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Language for presentations Some formulaic phrases
On this page you will find some language for presentations, also known as 'signpost' phrases. Many of these are similar to (or the same as) the lecture cues a lecturer uses. They are another example of the formulaic language used in academic contexts. You do not need to learn all of these phrases. Your basic aim is to be able to use at least one phrase for each function (e.g. expressing purpose and showing the structure in the introduction , using transitions between sections, referring to visual aids , concluding ).
How many more you learn after this is up to you. Presentations usually have many visual aids and transitions, so it would be useful to learn two or three different phrases for these functions. On the other hand, you will only state the purpose once in a presentation, so one phrase is enough for life!
The introduction is a crucial part of any presentation. There are many functions which you need to achieve:
- greet the audience
- express your purpose
- give the structure
- give the timing
- handle questions
Phrases for all of these are given in the box to the right.
Greeting the audience
- Good morning/afternoon, ladies and gentlemen.
- Good morning/afternoon, everyone.
Expressing the purpose
- My purpose/objective/aim today is...
- What I want to do this morning/afternoon/today is...
- I'm here today to...
Giving the structure
- This talk is divided into four main parts.
- To start with/Firstly, I'd like to look at...
- Then/Secondly, I'll be talking about...
- My fourth point will be about...
- Finally, I'll be looking at...
Giving the timing
- My presentation/talk/lecture will take/last about 20 minutes.
- At the end of my talk, there will be a chance to ask questions.
- I'll be happy to answer any questions you have at the end of my presentation.
It is important to be able to refer to your visual aids appropriately. Some useful phrases for visuals are shown to the right.
- As you can see here...
- Here we can see...
- If we look at this slide...
- This slide shows...
- If you look at the screen, you'll see...
- This table/diagram/chart/slide shows...
- I'd like you to look at this...
- Let me show you...
- Let's (have a) look at...
- On the right/left you can see...
A vital part of any presentation is 'transitioning' (moving on) to a new section. Why is this so crucial? Mainly because of the difference between listening and reading. When you are reading, you can easily see where one section (or paragraph) ends, and another begins. This is not true when you are listening. To help with this, good academic speakers, whether in presentations or lectures , give cues to signal the end of a section. This helps the listener understand the structure and follow the main points.
Some useful transition phrases are shown to the right.
- Let's now move on to/turn to...
- I now want to go on to...
- This leads/brings me to my next point, which is...
- I'd now like to move on to/turn to...
- So far we have looked at... Now I'd like to...
There are some other phrases which are useful in a presentation. These include giving examples, summarising a point or section, and making a digression.
- Let me give you an example...
- for instance...
- A good example of this is...
- What I'm trying to say is...
- Let me just try and sum that up before we move on to...
- So far, I've presented...
- I might just mention...
The conclusion, like the introduction, has several functions which you need to achieve:
- sum up the main points of the presentation
- conclude (by giving a 'take-away' message)
- close (by thanking the audience)
- invite questions
- Summing up...
- To summarise...
- So, to sum up...
- To recap...
- Let me now sum up.
- Let me end by saying...
- I'd like to finish by emphasising...
- In conclusion I'd like to say...
- Finally, may I say...
- Thank you for your attention/time.
- Thank you (for listening/very much).
- If you have any questions or comments, I'll be happy to answer them now.
- If there are any questions, I'll do my best to answer them.
- Are there any more questions?
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Below is a checklist for presentation language. Use it to help you prepare. You can download a copy of the checklist from the speaking resources page .
Read more about body language in the next section.
- Body language
Read the previous article about presentation structure .
Author: Sheldon Smith ‖ Last modified: 10 January 2022.
Sheldon Smith is the founder and editor of EAPFoundation.com. He has been teaching English for Academic Purposes since 2004. Find out more about him in the about section and connect with him on Twitter , Facebook and LinkedIn .
The language for presentations involves common 'signpost phrases' which help understand the structure.
The structure of a presentation is straightforward, with introduction, main body, conclusion, and Q&A.
Taking part in academic discussions increases your understanding and challenges your ideas, and may form part of your assessment.
Agreeing and disagreeing in academic discussions is always done politely, often using certain common phrases.
Asking for and giving opinions is important if you want to express your ideas and have a voice in discussions.
Visual aids such as PowerPoint and handouts, help your audience to follow your spoken presentation.
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The power of language: How words shape people, culture
Speaking, writing and reading are integral to everyday life, where language is the primary tool for expression and communication. Studying how people use language – what words and phrases they unconsciously choose and combine – can help us better understand ourselves and why we behave the way we do.
Linguistics scholars seek to determine what is unique and universal about the language we use, how it is acquired and the ways it changes over time. They consider language as a cultural, social and psychological phenomenon.
“Understanding why and how languages differ tells about the range of what is human,” said Dan Jurafsky , the Jackson Eli Reynolds Professor in Humanities and chair of the Department of Linguistics in the School of Humanities and Sciences at Stanford . “Discovering what’s universal about languages can help us understand the core of our humanity.”
The stories below represent some of the ways linguists have investigated many aspects of language, including its semantics and syntax, phonetics and phonology, and its social, psychological and computational aspects.
Stanford linguists and psychologists study how language is interpreted by people. Even the slightest differences in language use can correspond with biased beliefs of the speakers, according to research.
One study showed that a relatively harmless sentence, such as “girls are as good as boys at math,” can subtly perpetuate sexist stereotypes. Because of the statement’s grammatical structure, it implies that being good at math is more common or natural for boys than girls, the researchers said.
Language can play a big role in how we and others perceive the world, and linguists work to discover what words and phrases can influence us, unknowingly.
How well-meaning statements can spread stereotypes unintentionally
New Stanford research shows that sentences that frame one gender as the standard for the other can unintentionally perpetuate biases.
Algorithms reveal changes in stereotypes
New Stanford research shows that, over the past century, linguistic changes in gender and ethnic stereotypes correlated with major social movements and demographic changes in the U.S. Census data.
Exploring what an interruption is in conversation
Stanford doctoral candidate Katherine Hilton found that people perceive interruptions in conversation differently, and those perceptions differ depending on the listener’s own conversational style as well as gender.
Cops speak less respectfully to black community members
Professors Jennifer Eberhardt and Dan Jurafsky, along with other Stanford researchers, detected racial disparities in police officers’ speech after analyzing more than 100 hours of body camera footage from Oakland Police.
How other languages inform our own
People speak roughly 7,000 languages worldwide. Although there is a lot in common among languages, each one is unique, both in its structure and in the way it reflects the culture of the people who speak it.
Jurafsky said it’s important to study languages other than our own and how they develop over time because it can help scholars understand what lies at the foundation of humans’ unique way of communicating with one another.
“All this research can help us discover what it means to be human,” Jurafsky said.
