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ELIZABETH CHOE: All right, so
everyone is here for 20.219,

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correct, Becoming
the Next Bill Nye?

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No one's in the wrong room?

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All right.

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OK, well, welcome to the class.

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I'm Elizabeth, I run
the K12 videos program.

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Maybe we can do a quick intro
with the staff over here.

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00:00:47,610 --> 00:00:48,569
So Jamie, you want to--

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JAIME GOLDSTEIN: Hi,
I'm Jaime Goldstein.

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I run the communication lab
in Biological Engineering,

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and I oversee it in Nuclear
Science and Engineering

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as well.

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CERI RILEY: I'm Ceri.

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I am the TA for this class.

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I'm a junior in Comparative
Media Studies and Biology.

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JOSH GUNN: I'm Josh.

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00:01:06,000 --> 00:01:08,650
I run an animation
studio here in Cambridge

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called Planet Nutshell.

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CHRIS BOEBEL: I'm Chris Boebel.

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I'm Media Development
Director at MITx,

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and I also teach a
class here at MIT

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called DV Lab on
documentary, and I'll

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be guest lecturing for
a couple of sessions.

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ELIZABETH CHOE: Come
on in, take a seat.

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So just logistics stuff.

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All the information
about this class

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is on our Tumblr, which I'll
email it out to you guys,

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but it's mit219.tumblr.com.

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And you'll find the class
syllabus, all the links,

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all the videos that I'll be
showing you during class,

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and basically
everything you need

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00:01:44,490 --> 00:01:46,480
to know about just
homework assignments

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and things like that.

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So we're just going to go
ahead and dive right in.

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This class is about writing,
hosting, and producing video,

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short-form video, but in the
context of this sort of scary,

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amorphous blob that people
talk about a lot, the problems

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in science, technology, and
engineering and math education.

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And the specific
problems that we're

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going to be trying
to be thinking

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about in the context
of making these videos

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are these three
problems, which is

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that the culture that we
have right now, especially

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with video and science,
is that it kind of implies

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that the door to
science and engineering,

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whether or not you
want to be a scientist

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or whether or not
you want to study it,

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is only open to certain people.

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We also have this
issue of maintaining

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a love of lifelong learning.

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Josh I were just talking
about the dark ages, when

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you quit playing with LEGOs.

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But kids are very
curious creatures,

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and somehow our
educational system

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squelches that curiosity.

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And science and engineering
are these topics

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that I'm sure you guys
are very excited about.

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I'm very excited about it too.

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But somehow it becomes this
sort of boring subject,

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and especially in high school,
people think of chemistry

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as their least favorite class.

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It was my least favorite
class in high school.

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And then you have this
civic responsibility

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as scientists and
engineers to make sure

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that you're promoting STEM
literacy among the public.

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We don't want everyone
in our culture

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to become a scientist
or an engineer.

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That would be terrible,
it would be super boring.

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It wouldn't really be
helping our society at all.

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But at the same time,
science and engineering

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affects your daily life.

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Whether or not you're an
artist or you're an author,

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you're voting on issues that
require a certain knowledge

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of science and engineering.

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And as scientists
and engineers, we

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need to be making
sure that we're

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promoting a basic
level of literacy

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among the voting public.

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So it's a practical
thing for us,

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as scientists and engineers.

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It's also sharing that
excitement and love

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of learning with other
people that maybe they

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lost in a boring class
or something like that.

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So the idea of this class
is to bring together

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the best practices in education,
and some of these problems

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that I'm talking about
with STEM education,

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and bringing it together
with some of the tools

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that we have in entertainment.

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So how can we use video, how
can we leverage video to address

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that big, amorphous blob.

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So we're going to try to
occupy this middle space.

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But the problem is that the best
practices in this middle space

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have not really
been established.

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Part of that is because
there aren't really experts

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in edutainment, necessarily.

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It's not a super academic field.

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It's also pretty new.

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The advent of science
entertainment on the web,

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especially now it's exploding,
but it's all very new,

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so it's hard to establish
the best practices.

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And on top of that, the
best practices in education

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and the best practices
in entertainment

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don't always align.

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A lot of times they
conflict with each other.

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So a lot of this class
will be piecing together

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what's great about
these two disciplines,

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and it'll also be sort
of discovering on our own

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what are the pieces that we
want to take and implement

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ourselves.

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At this point, I wanted you guys
to think about this question,

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partially to inform us
and help us help you guys

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over the course of this month.

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But I wanted to get a
sense of why you all

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signed up for this class.

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Maybe it was because you needed
six extra units to graduate,

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which is totally fine.

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And also what you wanted
to get out of this class.

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If you're coming into
the class and you

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want to learn how
to record video,

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we want to know if
that's your objective.

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If you came in
because you thought

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it sounded interesting
or anything like that,

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we want to know, too.

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So you guys can think
about it, maybe share.

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If you don't want to share
right now, that's totally fine.

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But I will mention this
at the end of class,

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but every day you're
going to be writing

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blog posts and
daily reflections,

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so hopefully this is something
that you can incorporate

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into your reflection today.

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JAIME GOLDSTEIN: Elizabeth,
why don't you start?

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Why are you here?

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ELIZABETH CHOE: Why am I here?

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Well, I'm going to talk about
why I'm here after this,

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so I don't want to spoil it.

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But Jaime, why are you here?

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JAIME GOLDSTEIN: Oh, OK.

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Really good question.

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I run the communication lab
in Biological Engineering,

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and that was it.

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I oversee Nuclear
Science as well.

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And our goal is really to help
scientists learn to communicate

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more effectively.

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And that's what I do now.

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I mostly train graduate
students to talk

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to each other about their
science, and to undergraduates,

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about how do you tell people
about what you're doing.

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And when Elizabeth approached
me-- she was an MBE originally,

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so she knew about our lab.

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This was a perfect match for
me personally, this course,

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because prior to my
life here I taught

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middle school for many years,
among the many other things.

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I was a magazine editor
for a little while.

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So this to me is a perfect
intersection of things

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that I'm passionate about,
because your videos are

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targeted, that
you're going to be

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making for that middle
school population.

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And that's one that
I know very well

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and that I care about a lot.

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So I'm looking forward
to sharing with you

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what I know about the work that
I do now blended with the work

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that I used to do.

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So I'm excited to tap
into your creativity.

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ELIZABETH CHOE: Anyone else
want to share why they're here?

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No wrong answers.

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PAUL FOLINO: My
name's Paul Folino.

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I came here to, kind of
on what you were saying,

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just try to be able to
convey technical concepts

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in a simple way, so I
can explain to someone,

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whether it's one of
my friends or someone

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like my niece, what I do.

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ELIZABETH CHOE: Awesome.

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Anyone else?

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You will have to stay
it in your blog, though.

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JAIME GOLDSTEIN: I want
to hear from everyone.

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JOSH CHEONG: I'll
probably go first.

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JAIME GOLDSTEIN: Sure.

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ELIZABETH CHOE: And
what's your name?

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Sorry.

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JOSH CHEONG: My name is Joshua.

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ELIZABETH CHOE: Joshua.

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JOSH CHEONG: You
can call me Josh.

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I come from Singapore.

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So we're here on a really short
exchange for about a month.

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We come from
Singapore University

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of Technology and Design.

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It's a university that was
started in collaboration

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with MIT.

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Well, I came to this class
because we study OCW a lot,

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and that's because
we are probably

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the first [? special ?]
university and most

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of our curriculum
comes from MIT.

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And honestly, I feel like
close to 25% of my education

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comes from online.

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And I'm very
comfortable with it,

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but-- my mom is a
chemistry teacher,

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and she tells me that
students don't necessarily

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like stuff like Khan
Academy, because it

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might look too boring for them.

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And that's kind of my
curiosity right now,

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how do I convey something
that people might not

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find really interesting but
very important for them,

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and make it very interactive.

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ELIZABETH CHOE:
It's Yuliya, right?

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YULIYA KLOCHAN: Mm-hm.

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So I was very interested in
education in high school,

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and I noticed that kids don't
like STEM subjects, generally.

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And so I just wanted
to, as a career,

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pursue promotion
of STEM subjects.

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That's one of the
things I'd like to do.

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ELIZABETH CHOE: Yes.

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JONATHAN: Hi, I'm Jonathan.

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ELIZABETH CHOE:
Did you say John?

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Josh?

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JONATHAN: Jonathan.

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ELIZABETH CHOE: John.

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JONATHAN: John is fine, too.

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So I noticed there were a number
of videos on YouTube popping

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up, a number of
educational videos in range

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from exciting to pretty boring.

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And I think this is a
very powerful medium

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to reach kids who
wouldn't normally be

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interested in science, or math.

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And exposure, and
how you receive

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and where you get
information, usually

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tends to tip the scales as
far as who's into something

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and who's not.

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So I think this is a
really cool project.

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And I like to be on the other
side of the camera as well.

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ANDREA DESROSIERS: I
guess I'll go next.

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My name is Andrea.

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I'm a Sloan Fellow here at MIT.

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So I'm significantly older
than maybe everybody.

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What I've been doing for
the past 10 years of my life

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has been working in regulatory,
so doing medical device

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submissions to the FDA.

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So it's a lot of communicating
highly technical information

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00:10:41,860 --> 00:10:44,530
to people who aren't
exactly laypeople,

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00:10:44,530 --> 00:10:47,730
but they're not going to be
as familiar with the topic

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00:10:47,730 --> 00:10:48,560
as, say, I am.

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00:10:48,560 --> 00:10:50,050
So that's what I've been doing.

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And one of the things that
I'd really like to introduce

250
00:10:53,380 --> 00:10:56,942
is using video as another tool
to convey this information.

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00:11:04,718 --> 00:11:06,662
NATHAN HERNANDEZ:
Hi, I'm Nathan.

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00:11:06,662 --> 00:11:11,432
I think why I'm taking this
class is [INAUDIBLE] spread

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00:11:11,432 --> 00:11:13,787
scientific information, too.

254
00:11:13,787 --> 00:11:16,340
At least for me, I think,
not necessarily people

255
00:11:16,340 --> 00:11:19,707
who adore the science, but
just people so they can

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00:11:19,707 --> 00:11:22,112
be scientifically literate now.

257
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I don't know.

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00:11:28,365 --> 00:11:32,690
KENNETH CHEAH: Hi, I'm
Kenneth, from SUTD as well.

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00:11:32,690 --> 00:11:35,260
Back when I first graduated
from junior college,

260
00:11:35,260 --> 00:11:38,760
I actually went to have
a teaching internship

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00:11:38,760 --> 00:11:40,790
for a period in
Singapore, and that's

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00:11:40,790 --> 00:11:43,640
when I realized that most
students in Singapore

263
00:11:43,640 --> 00:11:48,890
do not really like blackboard
or whiteboard teaching.

