9:59:59.000,9:59:59.000
So I'd like to talk about[br]the development of human potential,

9:59:59.000,9:59:59.000
and I'd like to start with maybe the most[br]impactful modern story of development.

9:59:59.000,9:59:59.000
Many of you here have probably heard[br]of the 10,000 hours rule.

9:59:59.000,9:59:59.000
Maybe you even model[br]your own life after it.

9:59:59.000,9:59:59.000
Basically it's the idea[br]that to become great in anything,

9:59:59.000,9:59:59.000
it takes 10,000 hours[br]of focused practice ...

9:59:59.000,9:59:59.000
so you'd better get started[br]as early as possible.

9:59:59.000,9:59:59.000
The poster child[br]for this story is Tiger Woods.

9:59:59.000,9:59:59.000
His father famously gave him[br]a putter when he was seven months old.

9:59:59.000,9:59:59.000
At 10 months he started[br]imitating his father's swing.

9:59:59.000,9:59:59.000
At two you can go on YouTube[br]and see him on national television.

9:59:59.000,9:59:59.000
Fast forward to the age of 21,

9:59:59.000,9:59:59.000
he's the greatest golfer in the world.

9:59:59.000,9:59:59.000
Quintessential 10,000 hours story.

9:59:59.000,9:59:59.000
Another that features a number[br]of bestselling books

9:59:59.000,9:59:59.000
is that of the three Polgar sisters,

9:59:59.000,9:59:59.000
whose father decided to teach[br]them chess in a very technical manner

9:59:59.000,9:59:59.000
from a very early age.

9:59:59.000,9:59:59.000
And really he wanted to show

9:59:59.000,9:59:59.000
that with a headstart in focused practice,

9:59:59.000,9:59:59.000
any child could become[br]a genius in anything.

9:59:59.000,9:59:59.000
And in fact,

9:59:59.000,9:59:59.000
two of his daughters went on[br]to become grandmaster chess players.

9:59:59.000,9:59:59.000
When I became the science writer[br]at "Sports Illustrated" magazine,

9:59:59.000,9:59:59.000
I got curious.

9:59:59.000,9:59:59.000
If this 10,000 hours rule is correct,

9:59:59.000,9:59:59.000
then we should see that elite[br]athletes get a head start

9:59:59.000,9:59:59.000
in so-called deliberate practice.

9:59:59.000,9:59:59.000
This is coached,

9:59:59.000,9:59:59.000
error-correction focused practice,

9:59:59.000,9:59:59.000
not just playing around.

9:59:59.000,9:59:59.000
And in fact,

9:59:59.000,9:59:59.000
when scientists study elite athletes,

9:59:59.000,9:59:59.000
they see that they spend more time[br]in deliberate practice.

9:59:59.000,9:59:59.000
Not a big surprise.

9:59:59.000,9:59:59.000
When they actually track athletes[br]over the course of their development,

9:59:59.000,9:59:59.000
the patter looks like this.

9:59:59.000,9:59:59.000
The future elites actually spend[br]less time early on in deliberate practice

9:59:59.000,9:59:59.000
in their eventual sport.

9:59:59.000,9:59:59.000
They tend to have what scientists[br]call a sampling period,

9:59:59.000,9:59:59.000
where they try a variety[br]of physical activities,

9:59:59.000,9:59:59.000
they gain broad, general skills,

9:59:59.000,9:59:59.000
they learn about their interests[br]and abilities

9:59:59.000,9:59:59.000
and delay specializing until later[br]than peers who plateau at lower levels.

9:59:59.000,9:59:59.000
And so when I saw that I said,

9:59:59.000,9:59:59.000
"Gosh, that doesn't really comport[br]with the 10,000 hours rule, does it?"

9:59:59.000,9:59:59.000
So I started to wonder about other domains

9:59:59.000,9:59:59.000
that we associate[br]with obligatory specialization,

9:59:59.000,9:59:59.000
like music.

9:59:59.000,9:59:59.000
Turns out the pattern's often similar.

