ABOUT THE SPEAKER
Daphne Koller - Educator
With Coursera, Daphne Koller and co-founder Andrew Ng are bringing courses from top colleges online, free, for anyone who wants to take them.

Why you should listen

A 3rd generation Ph.D who is passionate about education, Stanford professor Daphne Koller is excited to be making the college experience available to anyone through her startup, Coursera. With classes from 85 top colleges, Coursera is an innovative model for online learning. While top schools have been putting lectures online for years, Coursera's platform supports the other vital aspect of the classroom: tests and assignments that reinforce learning.

At the Stanford Artificial Intelligence Laboratory, computer scientist Daphne Koller studies how to model large, complicated decisions with lots of uncertainty. (Her research group is called DAGS, which stands for Daphne's Approximate Group of Students.) In 2004, she won a MacArthur Fellowship for her work, which involves, among other things, using Bayesian networks and other techniques to explore biomedical and genetic data sets.

More profile about the speaker
Daphne Koller | Speaker | TED.com
TEDGlobal 2012

Daphne Koller: What we're learning from online education

Daphne Koller: O que estamos aprendendo da educación en liña

Filmed:
2,603,043 views

Daphne Koller está convencendo as mellores universidades para que poñan os cursos máis interesantes en liña e de balde, non só como un servizo, senón tamén como un xeito de investigar a forma en que aprende a xente. Cada vez que se preme unha tecla, que se fai un test de comprensión, que se discute nun foro de compañeiros e que se autocorrixe unha tarefa acumúlase unha marea de datos sen precedentes sobre como se procesa o coñecemento e, máis importante, como se absorbe.
- Educator
With Coursera, Daphne Koller and co-founder Andrew Ng are bringing courses from top colleges online, free, for anyone who wants to take them. Full bio

Double-click the English transcript below to play the video.