264
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I realized that a
little-- like halfway

265
00:11:51,220 --> 00:11:53,440
into my first week of
doing the internship,

266
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so that's when I revised
everything that I had prepared,

267
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started creating multimedia
tools and animations.

268
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It's been like two,
three years since then.

269
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But the whole idea of
using multimedia as well

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as video tools has
still stuck around.

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I still regularly,
when I'm bored

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00:12:10,870 --> 00:12:13,328
and I don't feel like doing my
homework, I'll go on YouTube

273
00:12:13,328 --> 00:12:14,830
and watch all these
random videos,

274
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because at least I learn
something; not relevant,

275
00:12:17,070 --> 00:12:19,730
but something.

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00:12:19,730 --> 00:12:21,710
So this has always
been an interest.

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ELIZABETH CHOE: Does anyone
have any particular goals

278
00:12:26,900 --> 00:12:29,260
out of this month or something
that you want to get out

279
00:12:29,260 --> 00:12:30,285
of taking this class?

280
00:12:43,889 --> 00:12:44,780
That's OK.

281
00:12:44,780 --> 00:12:46,392
We'll give you
goals, don't worry.

282
00:12:49,560 --> 00:12:52,835
All right, well, I won't
torture you any further.

283
00:12:52,835 --> 00:12:54,376
JOSH GUNN: I'll just
mention that I'm

284
00:12:54,376 --> 00:12:55,594
excited about the class.

285
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I run an animation
studio, as I said,

286
00:12:58,690 --> 00:13:01,040
and we do this work every day.

287
00:13:01,040 --> 00:13:05,750
We're engaged in helping
biotechs and technology

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00:13:05,750 --> 00:13:10,660
companies and educators
explain very complex things,

289
00:13:10,660 --> 00:13:15,129
and sometimes not-so-complex
things, to very young kids.

290
00:13:15,129 --> 00:13:16,670
But I certainly
don't have the market

291
00:13:16,670 --> 00:13:18,550
cornered on how to do this.

292
00:13:18,550 --> 00:13:21,390
And as you said, this isn't
really an academic field,

293
00:13:21,390 --> 00:13:23,956
and there's no grand
unified theory of how

294
00:13:23,956 --> 00:13:25,872
to do this most effectively.

295
00:13:25,872 --> 00:13:27,872
I think a lot of things
are out there right now,

296
00:13:27,872 --> 00:13:32,713
but I'm just excited
to be engaged

297
00:13:32,713 --> 00:13:35,671
in a conversation about
techniques and strategies

298
00:13:35,671 --> 00:13:38,629
for doing this, because
they'll help me in my own work,

299
00:13:38,629 --> 00:13:43,560
and help me understand the
perspective that you guys have

300
00:13:43,560 --> 00:13:44,065
as well.

301
00:13:44,065 --> 00:13:47,675
So thanks.

302
00:13:47,675 --> 00:13:48,870
ELIZABETH CHOE: Great.

303
00:13:48,870 --> 00:13:51,620
As I said in the beginning,
I run the K12 videos program,

304
00:13:51,620 --> 00:13:56,477
which is a fairly new initiative
out of the Office of Digital

305
00:13:56,477 --> 00:13:57,060
Learning here.

306
00:13:57,060 --> 00:13:58,580
So it's the same
group that oversees

307
00:13:58,580 --> 00:13:59,640
MITx and OpenCourseWare.

308
00:14:02,250 --> 00:14:05,050
I produce a series called
Science Out Loud, which

309
00:14:05,050 --> 00:14:10,680
is essentially trying to mix
education and entertainment,

310
00:14:10,680 --> 00:14:14,230
having students like you
guys be the face of science

311
00:14:14,230 --> 00:14:15,790
and the face of engineering.

312
00:14:15,790 --> 00:14:19,810
And to get people not only
educated and informed, but also

313
00:14:19,810 --> 00:14:21,930
inspired as well.

314
00:14:21,930 --> 00:14:25,170
So I've had an interest
in the intersection

315
00:14:25,170 --> 00:14:27,660
of all that stuff, I guess,
since I took Chris' class.

316
00:14:27,660 --> 00:14:30,710
When I was an undergrad
I took his DV Lab class.

317
00:14:30,710 --> 00:14:32,830
But I think it's a
very fascinating area.

318
00:14:32,830 --> 00:14:34,390
And like Josh said,
it's this market

319
00:14:34,390 --> 00:14:37,190
that I don't think anyone
really has cornered

320
00:14:37,190 --> 00:14:41,680
or really-- no one really has
a good grasp on what the best

321
00:14:41,680 --> 00:14:44,200
way to practice in it is.

322
00:14:44,200 --> 00:14:46,250
So I think it's a really
interesting problem,

323
00:14:46,250 --> 00:14:49,480
especially for people at
MIT to think about, as well.

324
00:14:52,560 --> 00:14:55,580
As some of you guys said,
videos have exploded

325
00:14:55,580 --> 00:14:57,470
in the last decade or so.

326
00:14:57,470 --> 00:15:00,020
These are all science
YouTube channels

327
00:15:00,020 --> 00:15:03,720
that have over a million
subscribers each.

328
00:15:03,720 --> 00:15:08,040
And it's not just video
exploding in a certain area.

329
00:15:08,040 --> 00:15:11,680
You have YouTube entertainment
slash educational shows,

330
00:15:11,680 --> 00:15:17,200
and then you have things that
are very lucrative in our pop

331
00:15:17,200 --> 00:15:17,700
culture.

332
00:15:17,700 --> 00:15:20,700
Cosmos was raking in like
five million viewers a week.

333
00:15:20,700 --> 00:15:24,070
Which isn't a whole
lot compared to some

334
00:15:24,070 --> 00:15:26,050
of the other primetime
network shows,

335
00:15:26,050 --> 00:15:30,900
but thinking about the fact
that a science-based show aired

336
00:15:30,900 --> 00:15:33,400
on the FOX Network
during a primetime slot

337
00:15:33,400 --> 00:15:36,130
and was raking in those
views is pretty amazing.

338
00:15:36,130 --> 00:15:38,440
And then you have movies
like Interstellar,

339
00:15:38,440 --> 00:15:42,540
which are addressing a lot
of real science topics,

340
00:15:42,540 --> 00:15:46,820
and is also making like $50
million during opening weekend.

341
00:15:46,820 --> 00:15:49,780
And then you have things
like edX and OpenCourseWare,

342
00:15:49,780 --> 00:15:52,450
and all these open
education resources that

343
00:15:52,450 --> 00:15:55,540
are video-based, and
are also reaching

344
00:15:55,540 --> 00:15:59,790
this incredible audience
and have a huge group

345
00:15:59,790 --> 00:16:01,730
of people investing in it.

346
00:16:01,730 --> 00:16:04,880
And these are all very, very
different styles of video,

347
00:16:04,880 --> 00:16:08,170
but they're all unified by this
theme that they're using video

348
00:16:08,170 --> 00:16:12,680
and they're accumulating
a huge database of users.

349
00:16:12,680 --> 00:16:16,070
So something must be
happening with video

350
00:16:16,070 --> 00:16:17,850
that's making it
compelling for people

351
00:16:17,850 --> 00:16:21,540
to use to learn
and to entertain.

352
00:16:21,540 --> 00:16:23,300
What can video do?

353
00:16:23,300 --> 00:16:25,090
What is it about
video that makes it

354
00:16:25,090 --> 00:16:27,530
so compelling to use as a tool?

355
00:16:27,530 --> 00:16:31,410
Educationally, you have stuff
like OpenCourseWare that's

356
00:16:31,410 --> 00:16:35,570
really great, because people
can pause the video whenever

357
00:16:35,570 --> 00:16:39,500
they want, they can rewind
and rewatch an explanation.

358
00:16:39,500 --> 00:16:41,180
And it's also super
scalable, so it

359
00:16:41,180 --> 00:16:44,330
means that you don't have to
be physically in Cambridge

360
00:16:44,330 --> 00:16:47,946
to hear Eric Lander talk about
genetics in the 7.012 class.

361
00:16:47,946 --> 00:16:49,320
You can be anywhere
in the world.

362
00:16:49,320 --> 00:16:51,010
You can be in Singapore.

363
00:16:51,010 --> 00:16:54,871
You don't have to be restricted
to the confines of room 26-100,

364
00:16:54,871 --> 00:16:55,370
right?

365
00:16:55,370 --> 00:16:59,910
It's a very scalable tool.

366
00:16:59,910 --> 00:17:03,840
And then in terms of movies,
I mean the thing about movies

367
00:17:03,840 --> 00:17:08,050
is we have this culture where
people say that the attention

368
00:17:08,050 --> 00:17:11,890
span for video is like less than
three minutes, yet you and I--

369
00:17:11,890 --> 00:17:15,210
or at least I spend
$10 to sit for two,

370
00:17:15,210 --> 00:17:17,130
three hours in a dark room.

371
00:17:17,130 --> 00:17:19,770
And it's because movies are
these completely immersive

372
00:17:19,770 --> 00:17:22,099
experiences that
give us a chance

373
00:17:22,099 --> 00:17:23,910
to sort of escape
into this other world.

374
00:17:23,910 --> 00:17:26,440
And you don't see
people paying $10

375
00:17:26,440 --> 00:17:29,750
to sit in a room to listen
to a radio podcast, right?

376
00:17:29,750 --> 00:17:31,840
There's something
about the integration

377
00:17:31,840 --> 00:17:34,210
of the visual with the
storytelling and the acting

378
00:17:34,210 --> 00:17:36,250
that totally immerses
you in this experience,

379
00:17:36,250 --> 00:17:42,670
and that's a very, very powerful
element that video can do.

380
00:17:42,670 --> 00:17:45,400
I also think it's a
window into a world

381
00:17:45,400 --> 00:17:48,000
that you don't necessarily
have access to.

382
00:17:48,000 --> 00:17:51,420
So whether it's
the world of 26-100

383
00:17:51,420 --> 00:17:53,660
where Eric Lander is
teaching or if it's

384
00:17:53,660 --> 00:17:57,950
the world of Middle
Earth-- I just

385
00:17:57,950 --> 00:18:01,810
went and saw Hobbit III--
you get this chance to look

386
00:18:01,810 --> 00:18:03,850
into this world that you
don't have access to,

387
00:18:03,850 --> 00:18:06,090
and that's what video can do.

388
00:18:06,090 --> 00:18:09,230
And then, finally, especially
in nonfiction video,

389
00:18:09,230 --> 00:18:11,800
there's this idea of
the trusted guide, which

390
00:18:11,800 --> 00:18:16,004
is a term that PBS Kids use
to think about new shows

391
00:18:16,004 --> 00:18:16,670
that they pitch.

392
00:18:16,670 --> 00:18:18,130
They think about
the person who's

393
00:18:18,130 --> 00:18:21,290
going to be the host, that it's
more than just the person who's

394
00:18:21,290 --> 00:18:24,080
going to stand and transfer
information to you.