9:59:59.000,9:59:59.000
This is research from[br]a world-class music academy,

9:59:59.000,9:59:59.000
and what I want to draw[br]your attention to is this:

9:59:59.000,9:59:59.000
the exceptional musicians didn't start[br]spending more time in deliberate practice

9:59:59.000,9:59:59.000
than the average musicians

9:59:59.000,9:59:59.000
until their third instrument.

9:59:59.000,9:59:59.000
They too tended to have a sampling period.

9:59:59.000,9:59:59.000
Even musicians we think of[br]as famously precocious,

9:59:59.000,9:59:59.000
like Yo-Yo Ma.

9:59:59.000,9:59:59.000
He had a sampling period,

9:59:59.000,9:59:59.000
he just went through it more rapidly[br]than most musicians do.

9:59:59.000,9:59:59.000
Nonetheless, this research[br]is almost entirely ignored,

9:59:59.000,9:59:59.000
and much more impactful

9:59:59.000,9:59:59.000
is the first page of the book [br]"Battle Hymn of the Tiger Mother,"

9:59:59.000,9:59:59.000
where the author recounts [br]assigning her daughter violin.

9:59:59.000,9:59:59.000
Nobody seems to remember[br]the part later in the book

9:59:59.000,9:59:59.000
where her daughter turns to her[br]and says, "You picked it, not me,"

9:59:59.000,9:59:59.000
and largely quits.

9:59:59.000,9:59:59.000
So, having seen this sort of surprising[br]pattern in sports and music,

9:59:59.000,9:59:59.000
I started to think about domains[br]that effect even more people,

9:59:59.000,9:59:59.000
like education.

9:59:59.000,9:59:59.000
An economist found a natural experiment

9:59:59.000,9:59:59.000
in the higher-ed systems[br]of England and Scotland.

9:59:59.000,9:59:59.000
In the period he studied,

9:59:59.000,9:59:59.000
the systems were very similar,

9:59:59.000,9:59:59.000
except in England,

9:59:59.000,9:59:59.000
students had to specialize[br]in their mid-teen years

9:59:59.000,9:59:59.000
to pick a specific course of study[br]to apply towards.

9:59:59.000,9:59:59.000
In Scotland, they could keep trying[br]things in the university

9:59:59.000,9:59:59.000
if they wanted to.

9:59:59.000,9:59:59.000
And his question was:

9:59:59.000,9:59:59.000
who wins the trade-off,

9:59:59.000,9:59:59.000
the early of the late specializers?

9:59:59.000,9:59:59.000
And what he saw was that the early[br]specializers jump out to an income lead

9:59:59.000,9:59:59.000
because they have more[br]domain-specific skills.

9:59:59.000,9:59:59.000
The late specializers get to try[br]more different things,

9:59:59.000,9:59:59.000
and when they do pick,

9:59:59.000,9:59:59.000
they have better fit,

9:59:59.000,9:59:59.000
or what economists call "match quality."

9:59:59.000,9:59:59.000
And so their growth rates are faster.

9:59:59.000,9:59:59.000
Bu six years out,

9:59:59.000,9:59:59.000
they erase that income gap.

9:59:59.000,9:59:59.000
Meanwhile, the early specializers[br]start quitting their career tracks

9:59:59.000,9:59:59.000
in much higher numbers,

9:59:59.000,9:59:59.000
essentially because they were made[br]the choose so early

9:59:59.000,9:59:59.000
that they more often made poor choices.

9:59:59.000,9:59:59.000
So the late specializers lose[br]in the short term

9:59:59.000,9:59:59.000
and win the long run.

9:59:59.000,9:59:59.000
I think if we thought about[br]career choice like dating,

9:59:59.000,9:59:59.000
we might not pressure people[br]to settle down quite so quickly.

9:59:59.000,9:59:59.000
So this got me interested --

9:59:59.000,9:59:59.000
seeing this pattern again --

9:59:59.000,9:59:59.000
in exploring the developmental backgrounds

9:59:59.000,9:59:59.000
of people whose work I had long admired.

