Po-Shen Loh is a Princeton-educated mathematician, Carnegie Mellon professor, the head coach of the U.S. International Math Olympiad team, and now he’s adding start-up entrepreneur to his knock-out resume. Loh has created Expii, a math and science education tool that aims to turn every smartphone into a tutor. Loh combines his mathematical expertise with crowd-contributing strategies from sites like Wikipedia and Quora to “deliver free education to all of the world using a system that self-organizes in the same way that mathematics self-organizes from its basic assumptions,” says Loh. He hopes it will bring some equity to U.S. education and be a learning revolution for those who could not traditionally afford a tutor. “The idea is that this should cure boredom at the high end and also cure confusion at the struggling end,” says Loh.
Po-Shen Loh is a Hertz Foundation fellow and recipient of the prestigious Hertz Foundation Grant for graduate study in the applications of the physical, biological and engineering sciences. With the support of the Fannie and John Hertz Foundation, he pursued a PhD in combinatorics at the Pure Math Department at Princeton University.
The Hertz Foundation mission is to provide unique financial and fellowship support to the nation’s most remarkable PhD students in the hard sciences. Hertz Fellowships are among the most prestigious in the world, and the foundation has invested over $200 million in Hertz Fellows since 1963 (present value) and supported over 1,100 brilliant and creative young scientists, who have gone on to become Nobel laureates, high-ranking military personnel, astronauts, inventors, Silicon Valley leaders, and tenured university professors. For more information, visit hertzfoundation.org.
Read more at BigThink.com: http://bigthink.com/videos/po-shen-loh-using-technology-to-educate-the-globe
Transcript: About three years ago I became the national coach of the United States International Math Olympian Team. I was very happy for a day thinking this is very interesting. But the next day I started to think that maybe I should do something with this. And I decided that I wanted to focus not only on training an elite group of students but trying to do as much as I could to boost the baseline mathematics capability in this entire country.
Unfortunately I had no money, no connections and only one person. So the only thing I knew was mathematics, algorithms and this probability and network theory. So after thinking for some time I actually came to an idea which was based on using these core mathematical areas that I’d been working with to actually build a solution for education that could be delivered for free on every smart phone. This is actually the project I’m working on right now called Expii.
Our principle is that actually you could turn that smart phone into a virtual tutor which automates what a person would get if they hired a tutor. It wouldn’t be as good as a tutor, but it could get very close. And if you could deliver a free almost tutor on every smart phone in the United States you might solve equity problems, you might be able to allow everyone, even if they live in a different ZIP Code, to be able to access this tutor, which previously had only been accessible to people who are quite wealthy. Because today the cost of a tutor is in the $30 an hour, $20 an hour, $50 an hour depending on how you look at it. If you can reduce that to zero dollars an hour you would actually open up this accessibility to everyone.
If we realize that what we’re trying to build is this virtual tutor then you actually, again, can start to conceptualize well knowledge happens to be all of these concepts linked together in this network. Then the problem becomes if you have this network how do you mathematically analyze where a person should go next? That can be done by using probability and statistics to find new ways to measure how much each person understands about each concept. Statistics, because the way that one would measure this is by asking them questions.
The experience someone has is they indicate what they want to learn and then the system starts to pitch questions at them, questions that they would need to know how to answer in order to understand what they claim they want to understand. As the questions come, based on people’s responses to the questions, the system adjusts the difficulty of the questions and where the next questions come from in the same way that a human tutor adjusts their line of questioning based on whether a person is successful or not successful at the previous question. If the student reaches a point where they are hopelessly confused, meaning they don’t know how to do this question at all, then the system suggests that maybe they could read some explanations. [transcript truncated]