asking
הווה מושלם (Present perfect) have/has + past participle — פעולה שקרתה בעבר ועדיין יש לה חשיבות או השפעה עכשיו	you've done · have worked · you've learned
משפטי זיקה (Relative clauses) who / which + clause — מידע נוסף על אדם או דבר	people who are · somebody who like · people who were
סביל (Passive voice) be + past participle — הדגש הוא על מה שקורה, לא על מי שעושה את הפעולה	were made · are involved · can be measured

הגייה ששווה לשים לב אליה

הדובר משתמש ב-56 קיצורים וצורות מקוצרות, כמו I'm, you're, don't. אמרו אותם בצורה הקצרה, כפי שאתם שומעים אותם.

הצלילים של “th”: algorithm /ˈælɡəɹɪðm̩/, thoughtful /ˈθɔːtfəl/, therapist /ˈθɛɹəpɪst/
הצלילים של “sh” ו-“zh”: coordination /kəʊˌɔːdɪˈneɪʃən/, organizational /ˌɔː(ɹ)ɡənɪˈzeɪʃənəl/, ideation /ˌaɪ.diˈeɪ.ʃən/, dissertation /ˌdɪsəˈteɪʃən/, negotiate /nəˈɡəʊ.ʃi.eɪt/
מילים ארוכות — שימו לב להטעמה: hierarchy /ˈhaɪ.ə.ɹɑː(ɹ).ki/, coordination /kəʊˌɔːdɪˈneɪʃən/, coordinate /koʊˈɔɹ.dəˌneɪt/, organizational /ˌɔː(ɹ)ɡənɪˈzeɪʃənəl/, ideation /ˌaɪ.diˈeɪ.ʃən/

צלילים שדוברי עברית מתקשים בהם:

/w/ — שפתיים מעוגלות, לא /v/: lightweight /ˈlaɪt.weɪt/, hallway /ˈhɔlˌweɪ/, microwave /ˈmaɪkɹoʊˌweɪv/, wheelchair /ˈ(h)wilt͡ʃɛɹ/
/æ/ — פתוח יותר מה-“אֶ” העברית, לא כמו “a” ב-“cup”: slack /slæk/, backstage /bækˈsteɪd͡ʒ/, algorithm /ˈælɡəɹɪðm̩/, fascinate /ˈfæsɪneɪt/, freelancer /ˈfɹiˌlæn.səɹ/
/r/ — הלשון לא נוגעת בשום מקום, לא ה-“ר” הגרונית: hierarchy /ˈhaɪ.ə.ɹɑː(ɹ).ki/, algorithm /ˈælɡəɹɪðm̩/, discursive /dɪsˈkɜː(ɹ)sɪv/, intrigue /ˈɪntɹiːɡ/, coordinate /koʊˈɔɹ.dəˌneɪt/

איך לתרגל עם הסרטון הזה

הקשיבו לכל הסרטון פעם אחת בלי לדבר, ורשמו את המילים שאתם לא מכירים.
התחילו במהירות 0.75×, תרגלו Shadowing משפט אחר משפט, וחזרו למהירות רגילה כשזה מרגיש קל.
הקליטו את עצמכם והשוו למקור, תוך תשומת לב למילים כמו hierarchy, coordination, algorithm.

מהי טכניקת השאדואינג?

שאדואינג היא טכניקת למידת שפה מבוססת מדע שפותחה במקור להכשרת מתורגמנים מקצועיים ופופולרית על ידי הפוליגלוט ד"ר אלכסנדר ארגואלס. השיטה פשוטה אך עוצמתית: אתה מקשיב לאודיו באנגלית ילידית וחוזר עליו בקול רם מיד — כמו צל העוקב אחרי הדובר עם עיכוב של 1–2 שניות בלבד. בניגוד להאזנה פסיבית או תרגילי דקדוק, שאדואינג מכריח את המוח והשרירים בפה לעבד ולשחזר דפוסי דיבור אמיתיים בו זמנית. מחקרים מראים שזה משפר משמעותית את דיוק ההגייה, האינטונציה, הקצב, הדיבור המחובר, הבנת השמיעה ושטף הדיבור — מה שהופך אותו לאחת השיטות היעילות ביותר להכנה לIELTS Speaking ולתקשורת באנגלית בעולם האמיתי.

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אוצר מילים והערות הגייה לשיעור הזה

אוצר מילים מרכזי בסרטון הזה

Phrasal verbs שתשמעו

משפטים שכדאי לחזור עליהם

דקדוק בסרטון הזה

הגייה ששווה לשים לב אליה

איך לתרגל עם הסרטון הזה

מהי טכניקת השאדואינג?

【TED】優れたリーダーはどうやって行動を促すか/サイモン・シネック（日本語字幕）