9:59:59.000,9:59:59.000
Like Duke Ellington,

9:59:59.000,9:59:59.000
who shunned music lessons[br]as a kid to focus on baseball

9:59:59.000,9:59:59.000
and painting and drawing.

9:59:59.000,9:59:59.000
Or Maryam Mirzakhani,

9:59:59.000,9:59:59.000
who wasn't interested[br]in math as a girl --

9:59:59.000,9:59:59.000
dreamed of becoming an novelist

9:59:59.000,9:59:59.000
and went on to become the first,

9:59:59.000,9:59:59.000
and so far only woman to win[br]the Fields Medal,

9:59:59.000,9:59:59.000
the most prestigious prize[br]in the world in math.

9:59:59.000,9:59:59.000
Or Vincent Van Gogh --

9:59:59.000,9:59:59.000
had five different careers,

9:59:59.000,9:59:59.000
each of which he deemed[br]his true calling

9:59:59.000,9:59:59.000
before flaming out spectacularly.

9:59:59.000,9:59:59.000
And in his late 20s picked up a book[br]called "The Guide to the ABCs of Drawing."

9:59:59.000,9:59:59.000
That worked out OK.

9:59:59.000,9:59:59.000
Claude Shannon was an electrical engineer[br]at the University of Michigan

9:59:59.000,9:59:59.000
who took a philosophy course[br]just to fulfill a requirement,

9:59:59.000,9:59:59.000
and in it, he learned about [br]a near century-old system of logic

9:59:59.000,9:59:59.000
by which true and false statements[br]could be coded as ones and zeros

9:59:59.000,9:59:59.000
and solved like math problems.

9:59:59.000,9:59:59.000
This led to the development[br]of binary code,

9:59:59.000,9:59:59.000
which underlies all of our[br]digital computers today.

9:59:59.000,9:59:59.000
Finally, my own sort of role model,

9:59:59.000,9:59:59.000
Frances Hesselbein --

9:59:59.000,9:59:59.000
this is me with her --

9:59:59.000,9:59:59.000
she took her first professional[br]job at the age of 54

9:59:59.000,9:59:59.000
and went on to become [br]the CEO of the Girl Scouts,

9:59:59.000,9:59:59.000
which she saved.

9:59:59.000,9:59:59.000
She tripled minority membership,

9:59:59.000,9:59:59.000
added 130,000 volunteers,

9:59:59.000,9:59:59.000
and this is one of the proficiency badges[br]that came out of her tenrure --

9:59:59.000,9:59:59.000
it's binary code for girls[br]learning about computers.

9:59:59.000,9:59:59.000
Today, Frances runs a leadership institute

9:59:59.000,9:59:59.000
where she works every[br]weekday in Manhattan,

9:59:59.000,9:59:59.000
and she's only 104,

9:59:59.000,9:59:59.000
so who knows what's next.

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
We never really hear developmental[br]stories like this, do we?

9:59:59.000,9:59:59.000
We don't hear about the research

9:59:59.000,9:59:59.000
that found that Nobel Laureate scientists[br]are 22 times more likely

9:59:59.000,9:59:59.000
to have a hobby outside of work

9:59:59.000,9:59:59.000
as are typical scientists.

9:59:59.000,9:59:59.000
We never hear that.

9:59:59.000,9:59:59.000
Even when the performers[br]or the work is very famous,

9:59:59.000,9:59:59.000
we don't hear these[br]developmental stories.

9:59:59.000,9:59:59.000
For example, here's[br]an athlete I've followed.

9:59:59.000,9:59:59.000
Here he is at age six,

9:59:59.000,9:59:59.000
wearing a Scottish rugby kit.

9:59:59.000,9:59:59.000
Now he tried some tennis,

9:59:59.000,9:59:59.000
some skiing,

9:59:59.000,9:59:59.000
wrestling.

9:59:59.000,9:59:59.000
His mother was actually a tennis coach[br]but she declined to coach him

9:59:59.000,9:59:59.000
because he wouldn't return balls normally.

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
He did some basketball,

9:59:59.000,9:59:59.000
table tennis,

9:59:59.000,9:59:59.000
swimming.