395
00:18:24,080 --> 00:18:26,270
It's someone who's
relatable, somebody

396
00:18:26,270 --> 00:18:28,020
who's a role model,
someone who you really

397
00:18:28,020 --> 00:18:31,210
trust, that you end
up really growing up

398
00:18:31,210 --> 00:18:32,400
with people like Bill Nye.

399
00:18:32,400 --> 00:18:34,450
I don't know if
you guys have shows

400
00:18:34,450 --> 00:18:36,985
or show hosts that you
remember growing up as kids.

401
00:18:36,985 --> 00:18:37,860
Mine was Jeff Corwin.

402
00:18:37,860 --> 00:18:41,030
I'm like obsessed
with Jeff Corwin.

403
00:18:41,030 --> 00:18:43,240
Does anyone have a
figure that they really

404
00:18:43,240 --> 00:18:44,350
loved watching growing up?

405
00:18:47,410 --> 00:18:51,041
Did anyone watch the old
Cosmos with Carl Sagan?

406
00:18:51,041 --> 00:18:51,540
Yeah?

407
00:18:51,540 --> 00:18:54,960
I feel like that's a
big one for people here.

408
00:18:54,960 --> 00:18:57,490
So the trusted guide is
a really powerful thing

409
00:18:57,490 --> 00:18:59,750
that video can leverage.

410
00:18:59,750 --> 00:19:02,700
And I think that's a really
big reason why we're here,

411
00:19:02,700 --> 00:19:04,330
at least the reason
why I'm here,

412
00:19:04,330 --> 00:19:08,070
is because when you look at
the landscape of trusted guides

413
00:19:08,070 --> 00:19:12,020
right now on especially
science and technical TV,

414
00:19:12,020 --> 00:19:16,010
and not just TV but Hank Green
hosts SciShow on YouTube.

415
00:19:16,010 --> 00:19:19,550
And the landscape of trusted
guide looks very homogeneous.

416
00:19:19,550 --> 00:19:22,690
And I'm not saying that it's a
bad thing to be a guy at all,

417
00:19:22,690 --> 00:19:26,920
but I do think that we have
this opportunity with video

418
00:19:26,920 --> 00:19:31,470
to showcase who the scientists
and engineers really are.

419
00:19:31,470 --> 00:19:35,520
And this landscape
is building a group

420
00:19:35,520 --> 00:19:38,700
of advocates who
are going to be sort

421
00:19:38,700 --> 00:19:42,430
of being the ambassadors to
the public about what you're

422
00:19:42,430 --> 00:19:44,280
learning about and
what you're studying.

423
00:19:44,280 --> 00:19:48,180
And we have this opportunity
to create a landscape that's

424
00:19:48,180 --> 00:19:50,090
just as diverse as
the group of people

425
00:19:50,090 --> 00:19:52,580
it's trying to represent.

426
00:19:52,580 --> 00:19:55,930
And it's an opportunity that
I think hasn't necessarily

427
00:19:55,930 --> 00:19:57,840
been capitalized upon.

428
00:19:57,840 --> 00:20:00,350
Maybe it's because there
are political things

429
00:20:00,350 --> 00:20:04,940
and it's hard to invest in a
figure that looks different

430
00:20:04,940 --> 00:20:09,420
than the science hosts
that we're used to seeing.

431
00:20:09,420 --> 00:20:13,440
But we have a chance here
at MIT where the people are

432
00:20:13,440 --> 00:20:15,690
so diverse, not just in
ethnicity and gender,

433
00:20:15,690 --> 00:20:19,580
but in background and
personalities and interests.

434
00:20:19,580 --> 00:20:24,150
We have this huge landscape here
that we can tap into and start

435
00:20:24,150 --> 00:20:27,310
contributing to a picture
that looks a little bit more

436
00:20:27,310 --> 00:20:31,110
like what science and
engineering really is.

437
00:20:31,110 --> 00:20:34,140
And the other thing is literacy
in digital media, which

438
00:20:34,140 --> 00:20:36,420
is the whole idea
of understanding

439
00:20:36,420 --> 00:20:39,210
your video product as
something more than the thing

440
00:20:39,210 --> 00:20:40,890
that you just hit
play and watch,

441
00:20:40,890 --> 00:20:43,400
or understanding making
video as something

442
00:20:43,400 --> 00:20:46,730
more than just hitting
certain buttons to record

443
00:20:46,730 --> 00:20:50,090
the present moment, is something
that is going to become

444
00:20:50,090 --> 00:20:51,600
increasingly relevant.

445
00:20:51,600 --> 00:20:54,670
I don't know you guys
UROP in labs or anything,

446
00:20:54,670 --> 00:20:57,870
but a lot of labs right
now have their own cameras.

447
00:20:57,870 --> 00:20:59,730
Many of you will
probably end up having

448
00:20:59,730 --> 00:21:02,540
to give like a TED Talk
or some sort of talk

449
00:21:02,540 --> 00:21:06,160
to the public where it's going
to be more than just conveying

450
00:21:06,160 --> 00:21:06,730
information.

451
00:21:06,730 --> 00:21:07,900
Like people were
saying, you want

452
00:21:07,900 --> 00:21:09,274
to learn more
about how to engage

453
00:21:09,274 --> 00:21:13,080
an audience in a way that is
going to inspire and engage

454
00:21:13,080 --> 00:21:14,890
them.

455
00:21:14,890 --> 00:21:17,460
So at the end of
the day, this class

456
00:21:17,460 --> 00:21:20,150
is not about becoming
the next Bill Nye.

457
00:21:20,150 --> 00:21:22,020
That title is just
totally clickbait

458
00:21:22,020 --> 00:21:24,410
to get people to sign
up for the class.

459
00:21:24,410 --> 00:21:27,220
And it's not even really
about making videos,

460
00:21:27,220 --> 00:21:29,010
like I was saying.

461
00:21:29,010 --> 00:21:31,274
The eventual deliverable
of this class,

462
00:21:31,274 --> 00:21:32,940
the thing that we're
going to be working

463
00:21:32,940 --> 00:21:34,850
towards every single
day of this month,

464
00:21:34,850 --> 00:21:38,670
is to eventually create
around a three-minute episode

465
00:21:38,670 --> 00:21:42,567
that you host, that
you're on camera for,

466
00:21:42,567 --> 00:21:44,400
where you talk about a
science or technology

467
00:21:44,400 --> 00:21:47,790
or engineering/math subject
or topic that you're

468
00:21:47,790 --> 00:21:49,104
interested in.

469
00:21:49,104 --> 00:21:50,770
So that's the
deliverable, it's a video.

470
00:21:50,770 --> 00:21:53,640
But it's not
necessarily about what

471
00:21:53,640 --> 00:21:56,190
are the technical steps
I need to get there.

472
00:21:56,190 --> 00:21:59,000
Those are important,
but eventually it's

473
00:21:59,000 --> 00:22:02,960
about taking those skills
of being a producer

474
00:22:02,960 --> 00:22:05,310
and transferring them
into your everyday life.

475
00:22:05,310 --> 00:22:08,010
So maybe some of you
won't make a video

476
00:22:08,010 --> 00:22:09,944
after this month is
over, and that's OK,

477
00:22:09,944 --> 00:22:11,860
but hopefully the skills
that you've picked up

478
00:22:11,860 --> 00:22:14,940
along the way to becoming
an effective video producer

479
00:22:14,940 --> 00:22:17,700
will help you become a
great advocate for science

480
00:22:17,700 --> 00:22:18,790
and engineering later on.

481
00:22:21,570 --> 00:22:24,610
Every video that you guys
will make in every assignment

482
00:22:24,610 --> 00:22:27,370
that you make, and every
video that's online right now,

483
00:22:27,370 --> 00:22:28,720
has different objectives.

484
00:22:28,720 --> 00:22:32,370
Some of you may want to do a
video on physics, some of you

485
00:22:32,370 --> 00:22:34,860
may want to talk about math.

486
00:22:34,860 --> 00:22:38,230
But the thing that should
be the overarching objective

487
00:22:38,230 --> 00:22:40,690
of everything you
make during this month

488
00:22:40,690 --> 00:22:45,210
should be to address these
three problems in that amorphous

489
00:22:45,210 --> 00:22:47,600
STEM blob that I was talking
about earlier, that you want

490
00:22:47,600 --> 00:22:51,030
to open the door to
science and engineering,

491
00:22:51,030 --> 00:22:53,950
and really love of
learning to everyone.

492
00:22:53,950 --> 00:22:57,470
So a lot of that will
translate to making sure

493
00:22:57,470 --> 00:23:00,697
that your script isn't
condescending to your audience,

494
00:23:00,697 --> 00:23:02,280
making sure that
you're really meeting

495
00:23:02,280 --> 00:23:03,780
and knowing your
audience where they

496
00:23:03,780 --> 00:23:07,180
are, encouraging this
lifelong learning.

497
00:23:07,180 --> 00:23:10,900
We want curiosity to drive a lot
of what your objectives should

498
00:23:10,900 --> 00:23:11,400
be.

499
00:23:11,400 --> 00:23:14,690
You want your audience
to become curious.

500
00:23:14,690 --> 00:23:17,090
And then, of course,
we want your science

501
00:23:17,090 --> 00:23:19,349
to be legit so you're
educating the public,

502
00:23:19,349 --> 00:23:20,640
you're spreading STEM literacy.

503
00:23:23,950 --> 00:23:26,410
What makes a good video?

504
00:23:26,410 --> 00:23:30,390
Now, this is a quote from one
of the optional readings that's

505
00:23:30,390 --> 00:23:31,602
listed on the syllabus.

506
00:23:31,602 --> 00:23:33,060
It's actually really
great, we just

507
00:23:33,060 --> 00:23:36,170
don't have time in
class to cover it.

508
00:23:36,170 --> 00:23:37,467
But I love this quote.

509
00:23:37,467 --> 00:23:39,300
"Learning how to make
really effective video

510
00:23:39,300 --> 00:23:41,380
is like learning to
speak a second language.

511
00:23:41,380 --> 00:23:45,120
You have to learn not just what
to say but how what you say

512
00:23:45,120 --> 00:23:46,700
will be received by others.

513
00:23:46,700 --> 00:23:49,665
We understand video
better than any humans

514
00:23:49,665 --> 00:23:50,540
that have ever lived.

515
00:23:50,540 --> 00:23:53,600
Most of us just
don't speak it well."

516
00:23:53,600 --> 00:23:55,865
We consume video all the
time, like you were saying

517
00:23:55,865 --> 00:23:57,290
you watch YouTube videos.

518
00:23:57,290 --> 00:24:00,060
But that doesn't
necessarily transfer into us

519
00:24:00,060 --> 00:24:01,870
knowing how to make videos.

520
00:24:01,870 --> 00:24:03,954
It's the argument
of, oh, teaching

521
00:24:03,954 --> 00:24:05,870
can't be that hard because
I've been a student

522
00:24:05,870 --> 00:24:07,350
this whole time, right?