00:16
Like many of you, I'm one of the lucky people.
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Como moitos de vós, son
unha persoa afortunada.
00:19
I was born to a family where education was pervasive.
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Medrei nunha familia
onde a educación impregnaba todo.
00:23
I'm a third-generation PhD, a daughter of two academics.
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Son a terceira xeración de doutorados,
filla de dous académicos.
00:27
In my childhood, I played around in my father's university lab.
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Na miña infancia, xoguei no laboratorio
universitario de meu pai.
00:31
So it was taken for granted that I attend some of the best universities,
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Así que se daba por feito que iría
a unha das mellores universidades,
00:35
which in turn opened the door to a world of opportunity.
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que, á súa vez, me abriría as portas
dun mundo de oportunidades.
00:38
Unfortunately, most of the people in the world are not so lucky.
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Por desgraza, a maioría das persoas
non ten tanta sorte.
00:42
In some parts of the world, for example, South Africa,
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Nalgunhas partes do mundo,
por exemplo, en Suráfrica,
00:46
education is just not readily accessible.
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a educación non é de libre acceso.
00:48
In South Africa, the educational system was constructed
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En Suráfrica, o sistema educativo
construíuse
00:51
in the days of apartheid for the white minority.
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nos días do apartheid
para a minoría branca.
00:54
And as a consequence, today there is just not enough spots
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E, como consecuencia, hoxe
non hai suficientes prazas
00:57
for the many more people who want and deserve a high quality education.
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para todas as persoas que queren e merecen
unha educación de alta calidade.
01:01
That scarcity led to a crisis in January of this year
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Esa escaseza provocou
unha crise en xaneiro deste ano
01:05
at the University of Johannesburg.
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na Universidade de Johannesburgo.
01:06
There were a handful of positions left open
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Había unhas cantas prazas dispoñibles
01:09
from the standard admissions process, and the night before
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nos procesos xerais de admisión,
e a noite anterior
01:11
they were supposed to open that for registration,
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a cando se supoñía
que ía abrir o rexistro,
01:14
thousands of people lined up outside the gate in a line a mile long,
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miles de persoas aliñáronse na porta
nunha fileira de 1,5 km,
01:18
hoping to be first in line to get one of those positions.
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agardando ser as primeiras
e conseguir unha das prazas.
01:22
When the gates opened, there was a stampede,
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Cando as portas abriron,
houbo un amoreamento,
01:24
and 20 people were injured and one woman died.
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20 persoas resultaron feridas
e unha muller morreu.
01:28
She was a mother who gave her life
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Era unha nai que deu a súa vida
01:30
trying to get her son a chance at a better life.
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intentando conseguirlle ao seu fillo
a oportunidade dunha vida mellor.
01:34
But even in parts of the world like the United States
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Mesmo en partes do mundo como os EE. UU.
01:37
where education is available, it might not be within reach.
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onde a educación é accesible,
pode estar fóra do alcance.
01:41
There has been much discussed in the last few years
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Debateuse moito nos últimos anos
sobre o incremento dos custos da sanidade.
01:44
about the rising cost of health care.
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01:46
What might not be quite as obvious to people
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O que talvez non é tan obvio para a xente
01:49
is that during that same period the cost of higher education tuition
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é que durante ese mesmo período
o custo das taxas da educación superior
01:53
has been increasing at almost twice the rate,
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foi aumentando
case dúas veces máis rápido,
01:55
for a total of 559 percent since 1985.
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ata sumar un total do 559 % desde 1985.
02:00
This makes education unaffordable for many people.
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Isto fai que a educación sexa
demasiado cara para moita xente.
02:04
Finally, even for those who do manage to get the higher education,
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Finalmente, mesmo para aqueles
que conseguen educación superior
02:08
the doors of opportunity might not open.
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as portas da oportunidade
pode que non se abran.
02:11
Only a little over half of recent college graduates
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Só un pouco máis da metade
de graduados recentes
02:14
in the United States who get a higher education
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nos EE.UU. que teñen formación superior
02:16
actually are working in jobs that require that education.
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están traballando en postos
que requiren ese nivel educativo.
Isto, claro, non é así para os estudantes
02:19
This, of course, is not true for the students
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02:21
who graduate from the top institutions,
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que se gradúan nas institucións elite,
02:23
but for many others, they do not get the value
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pero moitos outros
non conseguen que se lles valoren
02:26
for their time and their effort.
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o tempo e o esforzo.
02:29
Tom Friedman, in his recent New York Times article,
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Tom Friedman, no seu artigo recente
do New York Times, captou,
02:32
captured, in the way that no one else could, the spirit behind our effort.
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nunha forma en que ninguén máis podería,
o espírito por tras dese esforzo.
02:37
He said the big breakthroughs are what happen
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Dixo que os grandes avances
son os que ocorren
02:40
when what is suddenly possible meets what is desperately necessary.
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cando o que de súpeto é posible se une
ao que é desesperadamente necesario.
02:44
I've talked about what's desperately necessary.
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Eu falei do que é
desesperadamente necesario.
02:46
Let's talk about what's suddenly possible.
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Agora imos falar
do que é de súpeto posible.
02:49
What's suddenly possible was demonstrated by
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O que é de súpeto posible
foi demostrado por
02:52
three big Stanford classes,
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tres grandes cursos de Stanford,
02:54
each of which had an enrollment of 100,000 people or more.
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cada unha das cales tivo unha inscrición
de 100 000 persoas ou máis.
02:58
So to understand this, let's look at one of those classes,
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Para entendelo, imos
observar un deses cursos,
o de Aprendizaxe Automática,
impartido polo meu colega
03:01
the Machine Learning class offered by my colleague
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03:03
and cofounder Andrew Ng.
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e cofundador Andrew Ng.
03:05
Andrew teaches one of the bigger Stanford classes.
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Andrew imparte un
dos grandes cursos de Stanford.
03:07
It's a Machine Learning class,
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É o de Aprendizaxe Automática
03:08
and it has 400 people enrolled every time it's offered.
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e ten unhas 400 persoas inscritas