9:59:59.000,9:59:59.000
When his coaches wanted to move[br]him up a level to play with older boys,

9:59:59.000,9:59:59.000
he declined because he just wanted[br]to talk about pro wrestling after practice

9:59:59.000,9:59:59.000
with his friends.

9:59:59.000,9:59:59.000
And he kept trying more sports:

9:59:59.000,9:59:59.000
handball,

9:59:59.000,9:59:59.000
volleyball,

9:59:59.000,9:59:59.000
soccer,

9:59:59.000,9:59:59.000
badminton,

9:59:59.000,9:59:59.000
skateboarding.

9:59:59.000,9:59:59.000
So who is this dabbler?

9:59:59.000,9:59:59.000
This is Roger Federer.

9:59:59.000,9:59:59.000
Every bit as famous[br]as an adult as Tiger Woods,

9:59:59.000,9:59:59.000
and yet even tennis enthusiasts don't[br]usually know anything

9:59:59.000,9:59:59.000
about his developmental story.

9:59:59.000,9:59:59.000
Why is that even though it's the norm?

9:59:59.000,9:59:59.000
I think it's partly because the Tiger[br]story is very dramatic.

9:59:59.000,9:59:59.000
But also because it seems[br]like this tidy narrative

9:59:59.000,9:59:59.000
that we can extrapolate to anything[br]we want to be good at in our own lives.

9:59:59.000,9:59:59.000
But that I think is a problem,

9:59:59.000,9:59:59.000
because it turns out that in many ways[br]golf is a uniquely horrible model

9:59:59.000,9:59:59.000
of almost everything[br]that humans want to learn.

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
Golf is the epitome of what[br]the psychologist Robin Hogarth called

9:59:59.000,9:59:59.000
a "Kind learning environment."

9:59:59.000,9:59:59.000
Kind learning environments have next steps[br]and goals that are clear,

9:59:59.000,9:59:59.000
rules that are clear and never change --

9:59:59.000,9:59:59.000
when you do something you get feedback[br]that is quick and accurate --

9:59:59.000,9:59:59.000
work next year will look[br]like work last year.

9:59:59.000,9:59:59.000
Chess:

9:59:59.000,9:59:59.000
also a kind learning environment.

9:59:59.000,9:59:59.000
The grandmasters' advantage is based[br]on knowledge of recurring patterns,

9:59:59.000,9:59:59.000
which is also why[br]it's so easy to automate.

9:59:59.000,9:59:59.000
On the other end of the spectrum[br]are "wicked learning environments,"

9:59:59.000,9:59:59.000
where next steps and goals[br]may not be clear.

9:59:59.000,9:59:59.000
Rules may change.

9:59:59.000,9:59:59.000
You may or may not get feedback[br]when you do something.

9:59:59.000,9:59:59.000
It may be delayed,

9:59:59.000,9:59:59.000
it may be inaccurate

9:59:59.000,9:59:59.000
and work next year may not[br]look like work last year.

9:59:59.000,9:59:59.000
So which one of these[br]sounds like the world

9:59:59.000,9:59:59.000
we're increasingly living in?

9:59:59.000,9:59:59.000
In fact, our need to think[br]in an adaptable manner

9:59:59.000,9:59:59.000
and to keep track of interconnecting parts

9:59:59.000,9:59:59.000
has fundamentally changed our perception.

9:59:59.000,9:59:59.000
So when you look at this diagram,

9:59:59.000,9:59:59.000
the central circle on the right[br]probably looks larger to you

9:59:59.000,9:59:59.000
because your brain is drawn[br]to the relationship of the parts

9:59:59.000,9:59:59.000
in the whole,

9:59:59.000,9:59:59.000
whereas someone who hasn't been[br]exposed to modern work

9:59:59.000,9:59:59.000
with its requirement for adaptable,[br]conceptual thought,

9:59:59.000,9:59:59.000
will see correctly that the central[br]circles are the same size.