523
00:24:07,350 --> 00:24:09,680
It's very hard to
extrapolate what

524
00:24:09,680 --> 00:24:11,440
it is about the practice
of the video that

525
00:24:11,440 --> 00:24:14,490
makes it good when all
you are used to doing

526
00:24:14,490 --> 00:24:15,530
is being a consumer.

527
00:24:15,530 --> 00:24:18,120
So what makes a great video?

528
00:24:20,952 --> 00:24:22,410
Let's just take
this piece by piece

529
00:24:22,410 --> 00:24:25,680
and look at best practices
in established video realm.

530
00:24:25,680 --> 00:24:27,690
So educational videos.

531
00:24:27,690 --> 00:24:29,760
There was this task
force that MITx

532
00:24:29,760 --> 00:24:32,840
had a couple years
ago on what makes

533
00:24:32,840 --> 00:24:35,440
an effective educational
video, and the four traits

534
00:24:35,440 --> 00:24:39,340
that they came up with were,
one, that they were short,

535
00:24:39,340 --> 00:24:41,740
that they were digestible
modules, usually

536
00:24:41,740 --> 00:24:44,080
under 10 minutes.

537
00:24:44,080 --> 00:24:46,840
Another is that the
learner could interact

538
00:24:46,840 --> 00:24:51,100
with the speaker of the
video, so maybe the speaker

539
00:24:51,100 --> 00:24:53,570
would mention a topic
and it would be something

540
00:24:53,570 --> 00:24:56,120
that the viewer could end
up looking up on their own

541
00:24:56,120 --> 00:24:59,540
and interacting with.

542
00:24:59,540 --> 00:25:02,360
The other thing was that
the host had them engaged,

543
00:25:02,360 --> 00:25:07,230
so it wasn't just this passive
recording of them rambling on

544
00:25:07,230 --> 00:25:10,570
for an hour, the host would
actually tell the viewer,

545
00:25:10,570 --> 00:25:14,880
OK, now try this problem
at home, for instance.

546
00:25:14,880 --> 00:25:18,530
And then the host would
acknowledge the viewers,

547
00:25:18,530 --> 00:25:23,640
so it wasn't just, here's
this math problem sent out

548
00:25:23,640 --> 00:25:26,790
to this vague audience, it
was, you try this at home.

549
00:25:30,310 --> 00:25:33,820
And this is also what a lot of
what I call explainer videos

550
00:25:33,820 --> 00:25:35,090
do on YouTube.

551
00:25:35,090 --> 00:25:38,750
I don't know-- you guys must
be familiar with Khan Academy,

552
00:25:38,750 --> 00:25:41,380
but there are also things
like MIT BLOSSOMS, which

553
00:25:41,380 --> 00:25:45,630
is a set of videos that's
developed by a group here.

554
00:25:45,630 --> 00:25:48,230
There's Bozeman Science, who's
this high school teacher out

555
00:25:48,230 --> 00:25:52,020
in Montana, and he does tutorial
videos on all the AP science

556
00:25:52,020 --> 00:25:53,060
subjects.

557
00:25:53,060 --> 00:25:55,580
Tyler DeWitt, a former
grad student here, he

558
00:25:55,580 --> 00:25:57,140
does chemistry tutorial videos.

559
00:25:57,140 --> 00:25:59,820
And they're all
very, very successful

560
00:25:59,820 --> 00:26:03,380
because they take an
audience that's already

561
00:26:03,380 --> 00:26:05,890
motivated in learning
something and they're

562
00:26:05,890 --> 00:26:06,900
sort of one-stop shops.

563
00:26:06,900 --> 00:26:11,430
So how do I calculate the
molar mass of this compound?

564
00:26:11,430 --> 00:26:13,270
You can just go to
one of Tyler's videos

565
00:26:13,270 --> 00:26:15,500
and learn how to do it.

566
00:26:15,500 --> 00:26:20,370
It's very misleading sometimes,
though, because people see it

567
00:26:20,370 --> 00:26:24,030
and they often mistake it for
it being a direct recording

568
00:26:24,030 --> 00:26:25,260
of an instruction.

569
00:26:25,260 --> 00:26:28,790
And so they say, oh,
these explainer videos

570
00:26:28,790 --> 00:26:31,760
are much easier to do than
big budget productions.

571
00:26:31,760 --> 00:26:33,290
And that's not necessarily true.

572
00:26:33,290 --> 00:26:36,530
They still spend weeks
and weeks writing a script

573
00:26:36,530 --> 00:26:38,790
and developing exactly
what they're going to say.

574
00:26:38,790 --> 00:26:41,250
And they're so
effective because it's

575
00:26:41,250 --> 00:26:44,680
a very talented host, a
very talented teacher who

576
00:26:44,680 --> 00:26:47,330
is engaging their audience in
a way that helps them achieve

577
00:26:47,330 --> 00:26:48,590
mastery of the subject.

578
00:26:48,590 --> 00:26:50,470
So it gives them
learning confidence.

579
00:26:50,470 --> 00:26:53,220
People love Sal Khan
because they really

580
00:26:53,220 --> 00:26:55,560
feel connected to
him beyond sort

581
00:26:55,560 --> 00:26:58,120
of this robotic voice that's
telling them how to calculate

582
00:26:58,120 --> 00:26:59,790
the derivative of
something, and that's

583
00:26:59,790 --> 00:27:02,000
a very intentional thing
I think that he does.

584
00:27:06,000 --> 00:27:09,585
Now, for entertainment, even
within the world of YouTuber

585
00:27:09,585 --> 00:27:11,680
or within the world of
entertaining videos,

586
00:27:11,680 --> 00:27:15,070
there are subcategories that
have their own best practices.

587
00:27:15,070 --> 00:27:16,710
But in general,
for entertainment,

588
00:27:16,710 --> 00:27:20,040
the thing that is most
important, at least I think,

589
00:27:20,040 --> 00:27:22,580
is building an emotional
connection with your audience.

590
00:27:22,580 --> 00:27:26,030
And that's something that is
repeated by some of the folks

591
00:27:26,030 --> 00:27:28,480
that I'll be quoting
in a little bit.

592
00:27:28,480 --> 00:27:30,480
And in terms of
viral video, the way

593
00:27:30,480 --> 00:27:34,010
to best establish that
emotional connection

594
00:27:34,010 --> 00:27:37,240
is through authenticity.

595
00:27:37,240 --> 00:27:39,410
By authenticity I
mean when you see

596
00:27:39,410 --> 00:27:41,500
a video that goes
viral on YouTube,

597
00:27:41,500 --> 00:27:43,040
it's not necessarily
something that

598
00:27:43,040 --> 00:27:44,530
has a super corporate sheen.

599
00:27:44,530 --> 00:27:46,130
It's not really polished.

600
00:27:46,130 --> 00:27:49,610
A lot of times it just looks
like a very janky video

601
00:27:49,610 --> 00:27:51,620
that someone took
with their iPhone.

602
00:27:51,620 --> 00:27:54,190
And that in some
ways helps people

603
00:27:54,190 --> 00:27:57,402
feel really connected to the
material that they're watching.

604
00:27:57,402 --> 00:27:58,860
And you have to be
careful with it.

605
00:27:58,860 --> 00:28:02,620
But I did want to show a couple
clips of two science videos

606
00:28:02,620 --> 00:28:06,000
that have each raked-- I
think the first one has

607
00:28:06,000 --> 00:28:07,680
over six million
and the second one

608
00:28:07,680 --> 00:28:09,520
has almost 10 million views.

609
00:28:09,520 --> 00:28:12,300
And we'll just
watch part of each.

610
00:28:19,258 --> 00:28:21,510
CRAZY RUSSIAN HACKER: All
right, here is what we need.

611
00:28:21,510 --> 00:28:26,110
Empty soda cans and put
a little bit of water.

612
00:28:26,110 --> 00:28:30,850
Just a little bit, so it
will boil down, you know?

613
00:28:30,850 --> 00:28:35,030
And then turn on the stove.

614
00:28:35,030 --> 00:28:38,830
While this gets ready we're
going to make a nice bowl.

615
00:28:38,830 --> 00:28:45,070
So right here we've got
our ice water already.

616
00:28:45,070 --> 00:28:50,190
And you see how water is
boiling and steam coming out.

617
00:28:50,190 --> 00:28:52,670
I don't know if you can
see it, but this steam

618
00:28:52,670 --> 00:28:54,610
is coming out right now.

619
00:28:54,610 --> 00:28:58,430
So we're going to
get it and drop it.

620
00:28:58,430 --> 00:29:01,090
Use the tongs, don't use hands.

621
00:29:01,090 --> 00:29:05,020
Get it and drop it upside-down.

622
00:29:05,020 --> 00:29:08,150
That kind of fell.

623
00:29:08,150 --> 00:29:09,710
Let's start with this one.

624
00:29:13,830 --> 00:29:14,950
So are you guys ready?

625
00:29:23,800 --> 00:29:25,610
You see?

626
00:29:25,610 --> 00:29:27,630
They called this implosion.

627
00:29:27,630 --> 00:29:30,450
I want you to tell
me why that happens.

628
00:29:34,460 --> 00:29:36,600
Why does it implode like that?

629
00:29:36,600 --> 00:29:38,740
So we've got this pan.

630
00:29:38,740 --> 00:29:40,450
Here you go, a pan.

631
00:29:40,450 --> 00:29:43,210
And just we're going
to turn this on.

632
00:29:43,210 --> 00:29:45,660
But remember, safety is first.

633
00:29:45,660 --> 00:29:48,640
Kids, you're going to
need adults' permission.

634
00:29:48,640 --> 00:29:51,662
So and there we're going
to leave it for a minute.

635
00:29:51,662 --> 00:29:53,370
We're going to put a
little bit of water.

636
00:29:53,370 --> 00:29:56,530
Do you see how water is boiling
now because it's too hot?

637
00:30:06,710 --> 00:30:10,730
So all the water is
gone, boiled out.

638
00:30:10,730 --> 00:30:13,480
And let's leave it for
another two minutes.

639
00:30:13,480 --> 00:30:15,670
So it's been about two minutes.

640
00:30:15,670 --> 00:30:17,420
You see how hot it is?

641
00:30:17,420 --> 00:30:22,100
Let's put just a little bit
of water, just little drops.

642
00:30:25,180 --> 00:30:30,850
You see how all these drops just
like spinning around and not

643
00:30:30,850 --> 00:30:32,430
boiling out?

644
00:30:32,430 --> 00:30:35,300
I want you to comment
and tell me why.

645
00:30:35,300 --> 00:30:38,382
Let's drop some more.

646
00:30:38,382 --> 00:30:40,340
ELIZABETH CHOE: So the
thing is like 10 minutes

647
00:30:40,340 --> 00:30:41,990
long so I'm not
going to show it.