cada vez que se ofrece.
03:12
When Andrew taught the Machine Learning class to the general public,
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Cando Andrew abriu o curso
Aprendizaxe Automática ao público xeral,
03:15
it had 100,000 people registered.
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inscribíronse 100.000 persoas.
03:18
So to put that number in perspective,
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Poñamos o número en perspectiva:
03:20
for Andrew to reach that same size audience
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para que Andrew acadase
unha audiencia do mesmo tamaño
03:22
by teaching a Stanford class,
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impartindo un curso en Stanford,
03:24
he would have to do that for 250 years.
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tería que impartilo durante 250 anos.
03:28
Of course, he'd get really bored.
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Claro, aburriríase moitísimo.
03:31
So, having seen the impact of this,
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Así que, ao vermos o impacto disto,
03:34
Andrew and I decided that we needed to really try and scale this up,
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Andrew e mais eu decidimos
que tiñamos que intentar escalalo
03:37
to bring the best quality education to as many people as we could.
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para levar a mellor educación de calidade
ao maior número de xente que puidésemos.
03:41
So we formed Coursera,
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Así que conformamos Coursera,
03:43
whose goal is to take the best courses
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cuxo obxectivo é coller os mellores cursos
03:46
from the best instructors at the best universities
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dos mellores instrutores
das mellores universidades
03:49
and provide it to everyone around the world for free.
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e proporcionárllelos de balde
a persoas de todo o mundo.
03:53
We currently have 43 courses on the platform
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Actualmente, temos
43 cursos na plataforma,
03:56
from four universities across a range of disciplines,
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de catro universidades e
de toda unha variedade de disciplinas.
03:59
and let me show you a little bit of an overview
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Deixádeme que vos mostre
unha pequena aproximación xeral
04:01
of what that looks like.
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de como é.
(Vídeo) Robert Ghrist:
Benvidos a Cálculo.
04:04
(Video) Robert Ghrist: Welcome to Calculus.
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04:05
Ezekiel Emanuel: Fifty million people are uninsured.
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E. Emanuel: 50 millóns
de persoas non teñen seguro.
04:07
Scott Page: Models help us design more effective institutions and policies.
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S. Page: Cos modelos deseñamos
políticas máis efectivas.
04:10
We get unbelievable segregation.
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Temos unha segregación incrible.
04:13
Scott Klemmer: So Bush imagined that in the future,
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S. Klemmer: Bush imaxinou que no futuro,
04:15
you'd wear a camera right in the center of your head.
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levariamos unha cámara
no centro da cabeza.
04:17
Mitchell Duneier: Mills wants the student of sociology to develop the quality of mind ...
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M. Duneier: Mills quere que o estudante
de socioloxía adquira a cualidade mental
04:21
RG: Hanging cable takes on the form of a hyperbolic cosine.
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RG: O cable colgante toma a forma
dun coseno hiperbólico.
04:25
Nick Parlante: For each pixel in the image, set the red to zero.
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N. Parlante: Para cada píxel da imaxe,
fixe o vermello a cero.
04:28
Paul Offit: ... Vaccine allowed us to eliminate polio virus.
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P. Offit: ... a vacina permitiunos
eliminar o virus da polio.
04:31
Dan Jurafsky: Does Lufthansa serve breakfast and San Jose? Well, that sounds funny.
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D. Jurafsky: A Lufthansa serve almorzo
e San Xosé? Ben, soa estraño.
04:35
Daphne Koller: So this is which coin you pick, and this is the two tosses.
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D. Koller: Así que esta é a moeda
que elixe e estes son os dous lanzamentos.
04:38
Andrew Ng: So in large-scale machine learning, we'd like to come up with computational ...
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A. Ng: Na aprendizaxe automática
a grande escala, gustaríanos chegar a...
04:42
(Applause)
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(Aplausos)
04:47
DK: It turns out, maybe not surprisingly,
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DK: Resulta, talvez non sexa
unha sorpresa,
04:50
that students like getting the best content
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que aos estudantes gústalles
ter o mellor contido
04:52
from the best universities for free.
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das mellores universidades de balde.
04:55
Since we opened the website in February,
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Desde que abrimos a web en febreiro,
04:57
we now have 640,000 students from 190 countries.
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temos agora 640 000 estudantes
de 190 países.
05:02
We have 1.5 million enrollments,
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Temos 1,5 millóns de inscricións,
05:04
6 million quizzes in the 15 classes that have launched
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6 millóns de probas enviadas
nos 15 cursos que lanzamos ata agora
05:07
so far have been submitted, and 14 million videos have been viewed.
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e 14 millóns de vídeos visualizados.
05:12
But it's not just about the numbers,
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Pero non vai só de números,
05:14
it's also about the people.
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tamén vai de xente.
05:16
Whether it's Akash, who comes from a small town in India
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Xa for Akash, que vén
dunha pequena cidade na India
05:19
and would never have access in this case
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e nunca tería acceso
05:21
to a Stanford-quality course
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a un curso da calidade de Stanford
05:22
and would never be able to afford it.
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e nunca sería quen de permitirse isto.
Xa for Jenny, que é nai solteira
de dous fillos
05:25
Or Jenny, who is a single mother of two
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05:27
and wants to hone her skills
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e quere mellorar as súas competencias
05:29
so that she can go back and complete her master's degree.
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para poder retomar
e completar o seu mestrado.
05:32
Or Ryan, who can't go to school,
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Ou Ryan, que non pode ir á escola,
05:35
because his immune deficient daughter
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xa que ten unha filla inmunodeficiente
05:37
can't be risked to have germs come into the house,
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e non pode arriscarse
a levar xermes á casa,
05:40
so he couldn't leave the house.
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por iso non pode abandonala.
05:42
I'm really glad to say --
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Eu alégrome realmente de dicir,
05:44
recently, we've been in correspondence with Ryan --
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recentemente estivemos
en contacto con Ryan,
05:46
that this story had a happy ending.
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que esa historia tivo un final feliz.
05:48
Baby Shannon -- you can see her on the left --
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A bebé Shannon, podedes vela á esquerda,
05:50
is doing much better now,
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está moito mellor agora
05:51
and Ryan got a job by taking some of our courses.
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e Ryan conseguiu un traballo grazas
aos nosos cursos.
Entón, que fai que estes
cursos sexan tan distintos?
05:56
So what made these courses so different?
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05:58
After all, online course content has been available for a while.