Stanford PhD student documents indigenous language of Papua New Guinea
Fifth-year PhD student Kate Lindsey recently returned to the United States after a year of documenting an obscure language indigenous to the South Pacific nation.
Students explore Esperanto across Europe
In a research project spanning eight countries, two Stanford students search for Esperanto, a constructed language, against the backdrop of European populism.
Chris Manning: How computers are learning to understand language
A computer scientist discusses the evolution of computational linguistics and where it’s headed next.
Stanford research explores novel perspectives on the evolution of Spanish
Using digital tools and literature to explore the evolution of the Spanish language, Stanford researcher Cuauhtémoc García-García reveals a new historical perspective on linguistic changes in Latin America and Spain.
Language as a lens into behavior
Linguists analyze how certain speech patterns correspond to particular behaviors, including how language can impact people’s buying decisions or influence their social media use.
For example, in one research paper, a group of Stanford researchers examined the differences in how Republicans and Democrats express themselves online to better understand how a polarization of beliefs can occur on social media.
“We live in a very polarized time,” Jurafsky said. “Understanding what different groups of people say and why is the first step in determining how we can help bring people together.”
Analyzing the tweets of Republicans and Democrats
New research by Dora Demszky and colleagues examined how Republicans and Democrats express themselves online in an attempt to understand how polarization of beliefs occurs on social media.
Examining bilingual behavior of children at Texas preschool
A Stanford senior studied a group of bilingual children at a Spanish immersion preschool in Texas to understand how they distinguished between their two languages.
Predicting sales of online products from advertising language
Stanford linguist Dan Jurafsky and colleagues have found that products in Japan sell better if their advertising includes polite language and words that invoke cultural traditions or authority.
Language can help the elderly cope with the challenges of aging, says Stanford professor
By examining conversations of elderly Japanese women, linguist Yoshiko Matsumoto uncovers language techniques that help people move past traumatic events and regain a sense of normalcy.
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25 English Presentation Phrases to Impress Your Audience
Does giving a presentation make you feel a little nervous?
Well, you’re not alone.
According to Forbes , giving a presentation makes 80% of us feel nervous !
The good news is that feeling nervous might be a good thing. This feeling pushes us to prepare ourselves better, and as long as you’re well prepared, you’ll do just fine.
So then, let’s take a look at how we can prepare ourselves to give amazing presentations in English. Today, we’re going to focus on the business English phrases you can count on (depend on) to make your presentation go more smoothly from start to finish.
But first, here are some tips to use when preparing for your presentation.
Download: This blog post is available as a convenient and portable PDF that you can take anywhere. Click here to get a copy. (Download)
Greeting Your Audience
You’re now standing in front of your audience. Before you begin your presentation, start by greeting your audience, welcoming them to the event and introducing yourself.
1. Good morning/afternoon/evening, everyone.
2. welcome to [name of event]..
Sample sentence: Welcome to our 3rd Annual Sales Leadership Conference.
3. First, let me introduce myself. I am [name] from [company].
Beginning your presentation.
After you have given an introduction, you are ready to begin speaking about your topic. Use these phrases to get started.
4. Let me start by giving you some background information.
Use this phrase to give your audience a brief overview of the topic you’ll be discussing. This is a good way to give them an idea of what’s going on and to bring them up to date.
5. As you’re aware, …
If you’re bringing up a topic that your audience already knows about or is aware of, then you can use this phrase to introduce this known topic.
Sample sentence: As you’re aware , the CEO of DHL Express has often said that globalization is here to stay.
Transitioning to the Next Topic
Before you move on to your next point, be sure to make it clear to your audience that you’re now starting a new topic. Let them know exactly what that new topic will be. The two phrases below are very similar in meaning, and they can both be used for transitions.
6. Let’s move on to…
Sample sentence: Let’s move on to our second sales strategy.
7. Turning our attention now to…
Sample sentence: Turning our attention now to the results of our 2016 customer survey.
Providing More Details
Use these phrases to tell your audience that you’ll be giving them a more detailed explanation of the topic. Both the words ‘expand’ and ‘elaborate’ mean to explain more fully.
8. I’d like to expand on…
Sample sentence: Now I’d like to expand on my point about increasing our market share.
9. Let me elaborate further.
Linking to another topic.
When making reference to a point you made earlier, or to remind your audience about something you said before, use these phrases to that link.
10. As I said at the beginning, …
This phrase lets you remind your audience about a point you made earlier. It can also be used to emphasize a point or theme.
Sample sentence: As I said in the beginning , we’ll see an increase in profit if we follow these five steps.
11. This relates to what I was saying earlier…
This phrase will help you make connections between ideas in your presentation. It shows that two different ideas are connected.
Sample sentence: This relates to what I was saying earlier about increasing production to meet the year-end demand.
12. This ties in with…
Sample sentence: This ties in with the way we’ve been doing business for the past 20 years.
Emphasizing a Point
Use these phrases to draw attention to an important point that you want your audience to note.
13. The significance of this is…
The word “significance'” is similar in meaning to “importance.”
Sample sentence: The significance of this is , if we complete this project on schedule, we’ll have more people available to work on the next project.
14. This is important because…
Sample sentence: This is important because any marketing effort we put in now will help to boost demand for our products in the long run.
15. We have to remember that …
Sample sentence: We have to remember that people are our most important resource.
Making Reference to Information
Very often, you may need to support your discussion points by drawing attention and making reference to information and data from studies, reports and other sources.
16. Based on our findings, …
Sample sentence: Based on our findings, 74% of our market is made up of teenagers who find our clothing line stylish and upbeat.
17. According to our study, …
Sample sentence: According to our study, 63% of working people in this city go directly to the gym after work.
18. Our data shows …
Sample sentence: Our data shows that more than 23% of men in this town who used to drive to work now prefer to save money and the environment by cycling instead.
To present a clearer picture of your point, you may show your data, information or examples in the form of visuals such as charts, tables and graphs.
19. I’d like to illustrate this point by showing you…
The word “illustrate” means “show,” usually with examples, data or visuals.
Sample sentence: I’d like to illustrate this point by showing you a chart of the number of people in each age group who prefer to shop online.
20. This chart shows a breakdown of …
A “breakdown” refers to the detailed parts or figures that make up the total picture. A breakdown is often used in a presentation to show all the smaller parts behind something bigger.
Sample sentence: This chart shows a breakdown of the ingredients we use in our gluten-free products.
Restating Your Point
Sometimes in order to emphasize your point, you have to state it in a way that’s easier for your audience to understand and remember. This often involves rephrasing, simplifying or clarifying your point.
21. In other words, …
Use this phrase to rephrase or reword your point in another way.
Sample sentence: In other words , we need to change our current design to make it more attractive to older children.
22. To put it simply, …
Use this phrase to simplify points that are complex or difficult to understand.
Sample sentence: To put it simply , we’ll need you to work harder at making this launch a success.