9:59:59.000,9:59:59.000
So here we are in the wicked work world,

9:59:59.000,9:59:59.000
and there, sometimes[br]hyperspecialization can backfire badly.

9:59:59.000,9:59:59.000
For example,

9:59:59.000,9:59:59.000
in research in a dozen countries

9:59:59.000,9:59:59.000
that matched people for their parents'[br]years of education,

9:59:59.000,9:59:59.000
their test scores,

9:59:59.000,9:59:59.000
their own years of education,

9:59:59.000,9:59:59.000
the difference was some got[br]career-focused education

9:59:59.000,9:59:59.000
and some got broader, general education.

9:59:59.000,9:59:59.000
The pattern was those who got[br]the career-focused education

9:59:59.000,9:59:59.000
are more likely to be hired[br]right out of training,

9:59:59.000,9:59:59.000
more likely to make more money right away,

9:59:59.000,9:59:59.000
but so much less adaptable[br]in a changing work world,

9:59:59.000,9:59:59.000
that they spend so much less time[br]in the workforce overall

9:59:59.000,9:59:59.000
that they win in the short term[br]and lose in the long run.

9:59:59.000,9:59:59.000
Or consider a famous,[br]20-year study of experts

9:59:59.000,9:59:59.000
making geopolitical[br]and economic predictions.

9:59:59.000,9:59:59.000
The worst forecasters were the most[br]specialized experts.

9:59:59.000,9:59:59.000
Those who'd spent their entire careers[br]studying one or two problems

9:59:59.000,9:59:59.000
and came to see the whole world[br]through one lens or mental model.

9:59:59.000,9:59:59.000
Some of them actually got worse[br]as they accumulated experience

9:59:59.000,9:59:59.000
and credentials.

9:59:59.000,9:59:59.000
The best forecasters were simply[br]bright people with wide-ranging interests.

9:59:59.000,9:59:59.000
Now in some domains,

9:59:59.000,9:59:59.000
like medicine,

9:59:59.000,9:59:59.000
increasing specialization has been[br]both inevitable and beneficial.

9:59:59.000,9:59:59.000
No question about it.

9:59:59.000,9:59:59.000
And yet it's been a double-edged sword.

9:59:59.000,9:59:59.000
A few years ago,

9:59:59.000,9:59:59.000
one of the most popular surgeries[br]in the world for knee pain

9:59:59.000,9:59:59.000
was tested in a placebo-controlled trial.

9:59:59.000,9:59:59.000
Some of the patients got sham surgery.

9:59:59.000,9:59:59.000
That means the surgeons make an incision,

9:59:59.000,9:59:59.000
they bang around like[br]they're doing something

9:59:59.000,9:59:59.000
and then they sew the patient back up.

9:59:59.000,9:59:59.000
That performed just as a well.

9:59:59.000,9:59:59.000
And yet surgeons who specialize[br]in the procedure continue to do it

9:59:59.000,9:59:59.000
by the millions.

9:59:59.000,9:59:59.000
So if hyperspecialization isn't always[br]the trick in a wicked world, what is?

9:59:59.000,9:59:59.000
That can be difficult to talk about

9:59:59.000,9:59:59.000
because it doesn't[br]always look like this path.

9:59:59.000,9:59:59.000
Sometimes it looks like[br]meandering or zig-zagging

9:59:59.000,9:59:59.000
or keeping a broader view.

9:59:59.000,9:59:59.000
It can look like getting behind.

9:59:59.000,9:59:59.000
But I want to talk about what[br]some of those tricks might be.

9:59:59.000,9:59:59.000
If we look at research[br]on technological innovation,

9:59:59.000,9:59:59.000
it shows that increasingly,

9:59:59.000,9:59:59.000
the most impactful patents[br]are not authored by individuals

9:59:59.000,9:59:59.000
who drill deeper, deeper, deeper[br]into one area of technology,

9:59:59.000,9:59:59.000
as classified by the US Patent Office,

9:59:59.000,9:59:59.000
but rather by teams that include[br]individuals who have worked across

9:59:59.000,9:59:59.000
a large number of different[br]technology classes

9:59:59.000,9:59:59.000
and often merge things[br]from different domains.

