Why the best learners talk to themselves | Tania Lombrozo

0:02Tania Lombrozo: You're listening to TED Talks Daily, where we bring you new ideas to spark your curiosity every day. I'm your host, Elise Hu. With tools like the Internet and AI at our fingertips, learning should be easier than ever, right? And yet cognitive scientist Tania Lombrozo says it often isn't. In fact, she says that all the information we now have almost instant access to might actually be getting in the way. And more information can make learning harder rather than easier. We run the risk of information overwhelm. Part of the problem is that we tend to approach learning by looking outside of ourselves for more information.

0:44But that can just exacerbate the overwhelm.

0:47Tania Lombrozo: In her talk, Tanya makes a counterintuitive case that the best place to start learning isn't on the web or in a search bar or a chat bot, but in your own head. She calls it learning by thinking, and it starts by explaining things to yourself out loud the way a programmer might talk through a problem with a rubber duck on their desk. Try it, she says, and you'll often discover you understand less than you assumed. I suspect that all of us have had an experience like this one, an experience of trying to explain something and realizing in the course of doing so that we understand much less than we thought we did.

1:26It's a phenomenon called the illusion of explanatory depth.

1:31Tania Lombrozo: That's not a bad thing, though. This act of self-humbling actually sets you up to be a better student. It creates a foundation to build off of. Today, Tanya shares the science behind why explaining things to yourself in your own words makes you a better learner and how, in an age of endless information, the smartest first step might be to log off and look inward instead. That's coming up right after a short break.

2:02Tania Lombrozo: This message is brought to you by Apple Card. Ah, fall, that cozy season where we swap the swimwear for sweaters and sunnies for scarves. But before the Halloween decorations are put away or the Thanksgiving table has been set, there's already holly jolly music playing in the grocery store, reminding you that the year is coming to a close. Time to kick end of year into high gear. When you use Apple Card with Apple Pay, you earn 2 % daily cash back on all purchases, including food, decorations, gifts, and more. Get a head start on your end-of-year purchases. Apply for your Apple Card in the Wallet app on your iPhone today.

2:40Tania Lombrozo: And start using it right away with Apple Pay. Subject to credit approval, Apple Card is issued by Goldman Sachs, Bank USA, Salt Lake City Branch, Terms and More at AppleCard.com. This episode is brought to you by Walmart Business. The best leaders might tell you the work that moves an organization forward doesn't happen in spreadsheets or supply chain emails. It happens when you have the space to think big. That's the idea behind Walmart Business. It's built to take the friction out of running an organization so your team isn't losing hours to procurement logistics when they could just be focused on the problems that actually matter.

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3:59Tania Lombrozo: That's what you'll hear on Season 6 of Planet Visionaries, stories from the explorers, scientists, and conservation leaders whose work addresses research, biodiversity, and conservation issues in specific locations. Planet Visionaries, hosted by environmental advocate and professional climber Alex Honnold, brings you real stories of discovery, determination, and research and initiatives relating to environmental change. In partnership with the Rolex Perpetual Planet Initiative, this is Planet Visionaries. Listen or watch wherever you get your podcasts.

4:35Tania Lombrozo: And now, our TED Talk of the day. Software engineers have a delightful practice called rubber ducking. When they run into a problem with their code, they'll explain it to a rubber duck. They'll work step by step, line by line. and some of the time, they'll learn something new. But how can this work? The ducks don't talk back, so the programmers are explaining to themselves they're not getting any new information. And yet, something about this process helps them learn. Rubber ducking is an example of what I call learning by thinking. And understanding how learning by thinking works is the key to becoming a better learner.

5:32Now, most of us want to be better learners. That's because we want to make our minds better, more effective, and more informed. But learning can be hard. And in the years ahead, we'll have access to more and more tools and to more and more information through the internet and social media and AI. and more information can make learning harder rather than easier. We run the risk of information overwhelm. Part of the problem is that we tend to approach learning by looking outside of ourselves for more information. But that can just exacerbate the overwhelm. Instead, we could be learning by thinking.

6:22We could be starting with the information we already have. I'm a cognitive scientist, and I've been studying learning for over 25 years. One thing I've come to appreciate is that our minds are richer and deeper than we often give them credit for. In fact, our minds contain vast repositories of knowledge, knowledge that's contained in our memories and our skills. Learning by thinking is the process of tapping into that knowledge to become a better learner. To give you a sense for learning by thinking in action, I'd like to ask you a few questions. As soon as you have an answer, please raise your hand.

7:07You ready? How many windows are along the front of your house or apartment?