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Despois de todo, os cursos
en liña existen desde hai tempo.
06:02
What made it different was that this was real course experience.
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O que os fixo diferentes foi que estes
creaban unha experiencia real.
06:05
It started on a given day,
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Comezaban nun determinado día,
06:07
and then the students would watch videos on a weekly basis
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os estudantes tiñan que ver
vídeos semanalmente
06:11
and do homework assignments.
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e facer tarefas.
06:12
And these would be real homework assignments
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E estas eran tarefas reais
06:14
for a real grade, with a real deadline.
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para unhas notas reais,
cun prazo de entrega real.
06:18
You can see the deadlines and the usage graph.
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Podedes ver os prazos
e as gráficas de uso.
06:20
These are the spikes showing
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Estes son os picos que mostran
06:22
that procrastination is global phenomenon.
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que a procrastinación é
un fenómeno global.
06:26
(Laughter)
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(Risos)
06:28
At the end of the course,
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Á fin do curso,
06:30
the students got a certificate.
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os estudantes obtiñan un certificado.
06:32
They could present that certificate
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Podían presentar ese certificado
nunha empresa para conseguir
un traballo mellor,
06:34
to a prospective employer and get a better job,
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06:36
and we know many students who did.
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e sabemos que moitos estudantes fixérono.
06:38
Some students took their certificate
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Algúns estudantes colleron o certificado
06:40
and presented this to an educational institution at which they were enrolled
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e presentárono na institución educativa
en que estaban inscritos
06:43
for actual college credit.
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para obter créditos universitarios.
06:45
So these students were really getting something meaningful
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Conseguían así
algo realmente significativo
06:47
for their investment of time and effort.
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polo seu investimento
de tempo e de esforzo.
06:50
Let's talk a little bit about some of the components
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Imos falar un pouco dalgún dos compoñentes
06:52
that go into these courses.
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destes cursos.
06:54
The first component is that when you move away
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O primeiro compoñente é
que cando deixamos atrás
06:57
from the constraints of a physical classroom
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as restricións físicas dunha aula
06:59
and design content explicitly for an online format,
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e deseñamos contidos especificamente
para o formato en liña,
07:02
you can break away from, for example,
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podemos romper, por exemplo,
07:05
the monolithic one-hour lecture.
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coa clase monolítica dunha hora.
Podemos fragmentar o material,
por exemplo,
07:07
You can break up the material, for example,
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07:09
into these short, modular units of eight to 12 minutes,
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en unidades curtas, modulares,
de 8 a 12 minutos,
07:12
each of which represents a coherent concept.
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cada unha das cales representa
un concepto coherente.
Os estudantes poden percorrer
o material de distintos xeitos,
07:15
Students can traverse this material in different ways,
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07:18
depending on their background, their skills or their interests.
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segundo a súa experiencia,
as súas destrezas ou os seus intereses.
Así, por exemplo, algúns estudantes
pódense beneficiar
07:21
So, for example, some students might benefit
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07:24
from a little bit of preparatory material
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dunha pequena parte
de material preparatorio
07:27
that other students might already have.
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que outros estudantes poden xa coñecer.
07:29
Other students might be interested in a particular
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Outros poden estar interesados
nun tema concreto
07:31
enrichment topic that they want to pursue individually.
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que queren seguir individualmente
con maior profundidade.
07:34
So this format allows us to break away
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Así que este formato permítenos romper
07:38
from the one-size-fits-all model of education,
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co modelo educativo
en que todo vale para todos,
07:40
and allows students to follow a much more personalized curriculum.
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e permítelles aos estudantes seguir
un currículo máis personalizado.
07:44
Of course, we all know as educators
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Por suposto, todos sabemos
como educadores
07:47
that students don't learn by sitting and passively watching videos.
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que os estudantes non aprenden
sentados vendo vídeos de xeito pasivo.
07:50
Perhaps one of the biggest components of this effort
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Quizais un dos compoñentes
máis grandes deste proxecto
07:53
is that we need to have students
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é que precisamos ter estudantes
07:56
who practice with the material
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que practiquen co material
07:58
in order to really understand it.
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para entendelo de verdade.
08:01
There's been a range of studies that demonstrate the importance of this.
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Houbo unha serie de estudos
que demostraron a importancia disto.
08:04
This one that appeared in Science last year, for example,
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Este publicado en Science
o ano pasado, por exemplo,
08:07
demonstrates that even simple retrieval practice,
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demostrou que mesmo
a simple práctica de recuperación
08:10
where students are just supposed to repeat
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onde os estudantes só teñen que repetir
08:13
what they already learned
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o que xa aprenderon
08:14
gives considerably improved results
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dá resultados moito mellores
08:16
on various achievement tests down the line
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en varias probas de rendemento
08:18
than many other educational interventions.
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que moitas outras
intervencións educativas.
08:23
We've tried to build in retrieval practice into the platform,
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Tentamos construír unha práctica
de recuperación na plataforma
08:25
as well as other forms of practice in many ways.
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así como outras formas de práctica.
08:28
For example, even our videos are not just videos.
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Por exemplo, mesmo os nosos vídeos
non son só vídeos.
08:32
Every few minutes, the video pauses
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Cada poucos minutos, o vídeo detense
08:34
and the students get asked a question.
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e o estudante ten
que responder unha pregunta.
08:36
(Video) SP: ... These four things. Prospect theory, hyperbolic discounting,
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(Vídeo) SP: 4 cousas: prospectiva,
desconto hiperbólico,
08:38
status quo bias, base rate bias. They're all well documented.
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nesgo de statu quo, falacia da taxa base.
