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.
As you can see it turns the lesson flow upside down.
It’s not that the class comes first,
and then the homework, and then the exam.
The first thing that comes is the exam essentially,
followed by these practice problems, which adapt to you,
followed by the class for anything that you don’t know.
The idea is that this should cure boredom at the high end,
and also cure confusion at the struggling end.
I actually started this with
with a brilliant Carnegie Mellon undergraduate student,
and then the two of us built this system together.
But when you start with no resources,
you need to think of ways to
actually generate all of this content,
in a way which doesn’t cost enormous amount of resources.
And we took inspiration from Wikipedia.
Our system aggregates all of the questions and explanations
that anyone in the world might want to contribute,
uses voting like a website called Quora,
in order to find out which content is strong.
And uses statistics, these…
the algorithms to figure out what questions are easy and difficult.
So actually in the end,
it turns out that it sucks in all of this content.
It licenses it all
with the Creative Commons license, like Wikipedia.
and then puts it all across on a platform,
that anyone with a smartphone can use.
As we keep developing these mathematics and algorithms,
our goal is actually 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.