648
00:30:41,990 --> 00:30:44,900
But this video, which I
personally cannot stand

649
00:30:44,900 --> 00:30:47,980
watching, this thing has
gotten over five million views

650
00:30:47,980 --> 00:30:48,900
on YouTube.

651
00:30:48,900 --> 00:30:52,300
And Crazy Russian Hacker,
who's the user who created it,

652
00:30:52,300 --> 00:30:54,590
he has millions and
millions of subscribers.

653
00:30:54,590 --> 00:30:58,150
I have the co-worker
whose son is 12 years old

654
00:30:58,150 --> 00:31:01,540
and he loves Crazy
Russian Hacker.

655
00:31:01,540 --> 00:31:04,760
And I don't know how you
guys feel about the video.

656
00:31:04,760 --> 00:31:07,540
Were there any certain elements
that you noticed about it

657
00:31:07,540 --> 00:31:09,980
that either you liked
or you understood why

658
00:31:09,980 --> 00:31:11,520
people would like it so much?

659
00:31:17,520 --> 00:31:18,479
Yes, John.

660
00:31:18,479 --> 00:31:21,020
JONATHAN: He asked the audience
to explain what was going on,

661
00:31:21,020 --> 00:31:25,020
so that encouraged
feedback and more posts

662
00:31:25,020 --> 00:31:27,496
by commenting on the video.

663
00:31:27,496 --> 00:31:29,370
ELIZABETH CHOE: Yeah,
so there's that element

664
00:31:29,370 --> 00:31:33,300
of not only acknowledging
your audience but engaging it.

665
00:31:33,300 --> 00:31:36,280
And that's something that
a lot of YouTube videos do.

666
00:31:36,280 --> 00:31:38,810
Maybe it's to get more
comments, but it certainly

667
00:31:38,810 --> 00:31:40,620
works a lot of the time.

668
00:31:40,620 --> 00:31:41,220
Yes.

669
00:31:41,220 --> 00:31:42,040
PAUL FOLINO: That
video seemed like it

670
00:31:42,040 --> 00:31:44,010
was kind of-- it wasn't
necessarily scripted,

671
00:31:44,010 --> 00:31:46,070
so it kind of shows
that he really

672
00:31:46,070 --> 00:31:49,340
knows what he's talking
about, he's not robotically

673
00:31:49,340 --> 00:31:51,428
following a script.

674
00:31:51,428 --> 00:31:53,970
Shows he knows a little
bit about what he's doing.

675
00:31:53,970 --> 00:31:55,761
ELIZABETH CHOE: And
he's quite a character.

676
00:31:55,761 --> 00:31:58,110
I mean, Crazy Russian Hacker
has a huge brand, right?

677
00:31:58,110 --> 00:32:00,020
Like as soon as
he starts talking

678
00:32:00,020 --> 00:32:02,330
you know that it's a Crazy
Russian Hacker video.

679
00:32:02,330 --> 00:32:04,607
And he's kind of outrageous.

680
00:32:04,607 --> 00:32:06,190
Which is why it's
hard to repeat that.

681
00:32:06,190 --> 00:32:08,170
It would be hard--
if I replicated

682
00:32:08,170 --> 00:32:12,290
that exact same video, it
would probably not go viral.

683
00:32:12,290 --> 00:32:16,060
So his whole persona
and the way that he

684
00:32:16,060 --> 00:32:19,266
has this sort of unpolished
look about his videos

685
00:32:19,266 --> 00:32:21,640
is actually maybe one of the
reasons why it's compelling.

686
00:32:21,640 --> 00:32:23,122
Were you going to say
something, Yuliya?

687
00:32:23,122 --> 00:32:24,104
YULIYA KLOCHAN: Yeah, I
think it's also relatable.

688
00:32:24,104 --> 00:32:26,559
He dropped the can
the first time,

689
00:32:26,559 --> 00:32:30,547
so that tells the viewers that
they can also make mistakes.

690
00:32:30,547 --> 00:32:32,130
ELIZABETH CHOE: A
lot of online videos

691
00:32:32,130 --> 00:32:34,340
have this single-take format.

692
00:32:34,340 --> 00:32:37,580
So instead of having two
cameras like these guys

693
00:32:37,580 --> 00:32:40,410
set up where you're switching
back and forth between angles,

694
00:32:40,410 --> 00:32:43,340
he kind of just held his
iPhone where he was, right,

695
00:32:43,340 --> 00:32:45,360
or whatever camera,
and followed along.

696
00:32:45,360 --> 00:32:48,025
So you actually feel like
you're right there with him.

697
00:32:48,025 --> 00:32:50,220
You feel like you're in
the kitchen with him.

698
00:32:50,220 --> 00:32:53,400
There are no cuts back
and forth to him talking.

699
00:32:53,400 --> 00:32:55,650
It's just one long,
continuous take

700
00:32:55,650 --> 00:32:58,610
with just a couple mess-ups
taken out in between.

701
00:33:02,159 --> 00:33:03,950
JOSH CHEONG: Even though
he asked comments,

702
00:33:03,950 --> 00:33:06,930
I'm very sure these comments
are not all legitimate comments.

703
00:33:06,930 --> 00:33:10,060
I've very sure there will be
probably one or two people who

704
00:33:10,060 --> 00:33:11,990
purposely are trolls
and probably say,

705
00:33:11,990 --> 00:33:13,847
oh, this is black
magic or something,

706
00:33:13,847 --> 00:33:16,180
and then someone will comment,
and the virality probably

707
00:33:16,180 --> 00:33:18,390
gives him the extra
few million views.

708
00:33:18,390 --> 00:33:19,960
ELIZABETH CHOE: Yeah, yeah.

709
00:33:19,960 --> 00:33:23,120
Logan Smalley, who's the
head of TED-Ed-- you guys

710
00:33:23,120 --> 00:33:24,380
have seen TED Talks, right?

711
00:33:24,380 --> 00:33:27,060
Have you ever seen
TED-Ed videos?

712
00:33:27,060 --> 00:33:30,790
They do a spin-off where they
have animators and writers

713
00:33:30,790 --> 00:33:31,920
partner up.

714
00:33:31,920 --> 00:33:34,390
He's the one who
directs TED-Ed, and he

715
00:33:34,390 --> 00:33:38,460
had this talk where he was
saying how a video online has

716
00:33:38,460 --> 00:33:41,055
a beginning, middle, and end,
but the beginning, middle,

717
00:33:41,055 --> 00:33:43,000
and end isn't what's
in the video itself.

718
00:33:43,000 --> 00:33:45,470
The beginning is the tweet
that announces the video,

719
00:33:45,470 --> 00:33:47,570
the middle is the video
itself, and the end

720
00:33:47,570 --> 00:33:49,670
it is all the
conversation that takes

721
00:33:49,670 --> 00:33:53,660
place afterwards in the comments
online and social media.

722
00:33:53,660 --> 00:33:56,790
And so with things like
Crazy Russian Hacker,

723
00:33:56,790 --> 00:33:59,650
the end, the conversation,
is almost just as important

724
00:33:59,650 --> 00:34:01,630
or just as much a
part of the experience

725
00:34:01,630 --> 00:34:03,899
as the 10-minute video itself.

726
00:34:03,899 --> 00:34:05,440
I wanted to show
you one other video.

727
00:34:05,440 --> 00:34:10,199
This is from Smarter Every
Day, and this has also

728
00:34:10,199 --> 00:34:11,289
over five million views.

729
00:34:11,289 --> 00:34:12,830
DESTIN SANDLIN: Hey,
it's me, Destin.

730
00:34:12,830 --> 00:34:14,246
Welcome back to
Smarter Every Day.

731
00:34:14,246 --> 00:34:17,040
So you've probably observed
that cats almost always

732
00:34:17,040 --> 00:34:18,540
land on their feet.

733
00:34:18,540 --> 00:34:20,730
Today's question is why.

734
00:34:20,730 --> 00:34:23,389
Like most simple questions,
there's a very complex answer.

735
00:34:23,389 --> 00:34:25,380
For instance, let me
reword this question.

736
00:34:25,380 --> 00:34:28,060
How does a cat go
from feet up to feet

737
00:34:28,060 --> 00:34:30,650
down in a falling
reference frame

738
00:34:30,650 --> 00:34:32,780
without violating the
conservation of angular

739
00:34:32,780 --> 00:34:33,929
momentum?

740
00:34:33,929 --> 00:34:36,334
Now, I've studied free-falling
bodies-- my own, in fact--

741
00:34:36,334 --> 00:34:37,750
in several different
environments.

742
00:34:37,750 --> 00:34:39,889
And once I get my angular
rotation started in one

743
00:34:39,889 --> 00:34:41,746
direction, I can't stop it.

744
00:34:41,746 --> 00:34:43,620
Today we're going to
use a high-speed camera.

745
00:34:43,620 --> 00:34:45,350
We're not going to use Ally
because this is my daughter's

746
00:34:45,350 --> 00:34:46,558
cat, I don't want to hurt it.

747
00:34:46,558 --> 00:34:48,270
We're going to use a stunt cat.

748
00:34:48,270 --> 00:34:50,699
Let me introduce you
to Gigi, the stunt cat.

749
00:34:56,710 --> 00:34:59,250
I'll just flip
the video vertical

750
00:34:59,250 --> 00:35:00,630
and then motion-track the cat.

751
00:35:00,630 --> 00:35:02,714
It's just going to take a
lot more effort in post.

752
00:35:02,714 --> 00:35:04,421
We're going to try to
do it in a way that

753
00:35:04,421 --> 00:35:05,520
doesn't make anybody mad.

754
00:35:05,520 --> 00:35:08,580
That's pretty hard to do.

755
00:35:08,580 --> 00:35:09,871
You got to drop a cat.

756
00:35:09,871 --> 00:35:10,370
Ready, Gigi?

757
00:35:14,305 --> 00:35:16,179
Checking out the high-speed
data there, Gigi?

758
00:35:36,831 --> 00:35:38,830
OK, the first thing a cat
does when it's falling

759
00:35:38,830 --> 00:35:40,640
is try to figure
out which way is up.

760
00:35:40,640 --> 00:35:43,700
It does this either with a gyro
in the ear or with its eyes.

761
00:35:51,960 --> 00:35:53,610
Ready to talk cat physics?

762
00:35:53,610 --> 00:35:54,370
All right.

763
00:35:54,370 --> 00:35:56,786
So check out this footage I
captured with the Phantom Miro

764
00:35:56,786 --> 00:35:58,500
while Gigi goes to
get a drink of water.

765
00:35:58,500 --> 00:36:00,340
So here's what's interesting
about this to me.

766
00:36:00,340 --> 00:36:02,256
If you'll notice, at the
beginning of the drop

767
00:36:02,256 --> 00:36:03,760
the cat is not rotating.

768
00:36:03,760 --> 00:36:05,890
Halfway through the drop
the cat is rotating,

769
00:36:05,890 --> 00:36:09,130
and then at the very end
Gigi somehow stops rotating.