23. What I mean to say is …
Use this phrase to explain your point in a way that’s easier for your audience to understand.
Sample sentence: What I mean to say is that we need to change the way we market our products.
Concluding Your Presentation
This is the very end of the presentation. You have said everything you need to say, and now you need to finish it nicely. You may also have some time for questions. If there is time for questions, invite your audience to ask any questions they have.
24. In conclusion, let me sum up my main points.
As part of your closing statement, “sum up” (summarize, state briefly) your speech by mentioning the main points of your speech.
25. Thank you for your attention. Now I am happy to answer any questions you might have.
End your presentation by thanking your audience and offering to answer their questions.
The Top 3 Tips for Preparing Your Business Presentation in English
1. have a plan.
Always have a plan. Spend some time thinking about not only what you’re going to say but how you’re going to say it.
If English isn’t your native language, it’s very important that you think about what language you’re going to be using. Think about all the vocabulary, phrases and grammar that will make your message clear and easy to understand.
What are the big ideas you want to explain for your presentation? Which words will express these ideas best? I recommend:
- Have a clear goal in mind to help you stay on track and be logical. Whenever you feel lost during the presentation, just remember this clear, main goal. An example of a goal could be to convince potential clients to work with you. Whenever you don’t know what to say next, remember to focus on the advantages you want to present and on examples of what you did in the past to deserve their trust. Encourage them to ask you questions related to this goal.
- Research content. If you know your facts, you already have the core of your presentation prepared. Write these facts down on topic cards, give out handouts (papers) with important information or include them on your PowerPoint slides.
- Prepare the delivery. Rehearse giving the presentation several times. Some people like recording themselves, others prefer practicing in front of a mirror or having friends listen to them while presenting. Choose the method that works best for you.
- Decide whether you are going to read or speak freely. Reading can sound unnatural, but you can use certain tricks to avoid this. You can underline important sentences which you can memorize, so that from time to time you can stop reading, say your memorized lines and look at the audience. In this way, reading can be made more natural. Make sure you slow down so that the audience can follow you.
Speaking freely is much better if you can remember everything you want to say, because you will seem more knowledgeable, prepared and confident. However, this can be more stressful.
2. Use Visuals
Using some visuals can make your presentation more entertaining, easier to understand and can get your points across more convincingly. My advice:
- Decide whether you need a PowerPoint presentation or not. Do you have graphs, results or other things like this to show? Then yes, you need one. Are you just telling a story? Then you probably do not.
- Do not fill your slides with too much information. Use a maximum of seven short lines of text—even seven can be too many. Highlight key words so the audience can see the main ideas right away. Use bullet points rather than full sentences.
- If you are presenting graphs or charts , give the audience time to read them. Do not show a huge table of data if they audience will not have time to read and understand it. Make sure you try reading each slide while timing yourself to see how long it takes, so you do not jump to the next slide too early during your presentation.
3. Structure Your Presentation Well
It is a common mistake to give an unclear and unorganized presentation. This happens when the presenter just starts speaking without a clear goal in mind. They might suddenly realize their allotted speaking time has ended, or that the audience is bored because they are not following what is being said. Here’s what you should do instead:
- Decide on three main points (or less) that you want to make. Audiences can’t usually focus on more than three points.
- Tell them from the beginning what points you will be making. Audiences like to know what to expect. Tell them the main goals of your presentation directly in the introduction.
- Presenting main points: firstly, secondly, last but not least
- Making additions: moreover, furthermore, in addition, besides, what’s more
- Making purposes clear: in order to, so as to
- Presenting reasons and causes: on account of, due to, since, seeing that
- Presenting consequences: consequently, as a result, therefore
- Expressing contrast: in spite of, despite, although, even though, however, nevertheless, in contrast, on the contrary
So with this, you’ve mastered the 25 most commonly used phrases used in presentations and my three favorite tips.
Once you learn them, I think you’ll find them very useful to you in any presentation.
Become familiar with them and I promise you’ll feel much less nervous in your next presentation.
And One More Thing...
If you like learning English through movies and online media, you should also check out FluentU. FluentU lets you learn English from popular talk shows, catchy music videos and funny commercials , as you can see here:
If you want to watch it, the FluentU app has probably got it.
The FluentU app and website makes it really easy to watch English videos. There are captions that are interactive. That means you can tap on any word to see an image, definition, and useful examples.
FluentU lets you learn engaging content with world famous celebrities.
For example, when you tap on the word "searching," you see this:
FluentU lets you tap to look up any word.
Learn all the vocabulary in any video with quizzes. Swipe left or right to see more examples for the word you’re learning.
FluentU helps you learn fast with useful questions and multiple examples. Learn more.
The best part? FluentU remembers the vocabulary that you’re learning. It recommends examples and videos to you based on the words you’ve already learned. You'll have a truly personalized experience.
Start using FluentU on the website with your computer or tablet or, better yet, download the FluentU app from the iTunes or from the Google Play store .
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Making a presentation: language and phrases (1)
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This is a list of phrases to help you make a professional presentation in English.
Clear structure, logical progression
Good presenters always use language (sometimes single words, sometimes phrases) which shows where they are in their presentation. These ‘signposts’ make it easier for the audience to:
- follow the structure of the presentation
- understand the speaker more easily
- get an idea of the length and content of the presentation.
We’ve divided the phrases and sentences into sections which follow the logical progression of a well-balanced presentation.
- Good morning and welcome to [name of company, name of conference hall, hotel, etc.].
- Thank you all very much for coming today.
- I hope you all had a pleasant journey here today.
2. Introducing yourself
- My name is Mark Watson and I am responsible for … .
- My name is Mark Watson from [name of company], where I am responsible for … .
- Let me introduce myself; my name is Mark Watson and I am responsible for … .
3. Introducing your presentation
- The purpose of today’s presentation is to … .
- The purpose of my presentation today is to … .
- In today’s presentation I’d like to … show you … . / explain to you how … .
- In today’s presentation I’m hoping to … give you an update on… / give you an overview of … .
- In today’s presentation I’m planning to … look at … . / explain … .
You can also outline your presentation to give the audience a clear overview of what they can expect:
- In today’s presentation I’m hoping to cover three points:
- firstly, … , after that we will look at … , and finally I’ll … .
- In today’s presentation I’d like to cover three points:
- firstly, … , secondly … , and finally … .
4. Explaining that there will be time for questions at the end
- If you have any questions you’d like to ask, please leave them until the end, when I’ll be happy to answer them.
- If there are any questions you’d like to ask, please leave them until the end, when I’ll do my best to answer them.
- Making a presentation: language and phrases (3)
- Making a presentation: language and phrases (2)
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What It Takes to Give a Great Presentation
- Carmine Gallo
Five tips to set yourself apart.