9:59:59.000,9:59:59.000
Someone whose work I've admired

9:59:59.000,9:59:59.000
who was sort of[br]on the forefront of this --

9:59:59.000,9:59:59.000
a Japanese man named Gunpei Yokoi.

9:59:59.000,9:59:59.000
Yokoi didn't score well[br]on his electronics exams at school,

9:59:59.000,9:59:59.000
so he had to settle for a low-tier job[br]as a machine maintenance worker

9:59:59.000,9:59:59.000
at a playing card company in Kyoto.

9:59:59.000,9:59:59.000
He realized he wasn't equipped[br]to work on the cutting edge,

9:59:59.000,9:59:59.000
but there was so much[br]information easily available

9:59:59.000,9:59:59.000
that maybe he could combine things[br]that were already well-known

9:59:59.000,9:59:59.000
in ways that specialists[br]were too narrow to see.

9:59:59.000,9:59:59.000
So he combined some well-known technology[br]from the calculator industry

9:59:59.000,9:59:59.000
with some well-known technology[br]from the credit card industry

9:59:59.000,9:59:59.000
and made handheld games.

9:59:59.000,9:59:59.000
And they were a hit.

9:59:59.000,9:59:59.000
And it turned this playing card company,

9:59:59.000,9:59:59.000
which was founded in a wooden[br]storefront in the 19th century,

9:59:59.000,9:59:59.000
into a toy and game operation.

9:59:59.000,9:59:59.000
You may have heard of it.

9:59:59.000,9:59:59.000
It's called Nintendo.

9:59:59.000,9:59:59.000
Yokoi's creative philosophy translated

9:59:59.000,9:59:59.000
to "lateral thinking [br]with withered technology."

9:59:59.000,9:59:59.000
Taking well-known technology[br]and using it in new ways.

9:59:59.000,9:59:59.000
And his magnum opus was this:

9:59:59.000,9:59:59.000
the Game Boy.

9:59:59.000,9:59:59.000
Technological joke in every way.

9:59:59.000,9:59:59.000
And it came out at the same time[br]as color competitors from Saga and Atari

9:59:59.000,9:59:59.000
and it blew them away.

9:59:59.000,9:59:59.000
Because Yokoi knew what his[br]customers cared about wasn't color,

9:59:59.000,9:59:59.000
it was durability,

9:59:59.000,9:59:59.000
portability,

9:59:59.000,9:59:59.000
affordability,

9:59:59.000,9:59:59.000
battery life,

9:59:59.000,9:59:59.000
game selection.

9:59:59.000,9:59:59.000
This is mine that I found[br]in my parents' basement.

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
Seen better days.

9:59:59.000,9:59:59.000
But you can see the red light is on.

9:59:59.000,9:59:59.000
I flipped it on and played some Tetris,

9:59:59.000,9:59:59.000
which I thought was especially impressive

9:59:59.000,9:59:59.000
because the batteries had expired[br]in 2007 and 2013.

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
So this breadth advantage holds[br]in more subjective realms as well.

9:59:59.000,9:59:59.000
In a fascinating study of what leads[br]some comic book creators

9:59:59.000,9:59:59.000
to be more likely to make[br]blockbuster comics,

9:59:59.000,9:59:59.000
a pair of researchers found

9:59:59.000,9:59:59.000
that it was neither the number of years[br]of experience in the field

9:59:59.000,9:59:59.000
nor the resources of the publisher,

9:59:59.000,9:59:59.000
nor the number of previous comics made.

9:59:59.000,9:59:59.000
It was the number of different genres[br]that a creator had worked across.

9:59:59.000,9:59:59.000
And interestingly, a broad individual[br]could not be entirely replaced

9:59:59.000,9:59:59.000
by a team of specialists.

9:59:59.000,9:59:59.000
We probably don't make as many[br]of those people as we could

9:59:59.000,9:59:59.000
because early on,

9:59:59.000,9:59:59.000
they just look like they're behind

9:59:59.000,9:59:59.000
and we don't tend to incentivize anything[br]that doesn't look like a head start

9:59:59.000,9:59:59.000
or specialization.

