Hi, I'm Judy Cole, the Executive Vice President
and CEO of the MIT Alumni Association,
and I'm delighted to welcome you to this web production
of the MIT Alumni Association.
Good morning.
I'm so proud to be a member of your community.
I'm proud that I got my PhD at MIT in the 1980s.
I'm proud to be a member of the faculty now.
I'm proud to be part of the mission
that you've heard about this morning in the previous talks
and from President [INAUDIBLE].
And I'm excited that MIT is showing its commitment
to excellence and education for all
by establishing the MIT Integrated Learning Initiative.
The goal of this initiative-- which I've been asked,
and I'm grateful to have the honor to direct--
is to bring the best of science, engineering,
and policy to figure out what works
for learners and education.
There's so much issues in terms of society, economics,
politics about education, where we
can shine the light of science, technology, and policy to make
education better for everybody.
For the superstars at MIT, for the children born into poverty
in this nation and around the world,
for different kinds of learners, for whom
the standard curriculum you heard described--
you know beautiful poetically earlier.
The standard curriculum is not the right curriculum.
We want to revolutionize that by the power
of scientific knowledge.
That's our mission.
I need your help, as MIT does, and the scientists to do this.
So let me give you a couple of examples
of how we think neuroscience, the area I work in,
is starting to give us some ideas about how we can make
education better for everybody at all levels of opportunity,
and from all kinds of different backgrounds,
and individualities.
So here's something.
Imagine you go visit a place like this.
Although, in our boring experiments and imaging,
you're in a tube, in a scanner, and you're
seeing this in your mirror, OK?
And when you have the best learning moments
that you heard described earlier,
sometimes we know we're ready to learn.
That moment you're ready to learn,
and sometimes it's been a tough day,
or the speaker's not that interesting,
or the topic is a little confusing,
and you're not ready to learn.
Are we able to find in the human brain
the moment of learning when you're ready to learn,
or the moment when you're not ready to learn?
And on top of that, can we give you
information when you're ready to learn that you'll remember,
and can we give it a break when you're not ready to learn?
I mean, that would be ideal, right?
If we knew that the information we were conveying,
whether it's orally or digitally,
was arriving in your brain when it's ready to learn or when
it's not ready to learn.
So here's the experiment.
A person is lying in a scanner like this,
and we're watching the natural fluctuations of oxygenation
in their brain that reflects when
different parts of your brain are more active or less active.
You're just laying there doing nothing.
It's sort of like you're in your chairs now,
and we're watching that display over time,
and when a certain part of the--
sorry?
Can you lower the lights?
Can you lower the lights, please?
Do I have the power to do that?
No.
Can somebody lower the lights?
Who has the power to do that?
Thank you very much.
OK, so we're watching these two areas of the brain.
They're in the so-called parahippocampal place
area, part of your gyrus.
We all have them on the left and the right.
And when these areas are either high or low,
as you're just laying there, your brain state
triggers us to present one of these pictures
like you just saw.
And so when it's high or low.
And then when you're done with that,
we give you a test of your memory for the information,
and what find is this.
If we send in the information when
your brain is ready to learn, you remember it better than
if we send in the information when your brain was not
ready to learn.
So we know we're not going to roll in multi-ton, multimillion
dollar scanners into every classroom in the United States.
We know we can't do that, but we know now
with some scientific evidence that there's
a signal in your brain when you're ready to learn,
and when you're not ready to learn,
and we see whether we can exploit that in terms
of broad education application.
We could not have known this without this technology,
and we want to use this to create
inspirational effective learning for all students,
and it's why this situation is possible.
Another thing we can look at is brain structure,
and so let me just give you a moment's video.
So we're looking at an individual's brain
anatomy, gray matter and white matter as we go from one ear
to the other.
And then we can measure the cortical thickness.
So the surface of your brain has six layers
of neurons that compute much of what are
the intelligence of humanity--
language, problem solving, thinking, and so on.
And we can measure the thickness of that,
which is a very coarse neuroscience measure,
but it's a measure we can take.
And then we can look at eighth graders in the Boston School
system and ask two questions.
How does the thickness of the neocortex that
empowers the human brain to learn and to think,
how does that vary in relation to standardized test scores?
How well you read, how well you do math.
And how does it vary in relation to whether you have the luck
to be born into a family with affluence, or poverty,
and qualify for free or reduced lunch.
How does that change the structure of the brain?
And here's what we found.
So let me say a word what you see here.
This is the left and right hemispheres
viewed from the sides, viewed from the ears.
Everything that's in red and yellow
means it's statistically significant.
That's why it's color there.