Never underestimate the power of great communication. It can help you land the job of your dreams, attract investors to back your idea, or elevate your stature within your organization. But while there are plenty of good speakers in the world, you can set yourself apart out by being the person who can deliver something great over and over. Here are a few tips for business professionals who want to move from being good speakers to great ones: be concise (the fewer words, the better); never use bullet points (photos and images paired together are more memorable); don’t underestimate the power of your voice (raise and lower it for emphasis); give your audience something extra (unexpected moments will grab their attention); rehearse (the best speakers are the best because they practice — a lot).
I was sitting across the table from a Silicon Valley CEO who had pioneered a technology that touches many of our lives — the flash memory that stores data on smartphones, digital cameras, and computers. He was a frequent guest on CNBC and had been delivering business presentations for at least 20 years before we met. And yet, the CEO wanted to sharpen his public speaking skills.
- Carmine Gallo is a Harvard University instructor, keynote speaker, and author of 10 books translated into 40 languages. Gallo is the author of The Bezos Blueprint: Communication Secrets of the World’s Greatest Salesman (St. Martin’s Press).
Presentations in English
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Blog > English Presentation Structure (Introduction, Closing) & useful Phrases
English Presentation Structure (Introduction, Closing) & useful Phrases
02.21.20 • #powerpoint #presentation #english.
When giving a presentation in english, there are certain guidelines you should follow. Maybe you haven't got a lot of experience presenting - or you would simply like to refresh your already existing knowledge - we're here to teach you the basics about presenting and provide you with a free list of useful phrases and the basic structure you can in your presentation!
The general structure of a presentation is the following:
It is up to you to design these three parts. Using videos or everyday-examples can be a great way to introduce the audience to the topic. The important thing is that you capture the audience's attention from the beginning by making an interesting introduction. The main part is where you present your topic, ideally divided into sections. You can be creative with it - incorporate images, videos, stories or interactive polls . We generally recommend using different kinds of elements, as that makes the presentation more lively. Make sure your main part is well structured, so your audience can follow. In the conclusion, you should give a short summary of the points you made without adding any new information. You can also make an appeal to your audience in the end.
2. Useful Phrases
Here you'll find several phrases that you'll need in every presentation. Of course, you should adapt them and use them in a context that is suitable for your setting. The phrases are divided into subcategories so you can find what you're looking for more easily.
Starting your Presentation
In your introduction, you should:
Welcome your audience
Good morning/afternoon/evening everyone!
Ladies and gentlemen, I welcome you to my presentation about...
I am ... (from company ...) and today I would like to introduce you to the topic of ...
My name is ... and I am going to talk about ... today.
Icebreakers (for audience engagement)
Icebreaker polls are an amazing way to engage your audience instantly. They function as a fun and playful element at the beginning, giving you the perfect start you need to give a successful presentation. Click here to read our detailed post about icebreaker polls!
Mention the presentation topic and the reason for giving the presentation
I am grateful to be here today and tell you you about...
I would like to take this opportunity to talk about ...
I am here today to talk to you about ...
The reason why I am here today to talk about ... is ...
The purpose of this presentation is to ...
My goal today is to ...
Hopefully, by the end of the presentation, you will all know more about ...
Give a short overview of the content
To make it as understandable as possible, I divided my presentation into ... parts. In the first part, I will concentrate on ..., the second part will be about ..., ...
First of all, I will give you a short introduction, then we will move on to ...
... and finally, I will give you some insights to ...
Here are a few phrases that you could use during the whole presentation, but especially in the main part.
Engage your audience
In order to raise the audience's attention and improve their engagement, it is extremely important to make contact with them. A great way to do so is by adding interactive elements such as polls. If you would like to know more about this topic, read our article on How To Boost Audience Engagement . You can also use a software like SlideLizard , which allows you to conduct live polls, do Q&A sessions with your audience, share your resources and many more benefits that take your presentation to the next level.
Please raise your hand if you ...
Have you ever thought about ... ?
I would like to do a poll about ...
Please ask any questions as soon as they arrive.
On one hand, … on the other hand…
Comparing … with …, we can see that…
Clearly, … makes more sense than …
Whereas Option A is …, Option B is …
Making new points
What also has to be mentioned is…
Next, I would like to bring up the topic of…
That being said, now we are going to take a look at…
Let's move on to the next topic.
On the next slide,…
The last thing I would like to mention is…
We made a whole blog post about how to pose questions in your presentation: The Right Way to do a Question Slide .
Talking about images or videos
In this image you can clearly see that ...
We are now going to take a look at a picture/video of ...
I'm going to show you a video by ... about ... now.
I've prepared a video about ...
Talking about statistics and charts
I am now addressing this graph that refers to the results of study XY.
In the graph on this slide, you can see that ...
The average is at ...
This graph clearly shows that the majority ...
According to this graph, the focus should be on ...
What that study tells us for practice is that we should ...
I would like to emphasize the importance of ...
Moreover, it has to be said that ...
I want to stress the importance of ...
We always have to remember that ...
This is of high significance because ...
That part is especially important because ...
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The future of language learning
Cognitive scientist Michael Frank studies differences in how children and AI learn language.
There is a “data gap” between the billions of words ChatGPT has to work with and the millions of words a toddler is exposed to. But, says Frank, children learn in a rich social context that supports their learning. He’s currently conducting the “BabyView Study,” where he puts cameras on young children's heads to help him understand their learning experience, as Frank tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.
Listen on your favorite podcast platform:
Related : Michael Frank , professor of human biology
[00:00:00] Michael Frank: There's been a long tradition of trying to use artificial intelligence and, you know, the precursors to the current systems to try to understand kids learning, with the idea that these could be real scientific models that we could study in detail. And a lot of that history was really cool, but the models we were looking at were not very capable. So suddenly when something like ChatGPT explodes onto the scene, all of a sudden, we're thinking, wow, we could really learn a lot.
[00:00:31] Russ Altman: This is Stanford Engineering's The Future of Everything, and I'm your host, Russ Altman. If you enjoy The Future of Everything, please follow or subscribe wherever you get your podcasts. This will guarantee that you never miss an episode.
[00:00:43] Today, Michael Frank will tell us that both children and AI learn language, but there are big differences and some similarities. It's the future of language learning.
[00:00:55] Before I get started, please remember to follow the podcast if you aren't doing so already. Hit the bell icon if you're listening on Spotify. This ensures that you'll get alerted to all the new episodes and will never miss the future of anything.
[00:01:15] You know, we've all seen the miracle of how children learn languages. As babies, they start out, they babble, they do random things, random noises, but then they start to acquire a few words, they begin to put them together into sentences, and before you know it, they're fluid, they can speak, they can interact. Not only that, they can understand cultural cues, social cues. They even can infer unstated things that are implied by the things that people say to them.