Ben documentadas.
08:41
So they're all well documented deviations from rational behavior.
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Todas desviacións ben documentadas
do comportamento racional.
08:44
DK: So here the video pauses,
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DK: Aquí detense o vídeo,
08:46
and the student types in the answer into the box
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e o estudante escribe a resposta na caixa
08:48
and submits. Obviously they weren't paying attention.
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e envíaa. Obviamente,
non estaban prestando atención.
08:51
(Laughter)
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(Risos)
08:52
So they get to try again,
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Así que intentan facelo outra vez,
08:54
and this time they got it right.
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e desta vez fano ben.
08:57
There's an optional explanation if they want.
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Hai unha explicación
opcional se a desexan.
08:59
And now the video moves on to the next part of the lecture.
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E agora o vídeo segue
coa seguinte parte da lección.
09:03
This is a kind of simple question
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Este é un tipo de pregunta simple
que eu como instrutora
podería facer na clase,
09:05
that I as an instructor might ask in class,
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09:07
but when I ask that kind of a question in class,
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pero cando eu fago
ese tipo de pregunta nunha clase,
09:10
80 percent of the students
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o 80 % dos estudantes
09:11
are still scribbling the last thing I said,
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aínda están escribindo
o último que dixen,
09:13
15 percent are zoned out on Facebook,
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O 15 % están en Facebook,
09:16
and then there's the smarty pants in the front row
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e despois están os listos
na fila de diante
09:19
who blurts out the answer
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que soltan a resposta
antes de que ninguén máis
teña ocasión de pensala,
09:20
before anyone else has had a chance to think about it,
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2207
09:22
and I as the instructor am terribly gratified
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e eu como instrutora estou
moi satisfeita
09:25
that somebody actually knew the answer.
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de que alguén saiba a resposta.
09:27
And so the lecture moves on before, really,
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E así a clase continúa,
e a maioría de estudantes
09:29
most of the students have even noticed that a question had been asked.
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nin se chega a decatar de que eu
fixen unha pregunta.
09:33
Here, every single student
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Aquí, cada estudante
09:36
has to engage with the material.
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2784
ten que interactuar co material.
09:38
And of course these simple retrieval questions
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1936
E, claro, estas simples cuestións
de recuperación
09:40
are not the end of the story.
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non son a fin da historia.
09:42
One needs to build in much more meaningful practice questions,
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2970
Precisamos construír cuestións
prácticas moito máis significativas
09:45
and one also needs to provide the students with feedback
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2353
e tamén darlles aos estudantes
retroalimentación
09:47
on those questions.
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1663
sobre estas cuestións.
09:49
Now, how do you grade the work of 100,000 students
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2888
Agora, como se avalía o traballo
de 100 000 estudantes
09:52
if you do not have 10,000 TAs?
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3082
se non temos 10 000
asistentes técnicos?
09:55
The answer is, you need to use technology
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A resposta é que precisamos
usar a tecnoloxía
09:57
to do it for you.
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1495
para que o faga por nós.
09:59
Now, fortunately, technology has come a long way,
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583352
2648
Afortunadamente, a tecnoloxía
xa percorreu un bo camiño,
10:01
and we can now grade a range of interesting types of homework.
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3268
e podemos avaliar
unha variedade interesante de tarefas.
10:05
In addition to multiple choice
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Ademais das preguntas de escolla múltiple
10:06
and the kinds of short answer questions that you saw in the video,
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e de resposta curta que vistes no vídeo,
10:09
we can also grade math, mathematical expressions
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3260
tamén podemos avaliar
matemáticas, expresións matemáticas
10:13
as well as mathematical derivations.
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1952
así como derivacións matemáticas.
10:15
We can grade models, whether it's
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599160
2874
Podemos avaliar modelos,
10:17
financial models in a business class
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2176
xa for modelos financeiros
nunha clase de negocios
10:20
or physical models in a science or engineering class
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2984
ou modelos físicos nunha clase
de ciencias ou enxeñaría
10:23
and we can grade some pretty sophisticated programming assignments.
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607194
3744
e podemos avaliar algúns traballos
de programación moi sofisticados.
10:26
Let me show you one that's actually pretty simple
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610938
1919
Deixádeme amosarvos un que é moi sinxelo
10:28
but fairly visual.
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612857
1480
pero bastante visual.
É do curso Ciencias da Computación 101
de Stanford.
10:30
This is from Stanford's Computer Science 101 class,
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10:32
and the students are supposed to color-correct
225
616814
1604
Os estudantes teñen que corrixir a cor
10:34
that blurry red image.
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1592
da imaxe vermella borrosa.
10:35
They're typing their program into the browser,
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620010
2018
Están inserindo o programa no navegador,
10:37
and you can see they didn't get it quite right, Lady Liberty is still seasick.
228
622028
4058
e podedes ver que non o conseguen,
a Estatua da Liberdade aínda está mareada.
10:41
And so, the student tries again, and now they got it right, and they're told that,
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626086
3756
Así que o estudante inténtao outra vez,
e agora conseguiuno e díselle
10:45
and they can move on to the next assignment.
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2359
que pode seguir coa próxima tarefa.
10:48
This ability to interact actively with the material
231
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3148
Esta capacidade de interactuar
activamente co material
10:51
and be told when you're right or wrong
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1684
e de saber se o fixemos ben ou mal
10:52
is really essential to student learning.
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3126
é realmente esencial para
a aprendizaxe dos estudantes.
10:56
Now, of course we cannot yet grade
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2275
Claro que aínda
non podemos avaliar totalmente
10:58
the range of work that one needs for all courses.
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2834
as actividades que
se precisan para todos os cursos.
11:01
Specifically, what's lacking is the kind of critical thinking work
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3301
Concretamente, falta o tipo
de actividades de pensamento crítico
11:04
that is so essential in such disciplines
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1922
que son esenciais en disciplinas
11:06
as the humanities, the social sciences, business and others.
238
650491
3597
como as de humanidades,
ciencias sociais, negocios e outras.
11:09
So we tried to convince, for example,
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654088
2249
Así que intentamos
convencer, por exemplo,
11:12
some of our humanities faculty