7:23What is the fifth letter of the alphabet?

7:32Is the letter Z on the left or the right side of a typical keyboard?

7:45I'll bet that many of you didn't know the answers to these questions immediately. But you had the knowledge you needed to figure them out. You could use your visual memories to count the number of windows along the front of your home. You could use your auditory memories to figure out that E is the fifth letter of the alphabet. and you could use your motor skills to figure out that the letter Z on the left side of a typical keyboard. These simple examples highlight the richness in depth of the knowledge you already have, and they illustrate the process of learning by thinking. But recognizing that you have untapped knowledge is not enough to become a better learner.

8:33That's because you also need to know how to extract that knowledge when you need it. Suppose you decide to bake chocolate chip cookies, but the recipe calls for chocolate chips and for salted butter, neither of which you already have. Fortunately, you can transform that bar of chocolate you do have into the chocolate pieces you need for the recipe, and you can combine unsalted butter with salt to get salted butter. This is probably familiar. When we're cooking, we often transform and combine the ingredients we have to get the ingredients we need. It's just the same for learning. When we're learning by thinking, we transform and combine the information we already have.

9:24To see how this works, consider that information can be represented in all sorts of ways. Until today, you probably represented the windows along the front of your home, not in the form of a single number, but as a series of visual memories. So when you transform and combine those memories to extract a single number, you learn something new. You learn how many windows are along the front of your home. And so you can answer a question that you couldn't answer before. before. That's the magic of learning by thinking. There is a catch, though. Not all learning can be done by thinking alone. If I've never been to your home, I can't think my way to how many windows you have.

10:13I need new information. But asking myself how many windows you have sets me up to learn, so that when I do make it to your home, I know precisely what information to look for. That's why learning by thinking is so often the best place to start. Going back to our chocolate chip cookies, it makes sense to look at the ingredients you have already before you start making a shopping list. Unfortunately, though, when it comes to learning, we don't have a recipe. There's no single strategy for learning that guarantees the best outcome in every case. But there is one strategy that comes close. It's a version of learning by thinking that involves seeking explanations.

11:05In the late 1980s, scientists wanted to understand what it is that differentiates the most successful students from their less successful peers. Even when students have access to exactly the same information, the same textbooks, the same passage of text on an exam. How much they learn can vary enormously. So what sets those best learners apart can't just be the information available outside their heads. It has to be something about what they do with that information. The scientists found that many of the most successful students had something in common. As they studied, they explained to themselves.

11:55They asked themselves questions, and they did their best to offer good replies. They were their own rubber ducks. Since then, lots of studies have found that explaining to yourself can have a dramatic impact on learning across a range of contexts and a range of domains. When children or adults explain to themselves, they tend to learn better and can apply what they learn more broadly than those who don't explain. This is known as the self-explanation effect, and it is a powerful strategy for learning by thinking. Let me give you an example from my own research. It's an example that shows how children can transform the way they represent information by explaining.

12:51Just for fun, we'll illustrate with ducks. I'd like you to imagine a card with two ducks on it. We'll call it the reference card. Now imagine two new cards. One has two frogs. The other has one duck and one fox. you have to choose which of the two new cards goes with a reference card. Take a moment to consider which you would choose.

13:25Most research, including my own, finds that in a case like this one, adults will typically choose the card with two frogs to go with a card with two ducks. That's because they don't only represent the cards as having a frog and a frog and a duck and a duck. They also represent them as having the same objects and the same objects. When you represent the cards in this way, it's natural to pair the two sets of matching objects together. So what about kids? Five - and six-year-old children will typically choose the card with one duck and one fox to go with a card with two ducks. That's because they represent the reference card as having a duck and a duck.

14:18So a card with one duck on it will be more similar to it than a card with no ducks at all will. Children do this even when they're shown plenty of examples to make it clear that in this task, the right answer is the adult pattern of matching same with same. But in one of our studies, we were able to make five - and six-year-old children think like adults by prompting them to explain. After seeing examples equivalent to the card with two frogs being paired with a card with two ducks, we prompted half the children to explain why those cards went together. We didn't give them any feedback, so they didn't have any new information.

15:07Yet those kids who explained went on to pair new sets of cards just like adults, matching same with same. By explaining, they changed the way they represented the information to solve the task. Explaining has another remarkable property. It's one I've hinted at already. Explaining sets you up to learn. My friend Roxanna has a young son who asked her one day how tornadoes start. She'd taken a class on climate and natural disasters in college, so she thought she could explain it pretty well. She started to describe how there's a difference in pressure, and then she drew a blank. What sets it off?