[00:01:46] Well, Michael Frank is a professor of biology at Stanford University and an expert on how children acquire language. He studies not only how they learn the words, but he also studies how they use language to understand the world, the social interactions in the world, and basically how the world works.
[00:02:05] So Michael, you study children and how they learn language. This is particularly interesting these days when we're seeing AI systems also learning language. Do they have anything to do with one another?
[00:02:16] Michael Frank: Absolutely, Russ. Yeah. So, this is fascinating. It's an amazing moment to be in cognitive science of language because we're seeing for the first-time other agents that are at least able to produce grammatical sentences of English and sometimes they even seem to make sense and really, uh, be meaningful in some way. So, uh, there's been a long tradition of trying to use artificial intelligence and, you know, the precursors to the current systems to try to understand kids learning with the idea that these could be real scientific models that we could study in detail. And a lot of that history was really cool, but the models we were looking at were not very capable. So suddenly when something like ChatGPT explodes onto the scene, all of a sudden, we're thinking, wow, we could really learn a lot from what it means to just kind of learn English, learn a natural language from observing enough data. Of course, there are still big gaps.
[00:03:09] Russ Altman: Yeah, so, you know, I have to confess this right at the very start. I have a 16-month-old granddaughter, and so I am watching her in real time, uh, learn language. And I also know a little bit about large language models, and one of the things I know, and I think everybody knows, is they've been exposed to a ton of data. And I watch my granddaughter, and the way she's learning language is not because of being exposed to a ton of data, although it's an extremely rich environment that she's in. So, tell me how you as a kind of professional in this area, how do you try to learn things when the two learning methods seem to be very different?
[00:03:46] Michael Frank: Well, so it creates a really exciting scientific question. We think of this as the data gap between human learners and artificial intelligence. And the big question is what is responsible for that data gap? So, what's the, first of all, you want to quantify the size of the gap. So, something like GPT 3, which is now, you know, several generations back was exposed to 500 billion words. And you're 16-month-old, that's probably heard 15 million words.
[00:04:14] Russ Altman: Wow.
[00:04:14] Michael Frank: So yeah, so it's more data than you might think.
[00:04:18] Russ Altman: Probably mostly from me. I'm sorry to say, but that's a whole different.
[00:04:21] Michael Frank: So yeah, there's a million words a month is a lot of words actually. Does
[00:04:27] Russ Altman: that include repeat words?
[00:04:28] Michael Frank: Oh yeah. So that's, uh, being immersed in this, uh, you know, environment where people are talking to you.
[00:04:35] Russ Altman: Yes.
[00:04:35] Michael Frank: Or around you and you know, that's counting kind of everything. Probably the amount that's actually.
[00:04:41] Russ Altman: Okay.
[00:04:42] Michael Frank: You know, something you could really learn from as a baby, as opposed to your parents talking about the credit card bill is pretty different.
[00:04:47] Russ Altman: Right.
[00:04:48] Michael Frank: But then you mentioned kind of what are the big differences, right? The language that your granddaughter is hearing is social, it comes in this kind of complex context where there's something happening, something being communicated about. It's grounded in the world around her. It's got all kinds of extra multimodal, meaning like lots of different sensory modalities, information. She's got vision, she's got touch alongside the sound.
[00:05:14] Russ Altman: Yeah.
[00:05:14] Michael Frank: Um, so there's lots more richness to what she's experiencing in those millions of words than what ChatGPT gets from its many hundreds of billions.
[00:05:23] Russ Altman: Great. Okay. So, I want to step back because, you know. You were doing this way before ChatGPT came in, and I want to make sure we look at some of the things you're doing. One of your approaches involves lots of data, you know, um, big data approaches. And so, could you tell us about some of the resources that you've set up, and how you use them to learn about, uh, language acquisition?
[00:05:43] Michael Frank: Absolutely. So, uh, despite the fact that, you know, language learning, if you're talking about is a big data problem. A lot of the earlier approaches to studying language were very bespoke, it was studying one child, maybe, uh, somebody keeping a diary or doing an experimental study of 15 kids at the nursery school. And one of the things we've learned is that that kind of small data approach doesn't really work because of the diversity of outcomes for kids even in one culture, and then the vast diversity of the languages and cultures that kids are learning in around the world. So, what I've tried to do is really buildup databases that give us some rich quantitative information about what language learning looks like around the world.
[00:06:25] One of those, our flagship, is called Wordbank where we've got maybe close to 100,000 kids worth of data um, from something like 50 languages or dialects around the world. Uh, and what we've got actually is what parents say about them. So, we've got parents checking off my child knows ball and dog and, uh, cup, but not alligator.
[00:06:46] Russ Altman: Okay.
[00:06:46] Michael Frank: Um, and so for each child, we've got this kind of, uh, holistic assessment by the parents, sometimes many times, sometimes just one time, uh, of what they know, what they're saying and what they, what the parent thinks they understand. Um, and that allows us to look at variation in all sorts of really interesting ways.
[00:07:02] Russ Altman: And the parents are good reporters in your experience? Like there's not a lot of, uh, I don't know, projection of their hopes and dreams of the child onto your data set.
[00:07:11] Michael Frank: Well, um, so this is part of the craft of, uh, kind of doing good research in this area. You don't say, hey, um, you know, how brilliant is your child? Check very brilliant, exceedingly brilliant, or, you know, off the charts and also adorable. Um, you know, you, you've got, uh, what we do is we ask questions about observed behaviors that are happening right now, not retrospectively. And we do assume there are some biases involved here. So, there are certain things we have to take with a grain of salt, but in general, people don't have a specific bias that their child does or doesn't say alligator.
[00:07:44] Russ Altman: Yeah.
[00:07:44] Michael Frank: They either remember that happening or they don't. And so maybe any individual word is a little noisy. Maybe we're not sure if they actually said, um, you know, cat or not, but averaging over thousands of kids, we can actually get quite a detailed measure and we can learn, you know, unsurprisingly that cat is learned before alligator.
[00:08:04] Russ Altman: And now you mentioned, I think you mentioned that it's almost a hundred thousand kids, and I think you said multiple languages. So, are there differences? Are there easy languages and hard languages to learn? Or for a kid, is it all just like bring it on, I'm going to learn whatever we're talking here.
[00:08:19] Michael Frank: You know, the amazing thing, and I think this is really a discovery. You know, not just by me, but by language acquisition in general, is that kids really can learn? You know, the whole variety of human languages. And that's for an interesting reason. It's because languages are evolved to be learned by kids.
[00:08:35] Russ Altman: Yeah.
[00:08:36] Michael Frank: So, a language can't survive as a language if it's not learnable. So, but, uh, you know, largely the thing that pops out of our research is how consistent the process of learning is across very different languages. Now, of course, the details are different, the words are different, the grammar is different, but the general factors that influence language learning around the globe appear to be quite similar.