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656337
1616
algúns dos docentes de humanidades
11:13
that multiple choice was not such a bad strategy.
241
657953
2696
de que as preguntas tipo test
non son unha estratexia tan mala.
11:16
That didn't go over really well.
242
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2191
Iso non funcionou moi ben.
11:18
So we had to come up with a different solution.
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Así que tivemos que buscar outra solución.
11:21
And the solution we ended up using is peer grading.
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3074
E a solución á que chegamos
foi a avaliación entre compañeiros.
11:24
It turns out that previous studies show,
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668347
2422
Resulta que segundo estudos previos,
11:26
like this one by Saddler and Good,
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670769
1672
como este de Saddler e Good,
11:28
that peer grading is a surprisingly effective strategy
247
672441
2488
a avaliación entre compañeiros é
sorprendentemente efectiva
11:30
for providing reproducible grades.
248
674929
3214
para conseguir cualificacións
reproducibles.
11:34
It was tried only in small classes,
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678143
1770
Intentouse só en clases pequenas
11:35
but there it showed, for example,
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679913
1487
pero aí demostrouse, por exemplo,
11:37
that these student-assigned grades on the y-axis
251
681400
2482
que esas notas asignadas
por estudantes no eixe y
están moi ben correlacionadas
11:39
are actually very well correlated
252
683882
1311
11:41
with the teacher-assigned grade on the x-axis.
253
685193
2296
coas notas asignadas
por profesores no eixe x.
11:43
What's even more surprising is that self-grades,
254
687489
3160
Sorprende aínda máis
que as autoavaliacións
onde os estudantes puntúan
o seu propio traballo de xeito crítico,
11:46
where the students grade their own work critically --
255
690649
2311
11:48
so long as you incentivize them properly
256
692960
1737
sempre que os motivemos apropiadamente
11:50
so they can't give themselves a perfect score --
257
694697
1938
para que non poidan poñerse a nota máxima,
11:52
are actually even better correlated with the teacher grades.
258
696635
3191
están mellor correlacionadas
coas avaliacións do profesor.
11:55
And so this is an effective strategy
259
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1607
Así que é unha estratexia eficaz
11:57
that can be used for grading at scale,
260
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2104
que pode usarse
para avaliar a grande escala
11:59
and is also a useful learning strategy for the students,
261
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2736
e unha estratexia de aprendizaxe
útil para os estudantes,
12:02
because they actually learn from the experience.
262
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2255
porque eles realmente
aprenden da experiencia.
12:04
So we now have the largest peer-grading pipeline ever devised,
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708528
4649
Así que agora temos a maior rede de
avaliación entre compañeiros nunca vista,
12:09
where tens of thousands of students
264
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2504
con decenas de miles de estudantes
12:11
are grading each other's work,
265
715681
1198
que cualifican o traballo doutros
12:12
and quite successfully, I have to say.
266
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3069
e con bastante éxito, teño que dicilo.
12:15
But this is not just about students
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2260
Pero isto non se trata
unicamente de estudantes
12:18
sitting alone in their living room working through problems.
268
722208
3041
sentados sós nos seus salóns
traballando con problemas.
12:21
Around each one of our courses,
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725249
1807
Ao redor de cada un dos nosos cursos
12:22
a community of students had formed,
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2160
formouse unha comunidade de estudantes,
12:25
a global community of people
271
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1880
unha comunidade global de xente
12:26
around a shared intellectual endeavor.
272
731096
2532
ao redor dun esforzo
intelectual compartido.
12:29
What you see here is a self-generated map
273
733628
2652
O que vedes aquí é un mapa autoxerado
12:32
from students in our Princeton Sociology 101 course,
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736280
2961
de estudantes do noso curso 101
de Socioloxía de Princeton
12:35
where they have put themselves on a world map,
275
739241
2759
onde teñen que poñerse nun mapamundi,
12:37
and you can really see the global reach of this kind of effort.
276
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2960
e podedes ver o alcance global
deste tipo de proxecto.
12:40
Students collaborated in these courses in a variety of different ways.
277
744960
4567
Os estudantes colaboraron
nestes cursos de diferentes xeitos.
En primeiro lugar, había un foro
de preguntas e respostas
12:45
First of all, there was a question and answer forum,
278
749527
2639
12:48
where students would pose questions,
279
752166
2144
onde os estudantes
tiñan que poñer preguntas,
12:50
and other students would answer those questions.
280
754310
2424
e outros estudantes
tiñan que respondelas.
12:52
And the really amazing thing is,
281
756734
1713
E o máis abraiante é que,
12:54
because there were so many students,
282
758447
1670
como había tantos estudantes,
12:56
it means that even if a student posed a question
283
760117
2365
isto implicaba que mesmo
se un estudante poñía unha pregunta
12:58
at 3 o'clock in the morning,
284
762482
1632
ás 3 da mañá,
13:00
somewhere around the world,
285
764114
1582
nalgún punto do mundo
13:01
there would be somebody who was awake
286
765696
2074
habería alguén esperto
13:03
and working on the same problem.
287
767770
2313
e traballando no mesmo problema.
13:05
And so, in many of our courses,
288
770083
1958
Así que, en moitos dos nosos cursos,
13:07
the median response time for a question
289
772041
2329
o tempo medio de resposta
para unha pregunta
13:10
on the question and answer forum was 22 minutes.
290
774370
3418
no foro foi de 22 minutos.
13:13
Which is not a level of service I have ever offered to my Stanford students.
291
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4577
É un nivel de servizo que eu nunca lles
ofrecín aos meus estudantes de Stanford.
13:18
(Laughter)
292
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1341
(Risos)
13:19
And you can see from the student testimonials
293
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1942
E podedes ver nos testemuños
dos estudantes
13:21
that students actually find
294
785648
1687
que realmente cren
13:23
that because of this large online community,
295
787335
2521
que, grazas a esta enorme
comunidade en liña,
13:25
they got to interact with each other in many ways
296
789856
2599
puideron interactuar entre si
de moitas formas
13:28
that were deeper than they did in the context of the physical classroom.
297
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4193
que son máis profundas
das que hai no contexto da clase física.
13:32
Students also self-assembled,
298
796648
2344
Os estudantes tamén se agruparon,
13:34
without any kind of intervention from us,
299
798992
1863
sen ningún tipo de intervención nosa,
13:36
into small study groups.
300
800855
1903
en pequenos grupos de estudo.
13:38
Some of these were physical study groups
301
802758
2362
Algúns eran grupos de estudo presenciais
13:41
along geographical constraints
302
805120
1826
segundo as limitacións xeográficas
que se reunían cada semana
para traballar en series de problemas.
13:42
and met on a weekly basis to work through problem sets.
303
806946
2722
13:45
This is the San Francisco study group,
304
809668
1900
Este é o grupo de San Francisco,
13:47
but there were ones all over the world.
305
811568
2319
pero hainos por todo o mundo.
13:49
Others were virtual study groups,
306
813887
2032
Outros son grupos de estudo virtuais,
13:51
sometimes along language lines or along cultural lines,
307
815919
2989
formados segundo
trazos lingüísticos ou culturais
13:54
and on the bottom left there,
308
818908
1444
e na parte inferior esquerda
13:56
you see our multicultural universal study group
309
820352
3796
podedes ver o noso grupo de estudo
universal e multicultural
14:00
where people explicitly wanted to connect
310
824148
1763
onde a xente explicitamente quere conectar
14:01
with people from other cultures.
311
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3006
con xente doutras culturas.
14:04
There are some tremendous opportunities
312
828917
2111
Hai enormes oportunidades
14:06
to be had from this kind of framework.
313
831028
3325
que xorden deste tipo de contexto.
14:10
The first is that it has the potential of giving us