15:55She didn't know. How exactly does low pressure produce a funnel? She couldn't say. She told me that she realized she knew nothing. I suspect that all of us have had an experience like this one. An experience of trying to explain something and realizing in the course of doing so that we understand much less than we thought we did. It's a phenomenon called the illusion of explanatory depth. And this illusion points to another reason why it's so valuable to start the process of learning from within with the information we have already. When we start to transform and combine what we know, or what we think we know, to craft an explanation, we often uncover gaps that point us to the information we're missing.

16:57So we know what questions to ask and how to connect the answers to what we know already. By trying to explain, Roxanna identified a gap, something she needed to know, how it is that low pressure relates to a tornado's funnel. She knew what needed to go on her information shopping list. Knowing what we're missing, what to look for, can be a first step in navigating information overwhelm. That's crucial because in the years ahead, that overwhelm will only become worse. Tools for getting and synthesizing information will be all the more pervasive, and we'll be tempted to solve problems by turning first to the information available outside our heads.

17:53We'll be tempted to rely on AI-generated responses to our search queries, and on the explanations we can get from chatbots. These are incredible tools, but they shouldn't replace learning by thinking. If we don't start with the information we have already, we outsource the process of transforming and combining that information that sets us up to seek the right information and to make sense of that information when we get it. We become poor at policing the boundaries between what we know inside our heads and what we merely have access to outside them. We fall prey to illusions of understanding.

18:43But now you know how to break free from those illusions by seeking explanations. When you explain to yourself, you transform and combine the information you have to answer new questions. When you explain to yourself, you're more likely to recognize what it is you don't know. And so you know what to look for when it's time to shift from learning by thinking to learning from new information. Unfortunately, learning by thinking will not make learning easy. But it means your effort isn't wasted. It gives you a path through information overwhelm to insight. And learning by thinking won't eliminate the need for new information, at least in lots of cases.

19:35But it helps you know where to look. It helps you know what you're missing. And what to do with new information when you get it. So to be a better learner, don't start with the information outside your head. Look inside first. Take a moment to ask yourself questions, to explain to yourself. Be your own rubber duck. Thank you.

20:18Tania Lombrozo: That was Tanya Lombroso at TEDx New England in 2025. If you're curious about TED's curation, visit ted.com slash curation guidelines. And that's it for today. TED Talks Daily is a podcast from TED. This episode was fact-checked by the TED Research Team and produced and edited by our team, Martha Estefanos, Oliver Friedman, Lucy Little, Emma Taubner, and Tansika Sunglarnival. Additional support from Daniela Ballarezzo, Christopher Faze-Bogan, Valentina Bohanini, Banban Chang, Brian Green, and Lainey Lott. Learn more at podcasts.ted.com. I am Elise Hu. I'll be back tomorrow with a fresh idea for your feet.

21:00Tania Lombrozo: Thanks for listening.

21:10This episode is sponsored by Ashby.

21:12Tania Lombrozo: Every talk you hear on this show started as an idea, and every idea that actually gets built needs a team. Today's sponsor, Ashby, is the software that supports hiring for those ambitious teams. Ashby is the all-in-one recruiting platform used by the teams at Lovable, Notion, Plaid, and Clay. If you wish that AI could help you move faster through scheduling and scorecards, that you could find that silver medalist candidate from 18 months ago in a few seconds, or that you had better visibility into the state of your candidate pipeline, Ashby is for you. See why over 80 % of Forbes' top AI companies choose Ashby to hire the best talent.

21:49Tania Lombrozo: And visit www.ashbyhq.com slash TED.

21:57Tania Lombrozo: This episode is sponsored by Capital One. Capital One's tech team isn't just talking about multi-agentic AI. They already deployed one, Chat Concierge, for car shopping. Their tech team built in self-reflection with live API checks to help buyers find a car they love. That's how they stack. That's technology at Capital One. Hi there, it's Adam Grant from Ted's Rethinking Podcast, and this episode is brought to you by ServiceNow. I get to spend my days studying how people think and what it actually takes to change our minds. It's work I find deeply meaningful. But even in meaningful work, there's still busy work.

22:33Tania Lombrozo: The admin, the repetitive processes, the invisible load that pulls attention away from what really matters. That's where ServiceNow's AI specialists come in. They don't just tell you what you should do about your busy work. They actually do it. Start to finish. Cases closed. Requests handled. No extra work for you. To learn how to put AI to work for people, visit servicenow.com.