[00:08:57] Russ Altman: Very interesting. Now, I don't know if this is science or just something I read in People magazine. But is there a time when the babbling, like, so my 16-month-old granddaughter is babbling shit. There are a few words, but it's mostly about, you know, blah, blah, blah, blah. Do those diverge quickly, and when this child is destined to learn different languages, or is the babbling all kind of sound the same and like, when do they start sounding like the language that they're ultimately going to speak?
[00:09:24] Michael Frank: Yeah, they actually really do kind of start along that path. So, my father-in-law is a speech pathologist, and he loves to say that what Um, babies are doing is playing the instrument, right? The way when you pick up a guitar, you could just kind of go, strum, strum, strum, strum, strum. And you get this kind of the open strings. You don't get music.
[00:09:43] Russ Altman: Yes.
[00:09:43] Michael Frank: But you get something that sounds guitar like. And babies are kind of exploring their vocal instrument, or for sign language, uh, acquiring babies, their manual instrument in kind of the same way. So, you see these language-like elements start to emerge as they figure out, oh, that works. Oh, that sounds kind of like what I'm hearing. Uh, it looks kind of like what I'm seeing in the case of the signs.
[00:10:04] Russ Altman: Great. So that, actually makes, makes really good sense. And I love that analogy to instruments. So, in addition to Wordbank, I'm wondering, you, you made a mention, you made a reference to the fact that when the human kids are learning language, it's a multimodal experience. They're seeing things, they're hearing things, they're learning. And I know you've studied this, the social cues. Um, do you have any, ability to collect that kind of data? Um, I could imagine it would both be useful for you, and it might give the hint to the AI guys about how they might be able to be more efficient in their learning. So, what's the, our, the status of our ability to study these multimodal elements of language learning?
[00:10:42] Michael Frank: Well, creating those kinds of data sets is one of the biggest challenges right now for us Developmentalists. So actually about 10 years ago we started creating a resource that's become very useful. Uh, it's called SAYcam. So, the idea was that we had these for the first time, little cameras that we'd put on kids' heads, and we tried it a bunch in the lab, and it was fun. And then, uh, a couple of parents and I got together. Um, I actually didn't have a kid at that time, that's how long ago it was. And they said, we're going to try this two hours a week, you know, every week from six months until you know, the kid stops wearing it, sometime around two and a half - three. And we created this corpus of videos from the child's own perspective.
[00:11:22] Russ Altman: Wow.
[00:11:23] Michael Frank: And critically, uh, the videos of these parents were developmental psychologists and committed to their craft and were willing to let these sometimes somewhat unflattering videos out, um, in, not in public, but in a research repository for other researchers to use.
[00:11:37] Russ Altman: Yeah.
[00:11:37] Michael Frank: And as a result, there's really exciting research being done with these videos.
[00:11:43] Russ Altman: That is really exciting. So, have we gotten to the point where we can, like, get some preliminary results from that? Or is it still very much in the infrastructure building phase?
[00:11:51] Michael Frank: So, some super cool results are actually coming out really soon, doing machine learning on one kid's experience from this corpus. So, you can really get a deep dive into what you can learn from just a little bit of one child's life.
[00:12:03] Russ Altman: And I can see that it was, it must have been like tracking their head movements, so you can really see where they're focusing.
[00:12:08] Michael Frank: But you know, this was still by machine learning standards, pretty small data. So, we collected 400 hours and that's like about eight or 10 percent of one child's waking hours for one year. And so of course, you know, these greedy AI folks, um, so one of my collaborators, wonderful guy named Dan Yamins came to me and said, you know, this was great, and I'm sure you, it was very hard for you to collect, but could you just do something like 10 times as much? So that's really what we're doing now. We've got this study in progress called the BabyView study uh, which is essentially a baby GoPro. We hooked up a GoPro rig for, um, very small kids. And we're sending these things out, uh, you know, all over California and all over the US, um, and having parents put them on their kids once or twice or even three times a week and gathering these, uh, data that really reflect what the child's experience is like. And so that's going to create, hopefully, you know, once it's done an even more useful resource, both for scientists who want to characterize what do kids see, and also for AI folks who want to train models a bit more baby like than chat GPT.
[00:13:12] Russ Altman: That leads me actually to the next set of questions I wanted to ask, which is like, when you're getting this data, you're going to see what they're looking at and who they're taking cues from. And I know you've looked at, um, you know, language is not just language. It's a social tool. And you've looked at the social development of children. Can you give us some examples of how language acquisition kind of dovetails with the acquisition of social skills and being able to pick up social skills? I actually think this is very important also, because I've heard that people are worried about, um, cell phones and the potential that they're stunting some development of basic human capabilities in terms of social interactions. So, I don't know if that comes up in your work, but is there anything there to say?
[00:13:54] Michael Frank: So just starting out with what, uh, social learning looks like. I mean, if you think of the baby as kind of a code breaker, this is kind of funny. But think about, you know, your granddaughter there sitting on the floor and the parents are talking about the credit card bill. How do you break that code? You've never heard of a credit card bill. You can't see one. It's not there. They're talking really fast. But if you think about, um, now her parents talking to her in a kind of a grounded social interaction, there's toys in front of us. They're giving kind of short, repetitive phrases that are really grounded in something that she's interested in, the toy she's playing with right now.
[00:14:30] Russ Altman: Yes.
[00:14:31] Michael Frank: And you know, that's part of maybe a routine or a game where she can kind of figure out the rules. Um, and they use all these rich cues, like looking at the thing together, they're pointing to it. Um, all of that is going to create a situation where she can break that code. You can figure out what the name of something is, and maybe once you know the name, you can figure out what that word means, like kick the ball, right? So, then you're saying, kick the ball. Yeah, good job. Kick the ball with your foot. Um, so you get this, uh, set of cues that can help you kind of progressively break into more and more of this code when, uh, especially when it's grounded in these kinds of social interactions that follow the child's lead and give them all those social clues and contextual clues.
[00:15:12] Russ Altman: Now, I think you've also done some, what looked like to me, fascinating work that the children actually evaluate, like, how reliable the person who they're interacting with. Like, I'm guessing that mom is rock solid, but other people, it's like, I don't know, I don't know how much I'm going to believe what they're saying. So, um, what have you found about the kid's ability to kind of, I'll use the word decode, like the, um, the, uh, reliability of someone they're interacting with and how much they can really latch on to the words that they're learning. Any surprises there?
[00:15:45] Michael Frank: Yeah, so I mean I don't think we, we think that kids are going around being super skeptical of all the people around them. I'm not going to learn from you, you know. But at the same time, it is really, you know, interesting and useful generally as a social agent who's trying to learn about the world to figure out who to learn from. You know, uh, you want to take lessons with the expert in some sense.
[00:16:03] Russ Altman: Yes.