770
00:36:09,130 --> 00:36:11,630
Newton's first law says
that an object at rest

771
00:36:11,630 --> 00:36:14,780
will stay at rest unless
acted on by an external force.

772
00:36:14,780 --> 00:36:17,080
I see no external
forces on this cat.

773
00:36:17,080 --> 00:36:18,420
So what's happening here?

774
00:36:18,420 --> 00:36:19,950
It's not making sense to me.

775
00:36:19,950 --> 00:36:22,122
OK, so in order to really
get the right data,

776
00:36:22,122 --> 00:36:24,455
we're going to have to drop
her 90 degrees out of phase.

777
00:36:24,455 --> 00:36:25,770
Ready, girl?

778
00:36:25,770 --> 00:36:27,220
This time watch her tail.

779
00:36:27,220 --> 00:36:29,400
Three, two, one.

780
00:36:58,840 --> 00:37:00,530
OK, so you think
you figured it out?

781
00:37:00,530 --> 00:37:01,460
Check this out.

782
00:37:01,460 --> 00:37:04,480
You probably noticed that when
the cat was falling her tail

783
00:37:04,480 --> 00:37:06,800
was rotating in the
direction opposite of where

784
00:37:06,800 --> 00:37:08,230
her body was rotating.

785
00:37:08,230 --> 00:37:11,480
What's interesting about that
is that that's not how it works.

786
00:37:11,480 --> 00:37:14,410
In fact, even bobtail
cats can do this.

787
00:37:14,410 --> 00:37:16,020
It's called the cat
righting reflex.

788
00:37:16,020 --> 00:37:17,520
I'll prove it to you.

789
00:37:17,520 --> 00:37:19,280
I came across some
video from the '60s

790
00:37:19,280 --> 00:37:21,320
when the Air Force was
researching microgravity

791
00:37:21,320 --> 00:37:23,200
for future astronauts.

792
00:37:23,200 --> 00:37:26,110
Turns out they took some
cats up on parabolic flights.

793
00:37:26,110 --> 00:37:29,130
He turns to rotate his tail to
flip over, but it doesn't work.

794
00:37:29,130 --> 00:37:31,092
He just ends up nutating wildly.

795
00:37:31,092 --> 00:37:32,550
Then he does
something interesting.

796
00:37:32,550 --> 00:37:34,756
He takes his back
and he bends it.

797
00:37:34,756 --> 00:37:36,880
And when he bends his back
and then creates motion,

798
00:37:36,880 --> 00:37:38,713
something interesting happens.

799
00:37:38,713 --> 00:37:41,407
Ahhh, now we're
getting somewhere.

800
00:37:41,407 --> 00:37:43,490
So let me show you one
more cat flip with the Miro

801
00:37:43,490 --> 00:37:44,573
and we'll figure this out.

802
00:37:48,250 --> 00:37:50,762
OK, the arched back ends
up being pretty important.

803
00:37:50,762 --> 00:37:52,345
What he does is he
divides his body up

804
00:37:52,345 --> 00:37:54,115
into two separate
rotational axes that

805
00:37:54,115 --> 00:37:55,700
are tilted from one another.

806
00:37:55,700 --> 00:37:57,711
When he's released, he
pulls his front paws in

807
00:37:57,711 --> 00:37:58,960
and does the ice skater trick.

808
00:37:58,960 --> 00:38:01,220
He decreases his moment
of inertia in the front

809
00:38:01,220 --> 00:38:02,840
so he can spin fast up there.

810
00:38:02,840 --> 00:38:05,020
But in the back he pushes
his legs away from him,

811
00:38:05,020 --> 00:38:06,890
increasing his
moment of inertia.

812
00:38:06,890 --> 00:38:09,126
So a really large
twist in the front

813
00:38:09,126 --> 00:38:10,750
equals a really small
twist in the back

814
00:38:10,750 --> 00:38:13,520
in the opposite direction,
and the torques equal out.

815
00:38:13,520 --> 00:38:15,730
So as soon as he gets his
front paws in under him,

816
00:38:15,730 --> 00:38:17,834
all he has to do is
extend those legs back out

817
00:38:17,834 --> 00:38:19,250
to increase that
moment of inertia

818
00:38:19,250 --> 00:38:22,560
and stop the front twist,
and extend his back legs

819
00:38:22,560 --> 00:38:24,430
along that rear axis.

820
00:38:24,430 --> 00:38:26,650
That allows him to twist
those around really fast.

821
00:38:26,650 --> 00:38:28,233
And then all he has
to do is pull them

822
00:38:28,233 --> 00:38:31,520
back in under his body and
then extend all four legs,

823
00:38:31,520 --> 00:38:32,780
and brace for impact.

824
00:38:34,844 --> 00:38:36,260
ELIZABETH CHOE:
All right, so very

825
00:38:36,260 --> 00:38:39,800
different from Crazy Russian
Hacker but just as popular.

826
00:38:39,800 --> 00:38:42,070
I personally really
like Smarter Every Day.

827
00:38:42,070 --> 00:38:45,444
I think he's one of
the best hosts, period.

828
00:38:45,444 --> 00:38:47,360
You can disagree with
me, that's totally fine.

829
00:38:47,360 --> 00:38:49,930
But the thing I like about
him is even though he's

830
00:38:49,930 --> 00:38:51,360
maybe a little bit
more scripted--

831
00:38:51,360 --> 00:38:53,130
he doesn't say um a
lot, he doesn't really

832
00:38:53,130 --> 00:38:57,500
mess up as much-- I still feel
like Destin is talking to me,

833
00:38:57,500 --> 00:39:00,060
that it's just this random
guy in his backyard.

834
00:39:00,060 --> 00:39:03,360
He happens to be a
rocket scientist down

835
00:39:03,360 --> 00:39:07,470
at NASA or some similar
engineering firm in Alabama,

836
00:39:07,470 --> 00:39:09,220
so he obviously knows
his stuff very well.

837
00:39:09,220 --> 00:39:11,640
But there's something
about him that's still

838
00:39:11,640 --> 00:39:13,800
very relatable, very natural.

839
00:39:13,800 --> 00:39:16,280
He seems like who
he is on screen

840
00:39:16,280 --> 00:39:18,130
is who he is in real life.

841
00:39:18,130 --> 00:39:21,824
Did anyone have any particular
aspects about that video

842
00:39:21,824 --> 00:39:22,990
that they liked or disliked?

843
00:39:25,890 --> 00:39:27,140
Or anything that they noticed?

844
00:39:31,792 --> 00:39:33,167
KENNETH CHEAH: I
think he thought

845
00:39:33,167 --> 00:39:39,715
about how [INAUDIBLE] tail
was what affected the cat's

846
00:39:39,715 --> 00:39:43,152
movement, allowed the cat to--
but he mentioned that it wasn't

847
00:39:43,152 --> 00:39:45,442
the tail at all,
so then that made

848
00:39:45,442 --> 00:39:48,128
us more interested in wanting
to finish the rest of the video.

849
00:39:48,128 --> 00:39:49,044
ELIZABETH CHOE: Mm-hm.

850
00:39:49,044 --> 00:39:52,290
He anticipated the misconception
[INAUDIBLE] the cat.

851
00:39:52,290 --> 00:39:53,890
And that's actually
a really big tool

852
00:39:53,890 --> 00:39:56,560
that you can use in your
videos to hook people in.

853
00:39:56,560 --> 00:39:59,990
And Ceri, you take that
summer MIT course, right?

854
00:39:59,990 --> 00:40:01,740
Where you were
specifically addressing

855
00:40:01,740 --> 00:40:03,022
misconceptions in biology?

856
00:40:03,022 --> 00:40:05,355
CERI RILEY: Yeah, I actually
took a summer class at MIT,

857
00:40:05,355 --> 00:40:07,710
and I personally made a video.

858
00:40:07,710 --> 00:40:09,620
But our whole
objective of the class

859
00:40:09,620 --> 00:40:15,147
was to choose a topic in
science that people often

860
00:40:15,147 --> 00:40:16,230
have misconceptions about.

861
00:40:16,230 --> 00:40:20,350
So some people did videos
on you catch a cold

862
00:40:20,350 --> 00:40:21,910
if you're outside in the cold.

863
00:40:21,910 --> 00:40:25,150
And then mine was your
deoxygenated blood

864
00:40:25,150 --> 00:40:27,465
in diagrams is
always shown as blue

865
00:40:27,465 --> 00:40:29,930
and so people think our
blood is blue sometimes,

866
00:40:29,930 --> 00:40:32,980
but it's always
different shades of red.

867
00:40:32,980 --> 00:40:35,934
Yeah, and so our entire goal
was to figure out not only

868
00:40:35,934 --> 00:40:37,350
the real science
behind the topic,

869
00:40:37,350 --> 00:40:39,170
but how to explain
it in a way that

870
00:40:39,170 --> 00:40:41,181
debunks the myths or
the misconceptions

871
00:40:41,181 --> 00:40:42,769
that people have about them.

872
00:40:42,769 --> 00:40:44,310
ELIZABETH CHOE: And
I don't know what

873
00:40:44,310 --> 00:40:45,990
it is about
misconceptions, but it

874
00:40:45,990 --> 00:40:50,000
does seem to be something
that not necessary predicates

875
00:40:50,000 --> 00:40:55,530
but can help launch a video into
being something more engaging.

876
00:40:55,530 --> 00:40:59,800
And maybe it is because it
taps into the audience itself

877
00:40:59,800 --> 00:41:03,050
and it becomes more relatable,
because it's acknowledging,

878
00:41:03,050 --> 00:41:05,122
hey, this is what
you actually think.

879
00:41:05,122 --> 00:41:06,580
And it becomes
surprising and maybe

880
00:41:06,580 --> 00:41:08,740
more memorable in that way.

881
00:41:08,740 --> 00:41:13,170
That you're more likely to
remember that a cat doesn't use

882
00:41:13,170 --> 00:41:16,650
its tail to sort of
out-balance the rotation

883
00:41:16,650 --> 00:41:19,220
that it feels when it's flipping
but actually scrunches up.

884
00:41:19,220 --> 00:41:20,850
I mean, I'm going to
remember that way more

885
00:41:20,850 --> 00:41:23,280
than I'm going to remember a
single one of my 801 lectures

886
00:41:23,280 --> 00:41:26,424
on rotational physics.

887
00:41:26,424 --> 00:41:28,090
So that's just something
to think about.

888
00:41:30,671 --> 00:41:32,170
Now, something I
do want to mention,

889
00:41:32,170 --> 00:41:34,440
and this is a conversation
that Chris and I have

890
00:41:34,440 --> 00:41:40,510
a lot, which is that people
often confuse correlation

891
00:41:40,510 --> 00:41:41,660
for causation, right?