314
834353
3654
A primeira é que ten o potencial de darnos
14:13
a completely unprecedented look
315
838007
2434
unha mirada sen precedentes
14:16
into understanding human learning.
316
840441
2289
para entender a aprendizaxe humana.
14:18
Because the data that we can collect here is unique.
317
842730
3463
Porque os datos que podemos
conseguir aquí son únicos.
14:22
You can collect every click, every homework submission,
318
846193
4009
Podemos analizar cada clic,
cada envío de tarefas,
14:26
every forum post from tens of thousands of students.
319
850202
4363
cada publicación no foro
de decenas de miles de estudantes.
14:30
So you can turn the study of human learning
320
854565
2343
Así, no estudo da aprendizaxe humana
14:32
from the hypothesis-driven mode
321
856908
1933
podemos pasar de partir de hipóteses
14:34
to the data-driven mode, a transformation that,
322
858841
2858
a traballar desde os datos,
unha transformación que,
14:37
for example, has revolutionized biology.
323
861699
3041
por exemplo, revolucionou a bioloxía.
14:40
You can use these data to understand fundamental questions
324
864740
3424
Podemos usar estes datos
para entender preguntas fundamentais
14:44
like, what are good learning strategies
325
868164
1880
como cales son
as estratexias de aprendizaxe
14:45
that are effective versus ones that are not?
326
870044
2696
máis efectivas e cales non.
14:48
And in the context of particular courses,
327
872740
2240
E no contexto de cursos concretos,
14:50
you can ask questions
328
874980
1537
podemos facer preguntas
14:52
like, what are some of the misconceptions that are more common
329
876517
3255
como cales son
as equivocacións máis comúns
14:55
and how do we help students fix them?
330
879772
2177
e como axudamos aos estudantes
a resolvelas.
Este é un exemplo disto,
14:57
So here's an example of that,
331
881949
1424
do curso de Aprendizaxe Automática
de Andrew.
14:59
also from Andrew's Machine Learning class.
332
883373
2016
15:01
This is a distribution of wrong answers
333
885389
2208
Esta é unha distribución
de respostas erradas
15:03
to one of Andrew's assignments.
334
887597
1610
para unha das tarefas de Andrew.
As respostas resultan ser
pares de números,
15:05
The answers happen to be pairs of numbers,
335
889207
1893
15:07
so you can draw them on this two-dimensional plot.
336
891100
2271
así que podemos velas
nesta gráfica bidimensional.
15:09
Each of the little crosses that you see is a different wrong answer.
337
893371
3778
Cada pequena cruz
é unha resposta incorrecta diferente.
15:13
The big cross at the top left
338
897149
2406
A cruz grande na parte superior esquerda
15:15
is where 2,000 students
339
899555
2148
é onde 2 000 estudantes
15:17
gave the exact same wrong answer.
340
901703
3045
deron exactamente
a mesma resposta incorrecta.
15:20
Now, if two students in a class of 100
341
904748
2327
Agora, se dous estudantes
nunha clase de 100
15:22
give the same wrong answer,
342
907075
1287
cometesen o mesmo erro,
15:24
you would never notice.
343
908362
1351
nunca nos decatariamos.
15:25
But when 2,000 students give the same wrong answer,
344
909713
2560
Mais cando 2 000 estudantes
dan a mesma resposta errada,
15:28
it's kind of hard to miss.
345
912273
1697
é difícil non darse conta.
15:29
So Andrew and his students went in,
346
913970
2192
Así que Andrew e os seus estudantes
15:32
looked at some of those assignments,
347
916162
1520
analizaron algunhas desas tarefas,
15:33
understood the root cause of the misconception,
348
917682
4088
entenderon a raíz dos equívocos
15:37
and then they produced a targeted error message
349
921770
2520
e crearon unha mensaxe de erro específica
15:40
that would be provided to every student
350
924290
2249
que lles aparecería aos estudantes
15:42
whose answer fell into that bucket,
351
926539
2179
cuxa resposta caera nese caixón.
15:44
which means that students who made that same mistake
352
928718
2084
É dicir, os estudantes
que cometían o mesmo erro
15:46
would now get personalized feedback
353
930802
2026
agora terían
unha retroalimentación personalizada
15:48
telling them how to fix their misconception much more effectively.
354
932828
4399
que lles diría como solucionar
ese erro de xeito eficaz.
15:53
So this personalization is something that one can then build
355
937227
3811
Así que esta personalización
é algo que podemos construír
15:56
by having the virtue of large numbers.
356
941038
3140
grazas a termos estes grandes números.
16:00
Personalization is perhaps
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2312
A personalización é, talvez,
16:02
one of the biggest opportunities here as well,
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2423
unha das maiores oportunidades aquí
16:04
because it provides us with the potential
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948913
2345
porque nos permite resolver un problema
16:07
of solving a 30-year-old problem.
360
951258
2690
que temos desde hai 30 anos.
16:09
Educational researcher Benjamin Bloom, in 1984,
361
953948
3349
O investigador educativo
Benjamin Bloom, en 1984,
16:13
posed what's called the 2 sigma problem,
362
957297
2251
expuxo o que se chamou
o problema 2 sigma,
16:15
which he observed by studying three populations.
363
959548
3062
que observou ao estudar
tres grupos de estudantes.
16:18
The first is the population that studied in a lecture-based classroom.
364
962610
3608
O primeiro estudaba
nunha aula baseada en leccións.
16:22
The second is a population of students that studied
365
966218
2777
O segundo era un grupo
de alumnos que estudaba
nunha aula baseada en leccións estándar
16:24
using a standard lecture-based classroom,
366
968995
1719
pero cun enfoque orientado
ao dominio do contido,
16:26
but with a mastery-based approach,
367
970714
2080
16:28
so the students couldn't move on to the next topic
368
972794
1920
onde os estudantes non podían
pasar ao seguinte tema
16:30
before demonstrating mastery of the previous one.
369
974714
3354
se non demostraban
que dominaban o anterior.
16:33
And finally, there was a population of students
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978068
2294
E, finalmente, había
un grupo de estudantes
16:36
that were taught in a one-on-one instruction using a tutor.
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980362
4528
aos que se lles daba instrución
individual a través dun titor.
16:40
The mastery-based population was a full standard deviation,
372
984890
3272
O grupo baseado no dominio obtivo
un desvío padrón total,
16:44
or sigma, in achievement scores better
373
988162
2288
ou sigma, superior en rendemento
16:46
than the standard lecture-based class,
374
990450
2394
que o grupo baseado
en leccións convencionais,
16:48
and the individual tutoring gives you 2 sigma
375
992844
2144
e a titoría individual deu
unha mellora
16:50
improvement in performance.
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994988
1830
sigma 2 en rendemento.
16:52
To understand what that means,
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996818
1463
Para entender o que significa,
16:54
let's look at the lecture-based classroom,
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998281
1833
vexamos a clase baseada en leccións,
16:56
and let's pick the median performance as a threshold.
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1000114
2919
tomando o rendemento medio como limiar.
16:58
So in a lecture-based class,
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1003033
1338
Nunha clase baseada en leccións,
17:00
half the students are above that level and half are below.
381
1004371
3879
a metade dos estudantes están
por riba dese limiar e a metade por baixo.
17:04
In the individual tutoring instruction,
382
1008250
2098
Na instrución de titoría individual,
17:06
98 percent of the students are going to be above that threshold.
383
1010348
4801
o 98 % dos estudantes están
por riba dese limiar.
17:11
Imagine if we could teach so that 98 percent of our students
384
1015149
3920
Imaxinade que puidésemos ensinar
de xeito que o 98 % dos estudantes
17:14
would be above average.
385
1019069
2198
estivesen por riba da media.
17:17
Hence, the 2 sigma problem.
386
1021267
3423
Este é o problema sigma 2.
17:20
Because we cannot afford, as a society,
387
1024690
2399
Porque non podemos permitirnos,
como sociedade,
17:22
to provide every student with an individual human tutor.
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1027089
3072
proporcionarlle a cada estudante
un titor humano individual.
Mais quizais poidamos permitirnos
darlle a cada un
17:26
But maybe we can afford to provide each student
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1030161
2249
17:28
with a computer or a smartphone.
390
1032410
2019
un computador ou un teléfono intelixente.
17:30
So the question is, how can we use technology
391
1034429
2189
A cuestión é:
Como podemos usar a tecnoloxía
17:32
to push from the left side of the graph, from the blue curve,
392
1036618
3375
para ir desde o lado esquerdo da gráfica,
desde a curva azul,
17:35
to the right side with the green curve?