[00:16:03] Michael Frank: And that can just mean which of your peers is better at this skill or kind of more reliable. And so developmental psychologists often use that idea to kind of figure out what kids know and how actively they're seeking out information. Um, so we did this one study where we looked at, you know, kind of how kids, uh, process uncertainty and we'd put out a ball and a, another toy, you know, whatever, uh, like a box or something. We'd say, okay, look at the ball. And the kid goes, okay, here's the ball. And then you say, uh, and where's the blicket? And the kid looks at you like, huh? Which one's the blicket? You got to tell me here. And so, we actually were studying that huh response to try to figure out if the kids were actively tracking and looking to their social partner for more clarifying information and what they would do. And you know, of course, what they do at different ages changes. Maybe the, the littler kids are just puzzled. The bigger kids may actually ask a question or point to it, um, or make a guess and kind of try to get some affirmations. So, you can really see these active learning strategies where the kids are helping figure out that code by their own actions.
[00:17:09] Russ Altman: You know, I just going back to my situation, you know, as the grandfather, I just spent a lot of time just staring at her. Uh, and it's very clear that her mother and her big brother are two incredibly important sources of information that she tracks noticeably more than everybody else in the room. And so, this kind of all, um, makes sense.
[00:17:31] This is The Future of Everything with Russ Altman, more with Michael Frank next.
[00:17:48] Welcome back to The Future of Everything. I'm Russ Altman and I'm speaking with Professor Michael Frank from Stanford University.
[00:17:54] In the last segment, Michael told us about some of the ways that he is gathering data in order to learn across multiple cultures and geographies how children learn language.
[00:18:05] In this segment, he's going to tell us about an exciting project where he collaborates with people all over the world to increase the size of the database and the ability to quickly test hypotheses about what's universal and what's specific about childhood language acquisition.
[00:18:22] Michael, another project you have is called ManyBabies, which I love the name. Uh, what are the goals of ManyBabies and how is it kind of advancing your research?
[00:18:31] Michael Frank: We are generally interested in trying to understand how child development varies across different cultures and communities and individuals. And, you know, um, if your traditional strategy is studying 16 kids at a nursery school in Palo Alto, you don't get a lot of traction on that kind of topic. So, what we did, uh, you know, starting almost now, you know, seven, eight, nine years ago is sit down with a group of folks interested in this larger scale science and say, how could we distribute the same experiment around the world? How could we get not just a couple of babies, but many babies?
[00:19:05] Russ Altman: Many babies. Gotcha.
[00:19:06] Michael Frank: So, we ended up with this consortium of researchers all over the world. Um, and we decide on something that's really critical, something where we really have a lot of uncertainty about exactly what, uh, babies know, um, or what they can do. And then we create a consensus protocol and experiment often it's as simple as you know, playing babies, infant directed speech like that high squeaky, like, hi, look at me. Do you see this? Um, and then.
[00:19:34] Russ Altman: is that what we call it? That's great. Infant directed speech. I spend a lot of time doing that.
[00:19:38] Michael Frank: Oh yeah. They used to call it motherese, but you know, uh, sometimes dads and granddads are, uh, experts. So, um, our first ManyBabies study was actually studying the global preference of babies for infant directed speech. And the world around babies like it when you talk high and squeaky to them. It catches their attention, they focus longer. Even, you know, if in their culture, they're not hearing a lot of infant directed speech, they still like it. Even if the infant directed speech is in English, and they're not learning English, still sounds kind of appealing to their perceptual system. It draws their attention.
[00:20:11] Russ Altman: So, this is fascinating because there's a whole bunch there. But, um, in terms of the organization, you've basically created a worldwide network where hypotheses can be tested. You all agree to do it. And then, uh, it also sounds very kind of just in the sense of justice. Because you're doing it, not just in an English centric way, but you're learning much more general principles about human language acquisition. So, it sounds great. Who supports this kind of work?
[00:20:36] Michael Frank: Well, you know, to be honest, this is actually one of the projects that I've had the hardest time finding financial support for. Uh, you know, and this is maybe a sad fact about the way that science funding works, right? When you say, okay, I've got a consortium of, you know, top universities in the U. S. that's going to study something. Let's bring it to the National Institutes of Health or the National Science Foundation. But if you say, I want to do, you know, I want to give $3,000 to a lab in, you know, um, in Uganda to, uh, redo this study. It gets a lot harder to find somebody who's willing to send that money, even though it's a tiny amount of money and it makes a big difference to that lab to buy them the monitors and the speakers. This kind of global consortium work where you flexibly send a little bit of money to incentivize a collaboration, it's actually very tough to do. But so much of our work has been volunteer, which says a lot about the, I think the enthusiasm globally for this kind of research.
[00:21:28] Russ Altman: Exactly. No, it sounds great. And it really is a good model. It's obviously a good model for making sure that the findings are generalizable. Okay, just moving to another topic, you write a lot about pragmatics in your work, and sometimes you counter, you use it in distinction to other concepts like vocabulary. So, can you tell me what pragmatics is in language acquisition and in kid's development?
[00:21:52] Michael Frank: Yes, so we've been talking a lot about social cognition and the social use of language. And one of the things about being an adult who uses language all the time is we don't even recognize how much we infer about the social context of language. So, like, for example, if I say, you know, I gave an exam in my class and some of the students passed the test. You jump to the conclusion, well, that must have been a hard exam, not all of them passed the test. I didn't say that, could have been that all of them passed some, actually, even all passed. But so that's an example of a little teeny tiny inference you make, a little jump in logic that you make. And we think of this kind of the advanced mode of, um, you know, solving all these social inference questions that we were talking about with word learning.
[00:22:35] Russ Altman: Yeah.
[00:22:35] Michael Frank: So, what we've been interested in over the past 10 15 years is how those abilities to make little social inferences develop in young children. And a lot of the time what we do is just create kind of more kid friendly ways to ask the question. So instead of talking about some of the teachers passing the test, we say, you know, uh, here's a puppet with a hat and glasses, and here's a puppet with just glasses. And you say, um, okay, my friend has glasses. Which one is my friend?
[00:23:03] And the kids, not so much the three-year-olds, but three-and-a-half-year-olds, four-year-olds, they start to say, oh, glasses and not a hat, they make the inference.
[00:23:12] Russ Altman: I see.
[00:23:13] Michael Frank: And so that's a really kind of fun way to, um, you know, in a kid friendly way look at this little logical leap that they're making.
[00:23:21] Russ Altman: Yes. And I know that, uh, in the AI research community, there's a lot of concern that these systems don't have what people are calling common sense. Uh, which is related, I think, to some of the things you're talking about here, where we have these underlying models of the world that are not ever articulated unless, you know, unless it's the study that you're focusing on. And that can lead to, um, weird behavior from AI that you don't usually get from humans.
