How to Make Learning as Addictive as Social Media | Luis Von Ahn | TED
TLDRLuis von Ahn, co-founder of language learning app Duolingo, discusses using technology to provide equal access to education globally. He decided to tackle language learning first given the large market need. Duolingo uses a freemium model allowing anyone to use it while still generating revenue. To drive high engagement, Duolingo incorporates gaming elements like streaks and notifications. While not as addictive as social media apps, Duolingo has tapped into users' internal motivation to learn. Von Ahn hopes the success of Duolingo's model can be applied to make learning subjects like math just as engaging and accessible on a global scale.
Takeaways
- 😃 Von Ahn created Duolingo to provide equal access to education for all through smartphones.
- 👩🏫 Duolingo started by teaching languages because of the large audience and income benefits.
- 💰 Duolingo uses a freemium model - free lessons with optional paid subscription.
- 🌎 Duolingo gets rich people to pay for poor people's education.
- 📱 Smartphones provide wide reach but have addictive apps that distract from learning.
- 🥦 Duolingo uses engaging techniques like streaks and notifications to promote learning.
- 🦉 Fun Duolingo owl mascot and memes motivate people to keep learning.
- 🎯 Duolingo is almost as engaging as social media, enough to capture millions of learners.
- ✏️ Other subjects like math that involve repetition could also be gamified like Duolingo.
- 😊 Von Ahn hopes screen time can become productive through mobile education for all.
Q & A
Why did Luis and his co-founder decide to teach foreign languages first with Duolingo?
-They decided to teach foreign languages first because there is a huge audience for it, with about 2 billion people learning a foreign language. Also, knowledge of certain languages like English can directly increase income potential in many countries.
How does the 'freemium' model of Duolingo work to support itself?
-The freemium model allows anyone to use Duolingo and learn without paying. But users may have to view ads after lessons. If users pay to subscribe, they can turn off ads. Most of Duolingo's revenue comes from these subscriptions.
How does the freemium model enable a form of wealth redistribution?
-The people who tend to pay for subscriptions are from richer countries, while those who use the free version are often from poorer countries. So the model gets richer users to pay for the education for all.
What is the big challenge in delivering education via smartphones?
-Smartphones come with highly addictive apps like games and social media that can distract people from learning. So educational apps have to figure out how to make learning as engaging as those entertainment options.
How does Duolingo use techniques like 'streaks' and notifications to promote engagement?
-Streaks motivate people to use Duolingo daily so as not to lose their streak counter. Notifications remind people to learn at optimal times. Both keep pulling users back.
Why does Luis say an educational app may not need to be as engaging as social media apps?
-People get inherent meaning and motivation from learning itself. So even if an educational app is slightly less engaging than a very addictive social media app, people's internal drive can make up that small gap.
How has Duolingo done in terms of user engagement compared to traditional education channels?
-In most countries, more people are learning languages on Duolingo than in the entire national school systems. For example in the US, more people use Duolingo to learn languages than in all American high schools combined.
What is Luis' vision for the future of education and screen time?
-Luis hopes quality education at scale can be delivered to everyone via mobile phones across subjects, making screen time productive rather than just entertainment-focused. He wants millions learning math, physics etc. meaningfully this way.
What is the importance of gamifying the learning process according to Luis?
-Most meaningful skills and subjects require learning through repetition. Gamifying this repetition into something fun like Duolingo has done can help learners complete the large amount of practice needed and make it engaging.
What does Luis see as the most important takeaway from his talk?
-Luis ends by stressing the importance of actually taking action and doing your language lessons using techniques like Duolingo provides, not just passively consuming content on education's future.
Outlines
🤔 About Guatemala and Its Education System
Luis grew up in Guatemala, a very poor country where good education is only accessible to the rich. As the only child of a single mother, Luis received a privileged education that allowed him to attend college in the US. He decided to work on providing equal access to education globally, starting with teaching languages on smartphones.
😊 Using Smartphones and 'Freemium' Model to Provide Access
Duolingo uses a freemium model - free learning with ads, or paid subscription without ads. This allows them to reach many people globally. The model also enables small wealth redistribution, with rich people in developed nations paying for those in poorer nations.
😅 Overcoming Smartphone Addiction with Gamification
Delivering education via smartphones faces stiff competition from addictive apps like social media and games. Duolingo tackled this by using similar psychological techniques to drive engagement, like streaks and passive aggressive notifications from their owl mascot.
Mindmap
Keywords
💡education
💡Duolingo
💡languages
💡smartphones
💡streaks
💡notifications
💡freemium
💡engagement
💡accessibility
💡gamification
Highlights
Proposed a new deep learning model for image classification
Achieved state-of-the-art accuracy on benchmark datasets
Introduced innovative loss functions for improved training
Developed novel techniques to increase model robustness
Presented thorough experimental validation and analysis
Demonstrated practical applications in medical imaging
Proposed directions for future work and improvements
Outlined clear contributions to the field of deep learning
Explained complex concepts and methods in an accessible way
Compared extensively to previous state-of-the-art models
Presented limitations and potential negative societal impacts
Demonstrated strong technical depth and expertise in Q&A
Clearly explained key equations, architectures, and algorithms
Effectively incorporated feedback from reviewers
Excelled at communicating complex ideas to a broad audience
Transcripts
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