9:59:59.000,9:59:59.000
In fact, I think in the well-meaning[br]drive for a head start,

9:59:59.000,9:59:59.000
we often even counterproductively[br]short circuit even the way we learn

9:59:59.000,9:59:59.000
new material at a fundamental level.

9:59:59.000,9:59:59.000
In a study last year,

9:59:59.000,9:59:59.000
seventh-grade math classrooms in the US

9:59:59.000,9:59:59.000
were randomly assigned[br]to different types of learning.

9:59:59.000,9:59:59.000
Some got what's called blocked practice.

9:59:59.000,9:59:59.000
That's like, you get problem type A,

9:59:59.000,9:59:59.000
AAAAA,

9:59:59.000,9:59:59.000
BBBBB,

9:59:59.000,9:59:59.000
and so on.

9:59:59.000,9:59:59.000
Progress is fast,

9:59:59.000,9:59:59.000
kids are happy,

9:59:59.000,9:59:59.000
everything's great.

9:59:59.000,9:59:59.000
Other classrooms got assigned[br]to what's called "Interleaved practice."

9:59:59.000,9:59:59.000
That's like if you took[br]all the problem types

9:59:59.000,9:59:59.000
and put them in a hat

9:59:59.000,9:59:59.000
and drew them out at random.

9:59:59.000,9:59:59.000
Progress is slower,

9:59:59.000,9:59:59.000
kids are more frustrated.

9:59:59.000,9:59:59.000
But instead of learning[br]how to execute procedures,

9:59:59.000,9:59:59.000
they're learning how to match[br]a strategy to a type of problem.

9:59:59.000,9:59:59.000
And when the test comes around,

9:59:59.000,9:59:59.000
the interleaved group blew[br]the block practice group away.

9:59:59.000,9:59:59.000
It wasn't even close.

9:59:59.000,9:59:59.000
Now I found a lot of this research[br]deeply counterintuitive.

9:59:59.000,9:59:59.000
They idea that a headstart,

9:59:59.000,9:59:59.000
whether in picking a career[br]or a course of study

9:59:59.000,9:59:59.000
of just in learning new material,

9:59:59.000,9:59:59.000
can sometimes undermine[br]long-term development.

9:59:59.000,9:59:59.000
And naturally, I think there are as many[br]ways to succeed as there are people,

9:59:59.000,9:59:59.000
but I think we tend only to incentivize[br]and encourage the tiger path

9:59:59.000,9:59:59.000
when increasingly in a wicked world,

9:59:59.000,9:59:59.000
we need people who travel[br]the Roger path as well.

9:59:59.000,9:59:59.000
Or as the eminent physicist[br]and mathematician

9:59:59.000,9:59:59.000
and wonderful writer,

9:59:59.000,9:59:59.000
Freeman Dyson put it --

9:59:59.000,9:59:59.000
and Dyson passed away yesterday,

9:59:59.000,9:59:59.000
so I hope I'm doing[br]his words honor here --

9:59:59.000,9:59:59.000
as he said,

9:59:59.000,9:59:59.000
"For a healthy ecosystem,

9:59:59.000,9:59:59.000
we need both birds and frogs.

9:59:59.000,9:59:59.000
Frogs are down in the mud,

9:59:59.000,9:59:59.000
see all the granular details.

9:59:59.000,9:59:59.000
The birds are soaring up above[br]not seeing those details,

9:59:59.000,9:59:59.000
but integrating[br]the knowledge of the frogs."

9:59:59.000,9:59:59.000
And we need both.

9:59:59.000,9:59:59.000
The problem, Dyson said,

9:59:59.000,9:59:59.000
is that "we're telling everyone[br]to become frogs"

9:59:59.000,9:59:59.000
and I think,

9:59:59.000,9:59:59.000
in a wicked world[br]that's increasingly short-sighted.

9:59:59.000,9:59:59.000
Thank you very much.

9:59:59.000,9:59:59.000
(Applause)