393
1039993
2738
ao lado dereito coa curva verde?
17:38
Mastery is easy to achieve using a computer,
394
1042731
2337
O dominio é fácil de acadar
usando un computador,
17:40
because a computer doesn't get tired
395
1045068
1405
porque un computador non se cansa
17:42
of showing you the same video five times.
396
1046473
3073
de amosar o mesmo vídeo cinco veces.
17:45
And it doesn't even get tired of grading the same work multiple times,
397
1049546
3251
E non se cansa de avaliar
o mesmo traballo múltiples veces,
17:48
we've seen that in many of the examples that I've shown you.
398
1052802
3026
como vimos en moitos dos exemplos
que vos amosei.
17:51
And even personalization
399
1055828
1854
E mesmo a personalización
17:53
is something that we're starting to see the beginnings of,
400
1057682
2136
é algo cuxos comezos empezamos a ver,
17:55
whether it's via the personalized trajectory through the curriculum
401
1059818
3192
a través da traxectoria
personalizada polo currículo
17:58
or some of the personalized feedback that we've shown you.
402
1063010
3264
ou a través da retroalimentación
personalizada.
18:02
So the goal here is to try and push,
403
1066274
2488
Así que o obxectivo aquí
é intentar empurrar
18:04
and see how far we can get towards the green curve.
404
1068762
3497
e ver o lonxe que podemos
chegar cara á curva verde.
18:08
So, if this is so great, are universities now obsolete?
405
1072259
5359
Pero, se isto é tan estupendo,
estarán as universidades obsoletas?
18:13
Well, Mark Twain certainly thought so.
406
1077618
2992
Ben, Mark Twain pensaba iso.
Dicía: "A universidade é un lugar
onde os apuntamentos dun profesor
18:16
He said that, "College is a place where a professor's lecture notes
407
1080610
2545
18:19
go straight to the students' lecture notes,
408
1083155
1703
van directamente
aos apuntamentos dun estudante
18:20
without passing through the brains of either."
409
1084858
2376
sen pasar polo cerebro
de ningún deles."
18:23
(Laughter)
410
1087234
4047
(Risos)
18:27
I beg to differ with Mark Twain, though.
411
1091281
2668
Aínda que eu lamento
disentir de Mark Twain.
18:29
I think what he was complaining about is not
412
1093949
2665
Penso que el non se queixaba
18:32
universities but rather the lecture-based format
413
1096614
2750
das universidades senón
do formato de clase maxistral
18:35
that so many universities spend so much time on.
414
1099364
2784
en que moitas universidades
invisten gran parte do tempo.
18:38
So let's go back even further, to Plutarch,
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1102148
3159
Así que imos cara a atrás
un pouco, ata Plutarco, que dixo:
"A mente non é un recipiente
que hai que encher
18:41
who said that, "The mind is not a vessel that needs filling,
416
1105307
2227
senón madeira que necesita
ser acendida."
18:43
but wood that needs igniting."
417
1107534
2023
Talvez deberiamos investir
menos tempo nas universidades
18:45
And maybe we should spend less time at universities
418
1109557
2190
18:47
filling our students' minds with content
419
1111747
2571
a encher as mentes
dos nosos estudantes con contido
18:50
by lecturing at them, and more time igniting their creativity,
420
1114318
3800
a través de leccións, e máis tempo
a acender a súa creatividade,
18:54
their imagination and their problem-solving skills
421
1118118
3255
a súa imaxinación e as súas destrezas
na resolución de problemas
18:57
by actually talking with them.
422
1121373
2498
conversando, realmente, con eles.
18:59
So how do we do that?
423
1123871
1367
Entón, como o facemos?
19:01
We do that by doing active learning in the classroom.
424
1125238
3431
Facémolo a través
da aprendizaxe activa na aula.
19:04
So there's been many studies, including this one,
425
1128669
2449
Houbo moitos estudos, incluído este,
19:07
that show that if you use active learning,
426
1131118
2080
que demostran que coa aprendizaxe activa,
19:09
interacting with your students in the classroom,
427
1133198
2416
cando interactuamos
cos nosos estudantes na aula,
19:11
performance improves on every single metric --
428
1135614
2696
o rendemento mellora
en todas as dimensións,
19:14
on attendance, on engagement and on learning
429
1138310
2449
en asistencia, en compromiso
e en aprendizaxe
19:16
as measured by a standardized test.
430
1140759
2055
medidos en probas estandarizadas.
19:18
You can see, for example, that the achievement score
431
1142814
1864
Vedes, por exemplo,
que o nivel de rendemento
19:20
almost doubles in this particular experiment.
432
1144678
2870
case se duplica
neste experimento concreto.
19:23
So maybe this is how we should spend our time at universities.
433
1147548
4401
Entón, quizais é así como deberiamos
usar o noso tempo nas universidades.
19:27
So to summarize, if we could offer a top quality education
434
1151949
4577
Para resumir, se puidésemos ofrecer
unha educación de alta calidade
19:32
to everyone around the world for free,
435
1156526
1903
para todas as persoas do mundo, de balde,
19:34
what would that do? Three things.
436
1158429
2821
que suporía? Tres cousas.
19:37
First it would establish education as a fundamental human right,
437
1161250
3421
Primeiro, estableceríase a educación
como un dereito humano fundamental,
19:40
where anyone around the world
438
1164671
1366
calquera persoa ao redor do mundo
19:41
with the ability and the motivation
439
1166037
1921
con capacidades e motivación
19:43
could get the skills that they need
440
1167958
1951
podería desenvolver
as destrezas que precisase
19:45
to make a better life for themselves,
441
1169909
1585
para mellorar a súa vida,
19:47
their families and their communities.
442
1171494
2017
a das súas familias e
a das súas comunidades.
19:49
Second, it would enable lifelong learning.
443
1173511
2631
Segundo, faría posible
a aprendizaxe ao longo da vida.
19:52
It's a shame that for so many people,
444
1176142
1951
É unha vergoña que, para tantas persoas,
19:53
learning stops when we finish high school or when we finish college.
445
1178093
3312
a aprendizaxe remate ao finalizar
o ensino medio ou a universidade.
19:57
By having this amazing content be available,
446
1181405
2481
O feito de termos dispoñible
este asombroso contido,
19:59
we would be able to learn something new
447
1183886
2743
permítenos aprender algo novo
20:02
every time we wanted,
448
1186629
1136
cando o desexemos,
20:03
whether it's just to expand our minds
449
1187765
1329
para simplemente expandir a mente
20:04
or it's to change our lives.
450
1189094
1959
ou para cambiar as nosas vidas.
20:06
And finally, this would enable a wave of innovation,
451
1191053
3145
E, finalmente, isto faría posible
unha marea de innovación,
20:10
because amazing talent can be found anywhere.
452
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3072
xa que podemos atopar
un asombroso talento en calquera parte.
20:13
Maybe the next Albert Einstein or the next Steve Jobs
453
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3008
Quizais o próximo Albert Einstein ou
o próximo Steve Jobs
20:16
is living somewhere in a remote village in Africa.
454
1200278
2615
estea vivindo nalgún lugar
nunha remota aldea de África.
20:18
And if we could offer that person an education,
455
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2656
E se podemos ofrecerlle
a esa persoa unha educación,
20:21
they would be able to come up with the next big idea
456
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2356
poderá ser capaz de aparecer
coa próxima grande idea
20:23
and make the world a better place for all of us.
457
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2404
e facer do mundo un lugar
mellor para todos nós.
20:26
Thank you very much.
458
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1160
Moitas grazas.
20:27
(Applause)
459
1211469
7583
(Aplausos)
Translated by Carme Paz
Reviewed by Mario Cal

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ABOUT THE SPEAKER
Daphne Koller - Educator
With Coursera, Daphne Koller and co-founder Andrew Ng are bringing courses from top colleges online, free, for anyone who wants to take them.

Why you should listen

A 3rd generation Ph.D who is passionate about education, Stanford professor Daphne Koller is excited to be making the college experience available to anyone through her startup, Coursera. With classes from 85 top colleges, Coursera is an innovative model for online learning. While top schools have been putting lectures online for years, Coursera's platform supports the other vital aspect of the classroom: tests and assignments that reinforce learning.

At the Stanford Artificial Intelligence Laboratory, computer scientist Daphne Koller studies how to model large, complicated decisions with lots of uncertainty. (Her research group is called DAGS, which stands for Daphne's Approximate Group of Students.) In 2004, she won a MacArthur Fellowship for her work, which involves, among other things, using Bayesian networks and other techniques to explore biomedical and genetic data sets.

More profile about the speaker
Daphne Koller | Speaker | TED.com