892
00:41:41,660 --> 00:41:44,450
They think, oh, well, all
these videos did really well

893
00:41:44,450 --> 00:41:46,620
so I just need to
make a crappy video

894
00:41:46,620 --> 00:41:48,810
and do really bad
lighting and just

895
00:41:48,810 --> 00:41:51,375
be really terrible on
camera, and it'll go viral,

896
00:41:51,375 --> 00:41:52,110
it'll be great.

897
00:41:52,110 --> 00:41:53,580
It'll be relatable
and authentic.

898
00:41:53,580 --> 00:41:55,210
And that's not
necessarily true, right?

899
00:41:55,210 --> 00:41:58,040
Low production value
is not equal to

900
00:41:58,040 --> 00:42:02,020
and does not predict
a viral video.

901
00:42:02,020 --> 00:42:05,420
If any of us tried to
recreate Crazy Russian Hacker

902
00:42:05,420 --> 00:42:07,784
it would probably not go
viral for the same reasons

903
00:42:07,784 --> 00:42:09,200
that I talked about
earlier, which

904
00:42:09,200 --> 00:42:11,690
is that there are a
lot of elements that

905
00:42:11,690 --> 00:42:16,980
go in play into creating
something beyond what you see

906
00:42:16,980 --> 00:42:19,810
on screen when
you're watching it.

907
00:42:19,810 --> 00:42:23,900
That it's OK to have
good production.

908
00:42:23,900 --> 00:42:25,790
Smarter Every Day is
actually pretty decent,

909
00:42:25,790 --> 00:42:27,930
and when you see his newer
videos, his camera work,

910
00:42:27,930 --> 00:42:28,780
it's pretty good.

911
00:42:28,780 --> 00:42:31,330
And you can tell that he's
gotten new equipment and things

912
00:42:31,330 --> 00:42:31,830
like that.

913
00:42:31,830 --> 00:42:34,060
And it doesn't take away
at all from the experience,

914
00:42:34,060 --> 00:42:36,790
from the authenticity
of the video.

915
00:42:36,790 --> 00:42:40,075
That authenticity starts
at the core of the host,

916
00:42:40,075 --> 00:42:42,490
at the way they're
creating it, the reasons

917
00:42:42,490 --> 00:42:43,980
why they're creating the video.

918
00:42:43,980 --> 00:42:47,170
And it's not created by the
conditions of the production

919
00:42:47,170 --> 00:42:48,620
itself, necessarily.

920
00:42:48,620 --> 00:42:53,170
It's just that the conditions
don't hinder the authenticity.

921
00:42:53,170 --> 00:42:55,220
But please don't mistake.

922
00:42:55,220 --> 00:42:59,230
Bad video production does not
help you get to viral video.

923
00:42:59,230 --> 00:43:03,600
It just doesn't stop
you from getting there.

924
00:43:03,600 --> 00:43:07,010
Now, for YouTube-- and we sort
of previewed this a little bit

925
00:43:07,010 --> 00:43:08,580
with the two videos
that we watched--

926
00:43:08,580 --> 00:43:10,496
there are a couple traits
about YouTube videos

927
00:43:10,496 --> 00:43:13,410
that I think make them
really great for learning

928
00:43:13,410 --> 00:43:16,950
and for educating,
and for successfully

929
00:43:16,950 --> 00:43:17,870
engaging an audience.

930
00:43:17,870 --> 00:43:20,470
The first being just
sort of the format

931
00:43:20,470 --> 00:43:21,900
in which they're written.

932
00:43:21,900 --> 00:43:26,350
A lot of viral YouTube videos
or videos that are well known,

933
00:43:26,350 --> 00:43:28,620
or a lot of SciShow
videos, for instance,

934
00:43:28,620 --> 00:43:31,410
they follow this format
of asking the why, what,

935
00:43:31,410 --> 00:43:32,720
and how questions.

936
00:43:32,720 --> 00:43:36,030
So you'll notice that the
Smarter Every Day video was not

937
00:43:36,030 --> 00:43:41,230
titled gravitational
physics, Newton's second law,

938
00:43:41,230 --> 00:43:42,900
or rotational dynamics, right?

939
00:43:42,900 --> 00:43:46,670
It was why does a cat fall on
its feet when it falls down,

940
00:43:46,670 --> 00:43:47,170
right?

941
00:43:47,170 --> 00:43:49,140
It's contextualizing
the question.

942
00:43:49,140 --> 00:43:50,790
It's making it relatable.

943
00:43:50,790 --> 00:43:53,960
It's sort of tapping
into the innate curiosity

944
00:43:53,960 --> 00:43:56,660
that people have, even
if they hate science.

945
00:43:56,660 --> 00:44:00,492
People who watch that video
are not physics majors.

946
00:44:00,492 --> 00:44:01,825
And it makes them more sharable.

947
00:44:01,825 --> 00:44:03,810
It makes them more memorable.

948
00:44:03,810 --> 00:44:07,150
And I think it makes it a
little bit more conducive

949
00:44:07,150 --> 00:44:08,940
to this idea of
retrieval learning,

950
00:44:08,940 --> 00:44:11,940
that people aren't going to
just end the video right there,

951
00:44:11,940 --> 00:44:12,440
right?

952
00:44:12,440 --> 00:44:13,990
They're going to maybe
share it with their friends

953
00:44:13,990 --> 00:44:14,790
or they're going
to talk about it

954
00:44:14,790 --> 00:44:16,380
with their teacher at school.

955
00:44:16,380 --> 00:44:20,610
Which is such a powerful
thing to happen with learning.

956
00:44:20,610 --> 00:44:23,190
I think that's what really
everyone's objective is

957
00:44:23,190 --> 00:44:24,710
as a teacher, or
a lot of teachers

958
00:44:24,710 --> 00:44:27,544
have this objective, that
they don't want the lessons

959
00:44:27,544 --> 00:44:28,960
that they're
teaching to just stop

960
00:44:28,960 --> 00:44:30,400
once people leave the room.

961
00:44:30,400 --> 00:44:32,200
They want people to
keep thinking about it

962
00:44:32,200 --> 00:44:34,810
and thinking about it in
the context of their life

963
00:44:34,810 --> 00:44:36,750
outside of the classroom.

964
00:44:36,750 --> 00:44:38,861
So this format really
aids in doing that.

965
00:44:38,861 --> 00:44:40,360
And I have a couple
of videos I want

966
00:44:40,360 --> 00:44:42,740
to show you guys, the first
being from AsapSCIENCE.

967
00:44:45,899 --> 00:44:46,940
ASAPSCIENCE: Ahhh, sleep.

968
00:44:46,940 --> 00:44:49,260
You can never have
enough of it, it seems.

969
00:44:49,260 --> 00:44:51,150
In fact, sometimes
it literally feels

970
00:44:51,150 --> 00:44:52,710
like you aren't getting enough.

971
00:44:52,710 --> 00:44:55,280
But what if you stopped
sleeping altogether?

972
00:44:55,280 --> 00:44:57,260
Strangely, science
understands relatively

973
00:44:57,260 --> 00:45:00,420
little about why we sleep or how
it evolved in the first place.

974
00:45:00,420 --> 00:45:03,310
After all, laying unconscious
and dormant for hours on end

975
00:45:03,310 --> 00:45:06,850
while predators lurk hardly
seems advantageous or smart.

976
00:45:06,850 --> 00:45:09,200
But we have discovered
a few correlations.

977
00:45:09,200 --> 00:45:11,990
For example, adults who sleep
between six to eight hours

978
00:45:11,990 --> 00:45:13,850
a night tend to live longer.

979
00:45:13,850 --> 00:45:16,610
Excessive sleep, however,
can lead to medical problems,

980
00:45:16,610 --> 00:45:19,420
including cardiovascular
disease and diabetes.

981
00:45:19,420 --> 00:45:21,870
Similarly, chronic
sleep deprivation

982
00:45:21,870 --> 00:45:24,750
has been linked to aspects
of cardiovascular disease,

983
00:45:24,750 --> 00:45:27,320
obesity, depression,
and even brain damage.

984
00:45:27,320 --> 00:45:29,650
But what if you stopped
sleeping right now?

985
00:45:29,650 --> 00:45:32,580
Well, after your first sleepless
night, your mesolimbic system

986
00:45:32,580 --> 00:45:35,480
becomes stimulated and
dopamine runs rampant.

987
00:45:35,480 --> 00:45:38,290
And this may actually trigger
some extra energy, motivation,

988
00:45:38,290 --> 00:45:40,490
positivity, and even sex drive.

989
00:45:40,490 --> 00:45:43,020
Sounds appealing, but
it's a slippery slope.

990
00:45:43,020 --> 00:45:44,680
Your brain slowly
begins to shut off

991
00:45:44,680 --> 00:45:47,050
the regions responsible
for planning and evaluating

992
00:45:47,050 --> 00:45:50,090
decisions, leading to
more impulsive behavior.

993
00:45:50,090 --> 00:45:52,180
Once exhaustion sets
in, you'll find yourself

994
00:45:52,180 --> 00:45:54,510
with slower reaction
times, and reduced

995
00:45:54,510 --> 00:45:56,590
perceptual and
cognitive functions.

996
00:45:56,590 --> 00:45:58,620
After a day or two
of no sleep, the body

997
00:45:58,620 --> 00:46:01,590
loses its ability to
properly metabolize glucose,

998
00:46:01,590 --> 00:46:03,890
and the immune system
stops working as well.

999
00:46:03,890 --> 00:46:06,120
In some cases, three
days of no sleep

1000
00:46:06,120 --> 00:46:08,070
has led to hallucinations.

1001
00:46:08,070 --> 00:46:09,220
Care about how you look?

1002
00:46:09,220 --> 00:46:10,910
Studies have shown
a direct correlation

1003
00:46:10,910 --> 00:46:14,340
between sleep deprivation and
a person's perceived beauty.

1004
00:46:14,340 --> 00:46:16,730
That is to say,
sleep-deprived individuals

1005
00:46:16,730 --> 00:46:19,330
appeared less healthy and
less attractive than when

1006
00:46:19,330 --> 00:46:20,510
they were well-rested.

1007
00:46:20,510 --> 00:46:23,170
The longest scientifically
documented case of being awake

1008
00:46:23,170 --> 00:46:25,842
was 264 hours, or 11 days.

1009
00:46:25,842 --> 00:46:27,300
And while they did
develop problems

1010
00:46:27,300 --> 00:46:29,896
with concentration,
perception, and irritability,

1011
00:46:29,896 --> 00:46:31,270
the surprising
truth is that they

1012
00:46:31,270 --> 00:46:34,060
suffered no serious
long-term health effects.

1013
00:46:34,060 --> 00:46:37,220
In fact, no individuals under
these documented conditions

1014
00:46:37,220 --> 00:46:40,030
experienced medical,
physiological, neurological,

1015
00:46:40,030 --> 00:46:41,710
or psychiatric problems.

1016
00:46:41,710 --> 00:46:43,400
But there are limited
studies, and this

1017
00:46:43,400 --> 00:46:45,070
doesn't mean permanent
damage couldn't

1018
00:46:45,070 --> 00:46:46,990
be inflicted with more time.