[00:23:47] Michael Frank: Yeah, absolutely. And so, kind of at the forefront of AI safety is like, well, okay, the AI should try to infer what you mean and get at your intent rather than at the kind of the literal, uh, meaning. You don't want to say, you know, um, uh, like leave some kind of critical loophole in your instructions to the AI, kind of a la 2001, a space odyssey, right?
[00:24:09] Russ Altman: Yeah. Right.
[00:24:10] Michael Frank: So, it's really important that the, uh, these sorts of agents really be thinking in a charitable way and a human like way about the intentions of the other person who's talking to them. And that's what pragmatics is.
[00:24:21] Russ Altman: Yep, thank you. Okay, so in the last couple of minutes, I want to, this is the segment where I'm going to ask you about like all of these things that parents want to know. Everybody wants their kids to acquire language, they want them to be fluent, they want them to have a big vocabulary. I mean, most people. So, tell me, we always hear that it's important to read to infants. So, it's almost now a truism. Like, I don't know what data this is based on. Is that true? And can you give me a feeling for why it is versus all the other ways you could expose them to language? Like, for example, you could tell me maybe, well, Russ, don't read to a child because it's a two-dimensional book and the world is much richer in three dimensions, and I would rather have them go out and interact with the world.
[00:25:06] So. What about reading to kids? How important is it and why?
[00:25:09] Michael Frank: So, reading to kids is great. It's really fun to read to kids. They like it. It's enjoyable. Uh, and it's also, uh, you know, an important part of setting them up to learn about not just language, but also different kinds of language, right? You get different syntactic structures, you get different ways of describing the world, fiction, nonfiction, and so forth. Um, and if you think about the code breaking challenge that I was talking about.
[00:25:31] Russ Altman: Yeah, yeah.
[00:25:31] Michael Frank: Especially for a little one, a book is a great kind of key to that code. You're really showing them, okay, here's the picture of the thing we're both looking at it. I'm going to name it for you. I'm going to describe it to you. Maybe it's going to be in a memorable rhyme or a song or something like this. So, books are fabulous.
[00:25:47] On the other hand, you know, the biggest thing that I learned about parenting and about, uh, kind of input to kids is a little bit of humility. Like, when you look at these giant databases, the thing that pops out is that kids vary tremendously in their roots into language. Some kids learn very quickly, some kids learn slower. Now, uh, if a kid is way on the slow side, you want to talk to a pediatrician or speech language pathologist and get intervention. But within the normal range, there's a lot of variation, and I think a lot of parents want to just kind of accelerate it, push it forward as fast as possible. But a lot of that is outside of our hands, and so that, you know, the thing that's best for the kid and also for the family is to have fun. You know, read a book if you want to read a book, play with the kid if you want to play with the kid, um, you know, enjoy time together, have that rich social interaction in a way that's fun, and not worry about, you know, the big data problem of shoving more words into their ear.
[00:26:39] Russ Altman: Right. Okay, so forgive me for these next questions, but, uh, how early is it important to expose a baby to language? Uh, I am one of those fathers who spoke to my mother, to my wife's belly during pregnancy because I wanted the kids to recognize my voice. I mean, any science on that?
[00:27:00] Michael Frank: Yeah, so, um, even in utero, uh, there is some auditory learning. There's some classic studies that show, um, sensitivity to voice and to the rhythm of speech, um, really right at birth. So, from, uh, uh, learning before birth. So that's really true. And, um, One of the things that modern developmental methods show us is that even when babies look like they're, you know, not able to talk when they're six, nine months old, you still get these traces of language knowledge that are building up and that, that is really important.
[00:27:32] So it's never too early to interact in this rich social way with language. Um, that doesn't mean you need to read them Anna Karenina. If you want to...
[00:27:40] Russ Altman: Right.
[00:27:41] Michael Frank: If you're already reading Anna Karenina and it sounds fun, go for it, I love the novel. But it can be in a way that's appropriate to your child and to your family.
[00:27:50] Russ Altman: Yes.
[00:27:51] Michael Frank: But it's, you know, it is valuable for the kid.
[00:27:54] Russ Altman: And so finally, what about kids who are learning multiple languages? Uh, either two languages, like, you know, I don't know, Spanish and English or sign language in English. Are there any special considerations or understandings that have emerged from those kids? And I know it's a much smaller numbers perhaps, but it's always fascinating to see kids who are in these environments where they're learning multiple languages simultaneously.
[00:28:18] Michael Frank: Well, it's amazing because it's much smaller numbers in the U.S., but it's probably the modal, it's probably the, you know, the most common way that kids learn in the world. So, actually, bilingualism or multilingualism is really a norm, and the amazing thing is just how easy it is. I guess I like to think about it as like, you know, uh, nobody ever asks, hey, you know, you're riding a bike and learning to swim, but when you're on the bike, don't you, you know, do all this swimming? And you say, no, I'm on a bike. It's in the same way, if you've got contexts that support different languages, kids learn to use those languages in those contexts, and they do it fluidly and seamlessly.
[00:28:54] You know, there's a tiny little, um, measurable, but kind of, we think pretty insignificant delay. And at the point when the kid is figuring out, oh, there are two languages and you've got to use them in these ways.
[00:29:05] Russ Altman: Right.
[00:29:05] Michael Frank: But overall kids really do sort it out in a lot of different situations and they do so without much, uh, you know, without really measurable negative consequences. In fact, with a really huge measurable positive consequence, which is that they learn more languages.
[00:29:21] Russ Altman: So, we, and finally, we all know that kids are amazing at learning languages, especially compared to adults. When does that magical ability to like learn a language, when does it start to taper off and they become more brittle like me, for example?
[00:29:35] Michael Frank: Well, this is fascinating, right? Because, you know, you could go head-to-head with, um, your granddaughter and you'd probably memorize a lot more vocabulary words a lot faster if you, you know, both start learning, you know, Sesotho or something. Um, but what would happen is that you are ceiling out, you top out a little bit sooner because, you know, uh, you start learning these kinds of fixed grammatical rules, maybe your accent never gets that good. And she's going to go slow and steady, but eventually win the race and get a good accent speaking that language and really, um, you know, figure out all those complex endings that go on things.
[00:30:11] So it's less that the ability goes away and more that there are real changes in the way we learn that seem like they're happening gradually, maybe over the course of the teenage years. So, you know, you put an elementary school student in a new language context, and they largely achieve native like proficiency if they're given long enough. But at least by your 20s, that seems to decrease.
[00:30:35] Russ Altman: Thanks to Mike Frank. That was The Future of Language Learning. You have been listening to the Future of Everything podcast with Russ Altman. With close to 250 episodes in our library, you have instant access to lots of good stuff about The Future of Everything.
[00:30:51] If you're enjoying the show and learning something, please rate and review. Why not give us five stars? That'll help us grow, and it'll help others learn about their podcast as well. You can follow me at Twitter or x @RBAltman, and you can follow Stanford Engineering @StanfordENG.
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