And everything and red and yellow in this top panel
is the thicker the cortex of eighth graders
who are going to Boston public schools,
the better they do on standardized tests of reading
and math.
So that's one thing, and we expect that.
There's a relationship between your brain and what you learn.
In fact, you can't learn anything without a brain.
All the learning is a brain mechanism, right?
Down here we do a second question.
We divide the students into those
who qualify for free or reduced lunch,
because of low family income, or students
who don't qualify because their family makes
more money than that.
And this is the difference between children
born to poverty or born to relative affluence, which
is large and substantial, and not only do we find this,
but many other researchers in the last years
have shown this as well.
So now two things happen.
When people see this picture, sometimes they
think it's very discouraging.
It's no more discouraging than what
we know is the consequence of being
born into a family of low income and low education.
We know that already in terms of educational outcomes,
health outcomes, longevity, and every other measure
of human well-being.
It's something that want to do better at for everybody, right?
And the brain is very plastic.
It's stunningly plastic.
We know that in many animal research, but in human research
as well.
I could show you a picture after picture of human brains
changing as they learn.
We had a summer study where people learned Chinese.
You should see how their brain processes Chinese
now after two months of learning compared
to when it meant nothing to them at the beginning.
The brain is phenomenally plastic.
We can do amazing things, but we have
to recognize the challenges that are in front of us.
Lastly, we have another method to look at,
not the gray matter of the brain,
the neurons of the brain, but the white matter of the brain.
So what's the white matter the brain?
Let me remind you that's the internet of the brain.
That's the cabling of the brain.
Axons that talk to one another send out--
neurons sent out axons.
Those are myelinated.
They're covered in myelin to communicate
with other neurons at a distance accurately and quickly.
And using the flow of water in the brain,
we can map out the wiring of an individual person's brain.
What this shows you is a single person.
Where we see red, that's white matter
connecting your left and right hemispheres.
Green is front to back of the brain.
Blue is up and down in the brain.
And we can make an approximate picture
of how an individual brain communicates information
from brain area to brain area.
Practically everything we do that's interesting as a human
is an orchestrated set of networks
that are connected to one another
to accomplish human thought, feeling, and action.
So one thing we know is that there is many different kinds
of learners, and some children, for example,
struggle to learn to read.
About 10% of children have something
that's called dyslexia, an otherwise unexplained
difficulty in learning to read.
And one of the things that we want to accomplish
is not only to understand why that happens, but we
know that the earlier a child gets help--
and there are pretty effective programs.
None of them are perfect, but some of them
help children considerably to learn to read.
The earlier they get help, the better they do, in most cases.
The way things are set up now in schools,
there's a wait to fail model, and this was referred to
before, which is schools tend to wait until a child is so
clearly so far behind his or her classmates,
and then go, oh my gosh, you're a third or fourth grader who's
two years behind?
Now this triggers some action on our part.
What if we could identify as a child arrives
at the beginning of kindergarten before there's
any formal reading instruction, which child is
likely to become a poor reader?
And what if we gave that help before the child ever fell
behind his or her classmates?
Before the child ever was discouraged
about his or her prospects in academics and school.
And so this combination of behavioral analysis and brain
imaging, we've been looking at 2000 kindergartens
from 20 diverse schools in the Boston area,
and asking whether we can see differences in the brain
before a child gets his or her first reading
instruction in school that will help us identify
who will struggle to read, and therefore,
ought to trigger help to children before they fail.
And here's an example.
This is the white matter pathway that
connects the two major language areas of the brain.
Broca's area in the frontal cortex
and Wernicke's area in the temporal cortex.
It's called the left arcuate fasciculus.
And here are two kindergartener's-- and these
are representative of the sample over all.
A child who we identified through behavioral testing,
but also this brain difference, who by the end of first grade
is really falling behind.
We're following the children to know can we measure something
in the beginning that predicts who will struggle
and who will not?
Here's a child who arrived in kindergarten
with this kind of arcuate fasciculus larger
and differently organized.
She's a fine reader at the end of first grade.
So we think that through a combination of measures,
including these brain measures, we
will be able to identify children
with a wide variety of risks, and bring help to them
before they ever fall.
Not waiting for failure, but helping everybody
in an individuated way, and technology will certainly play
a fantastic role in individuated education to help different
kinds of learners-- and there's a huge variety of learners--
blossom, and express their full potential,
and not be blocked by one kind of learning
that's difficult for them.
So we're very excited through this MIT Integrated Learning
Initiative to bring the best of science, engineering,
and policy to shine the light of sort of honest research
where we can in education, and to be a partner to all
of the other parts of the educational communities
in making differences for children pre-K through 12,
undergraduates, and continuing adult education.
Thank you very much.
Thanks again for joining us.
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