1019
00:46:46,990 --> 00:46:49,710
Sleep deprivation experiments
on rats, for example,

1020
00:46:49,710 --> 00:46:52,110
generally lead to death
after about two weeks.

1021
00:46:52,110 --> 00:46:53,696
But scientists
aren't totally sure

1022
00:46:53,696 --> 00:46:55,320
if they're dying from
the lack of sleep

1023
00:46:55,320 --> 00:46:57,960
or from the stress of
constantly being woken up.

1024
00:46:57,960 --> 00:47:00,370
Perhaps we should look at
fatal familial insomnia

1025
00:47:00,370 --> 00:47:02,680
for an answer, a rare
genetic disease of the brain

1026
00:47:02,680 --> 00:47:05,080
which causes progressively
worsening insomnia,

1027
00:47:05,080 --> 00:47:08,160
or sleeplessness, leading
to hallucinations, dementia,

1028
00:47:08,160 --> 00:47:09,570
and ultimately death.

1029
00:47:09,570 --> 00:47:12,550
This disease has only affected
around 100 people in the world,

1030
00:47:12,550 --> 00:47:15,700
but their average survival
span was around 18 months.

1031
00:47:15,700 --> 00:47:17,920
Over time, the lack
of sleep becomes worse

1032
00:47:17,920 --> 00:47:20,150
and the body's organs
begin to shut down.

1033
00:47:20,150 --> 00:47:23,100
So while lack of sleep won't
necessarily kill you quickly,

1034
00:47:23,100 --> 00:47:25,120
continual sleep
deprivation will have

1035
00:47:25,120 --> 00:47:26,970
a negative effect on your body.

1036
00:47:26,970 --> 00:47:28,420
Sleep tight.

1037
00:47:28,420 --> 00:47:30,201
But not too much.

1038
00:47:30,201 --> 00:47:30,700
Got a--

1039
00:47:32,917 --> 00:47:35,250
ELIZABETH CHOE: So were there
any elements of that video

1040
00:47:35,250 --> 00:47:40,900
that you found striking, that
you liked, that you disliked?

1041
00:47:40,900 --> 00:47:41,650
Yes, Yuliya.

1042
00:47:41,650 --> 00:47:43,441
YULIYA KLOCHAN: I really
liked the movement

1043
00:47:43,441 --> 00:47:45,152
and that he changed
his materials.

1044
00:47:45,152 --> 00:47:47,610
ELIZABETH CHOE: Oh, like from
drawing to construction paper

1045
00:47:47,610 --> 00:47:48,544
and things like that.

1046
00:47:51,391 --> 00:47:53,016
What did you think
about the animation?

1047
00:47:53,016 --> 00:47:54,646
Did you like it or not?

1048
00:47:54,646 --> 00:47:56,020
JOSH GUNN: Oh,
are you asking me?

1049
00:47:56,020 --> 00:47:56,320
ELIZABETH CHOE: Yeah.

1050
00:47:56,320 --> 00:47:57,986
JOSH GUNN: Yeah, I
think it's effective.

1051
00:47:57,986 --> 00:48:01,160
I think one of the things
about it that's nice

1052
00:48:01,160 --> 00:48:07,940
is that the animation allowed
him to change to appeal to I

1053
00:48:07,940 --> 00:48:13,320
think a current need for a
constant stream of images

1054
00:48:13,320 --> 00:48:14,160
that are different.

1055
00:48:14,160 --> 00:48:16,690
This kind of-- I think
we've been conditioned

1056
00:48:16,690 --> 00:48:19,940
to be sort of
bombarded with images,

1057
00:48:19,940 --> 00:48:24,510
and animation is great for that.

1058
00:48:24,510 --> 00:48:26,010
ELIZABETH CHOE: I
mean, I personally

1059
00:48:26,010 --> 00:48:28,850
am not a huge fan of
AsapSCIENCE style,

1060
00:48:28,850 --> 00:48:31,142
but I also recognize
why it's super effective

1061
00:48:31,142 --> 00:48:32,600
and why other people
would like it.

1062
00:48:32,600 --> 00:48:35,210
Because like you said,
it's very engaging,

1063
00:48:35,210 --> 00:48:39,932
if only for just the visual--

1064
00:48:39,932 --> 00:48:41,640
JOSH GUNN: It's also
really well written.

1065
00:48:41,640 --> 00:48:43,014
I actually think
that it's better

1066
00:48:43,014 --> 00:48:45,830
written than it
is-- I mean, I think

1067
00:48:45,830 --> 00:48:49,750
there are any number of ways
it could have been performed.

1068
00:48:49,750 --> 00:48:51,460
But I think it's
really well written.

1069
00:48:51,460 --> 00:48:52,680
It's very concise.

1070
00:48:52,680 --> 00:48:53,900
ELIZABETH CHOE: Right.

1071
00:48:53,900 --> 00:48:55,790
It's very shareable.

1072
00:48:55,790 --> 00:48:57,830
It's sort of written
in this listicle form

1073
00:48:57,830 --> 00:49:01,950
that is dominating
web media in general.

1074
00:49:01,950 --> 00:49:04,620
It's like basically
taking a BuzzFeed article

1075
00:49:04,620 --> 00:49:06,310
and putting it into a video.

1076
00:49:06,310 --> 00:49:08,610
Yet with the visual
elements, there

1077
00:49:08,610 --> 00:49:11,540
is a motivation for you
to watch versus just

1078
00:49:11,540 --> 00:49:15,400
see it on text form, in
BuzzFeed, for instance.

1079
00:49:15,400 --> 00:49:19,270
JOSH GUNN: I actually thought
that the cat video lost

1080
00:49:19,270 --> 00:49:21,140
some of its
engagement for me when

1081
00:49:21,140 --> 00:49:24,300
he was-- there was
this sort of stream

1082
00:49:24,300 --> 00:49:27,070
of scientific information
and all you're doing

1083
00:49:27,070 --> 00:49:30,030
is just watching this
cat in slow motion.

1084
00:49:30,030 --> 00:49:34,180
And for me, it lost that
kind of key component

1085
00:49:34,180 --> 00:49:37,250
of what makes something
engaging, which

1086
00:49:37,250 --> 00:49:39,865
is the tight cohesion
between what you're seeing

1087
00:49:39,865 --> 00:49:41,440
and what's being said.

1088
00:49:41,440 --> 00:49:43,535
And also the streamlining
of scripting.

1089
00:49:43,535 --> 00:49:44,910
ELIZABETH CHOE:
And that's always

1090
00:49:44,910 --> 00:49:46,701
going to be a push-and-pull
that everyone's

1091
00:49:46,701 --> 00:49:50,120
going to experience, too,
with-- at some point,

1092
00:49:50,120 --> 00:49:52,500
are you explaining too
much to the viewer?

1093
00:49:52,500 --> 00:49:55,594
Should you just
rely on the visual?

1094
00:49:55,594 --> 00:49:57,260
Because you don't
want to be too jargony

1095
00:49:57,260 --> 00:50:00,320
and end up alienating an
audience, but at the same time

1096
00:50:00,320 --> 00:50:03,950
you have to cover-- you can't
cover everything, right?

1097
00:50:03,950 --> 00:50:06,480
You can't go in it in detail
and explain everything.

1098
00:50:06,480 --> 00:50:10,210
And that's a conflict that
we'll hit in later lectures,

1099
00:50:10,210 --> 00:50:12,430
how you can use
animation to help you

1100
00:50:12,430 --> 00:50:15,459
with that, some of the best
practices in that realm.

1101
00:50:15,459 --> 00:50:17,000
But that is something
to think about,

1102
00:50:17,000 --> 00:50:19,458
and I think that's a struggle
that everyone has with video,

1103
00:50:19,458 --> 00:50:20,630
for sure.

1104
00:50:20,630 --> 00:50:21,660
I have one more video.

1105
00:50:21,660 --> 00:50:23,160
Did anyone else
want to say anything

1106
00:50:23,160 --> 00:50:29,281
about what would happen
if you didn't sleep?

1107
00:50:29,281 --> 00:50:29,781
Yes.

1108
00:50:29,781 --> 00:50:31,489
JAIME GOLDSTEIN: You
know, I was watching

1109
00:50:31,489 --> 00:50:32,919
and I was thinking
because so much

1110
00:50:32,919 --> 00:50:37,560
of it is being shown
just sort of from Gary

1111
00:50:37,560 --> 00:50:39,595
of these pictures
and these words,

1112
00:50:39,595 --> 00:50:43,460
the thing that Crazy Russian
Hacker had and the cat guy had

1113
00:50:43,460 --> 00:50:47,695
that this guy doesn't is that
you know they're not making

1114
00:50:47,695 --> 00:50:49,380
anything up because
you can see the cat

1115
00:50:49,380 --> 00:50:51,852
and you can see the
bubbles, whereas there

1116
00:50:51,852 --> 00:50:53,425
are no references,
so how do I know

1117
00:50:53,425 --> 00:50:55,320
that everything
that is being said

1118
00:50:55,320 --> 00:50:57,192
is based on fact
upon fact upon fact.

1119
00:50:57,192 --> 00:50:59,590
He could be making all of
this up, for all I know.

1120
00:50:59,590 --> 00:51:01,996
And as I was watching
it, I was thinking,

1121
00:51:01,996 --> 00:51:04,930
how do I know he's not-- like
where's the truth in here?

1122
00:51:04,930 --> 00:51:05,472
I don't know.

1123
00:51:05,472 --> 00:51:07,388
JOSH GUNN: Yeah, there
is some of that element

1124
00:51:07,388 --> 00:51:09,770
of like the web has a lot of
information but what of it

1125
00:51:09,770 --> 00:51:12,520
is validated, or where
does it come from.

1126
00:51:12,520 --> 00:51:13,580
JAIME GOLDSTEIN: If there were
a little subtext somewhere even

1127
00:51:13,580 --> 00:51:15,170
just referencing
any of the ideas,

1128
00:51:15,170 --> 00:51:18,942
I'd feel more like, all
right, I can believe this guy.

1129
00:51:18,942 --> 00:51:20,650
But as it is, it's
hard, because you just

1130
00:51:20,650 --> 00:51:22,565
have a whiteboard and a
marker, and you think, well,

1131
00:51:22,565 --> 00:51:23,960
how do I know they've
done their research.

1132
00:51:23,960 --> 00:51:24,450
ELIZABETH CHOE: Right.

1133
00:51:24,450 --> 00:51:25,400
And I mean, with
YouTube channels,

1134
00:51:25,400 --> 00:51:27,691
a lot of them put in the
sources in their descriptions.

1135
00:51:27,691 --> 00:51:31,940
But I think the thing that maybe
I enjoy less about AsapSCIENCE

1136
00:51:31,940 --> 00:51:35,650
is you could switch the creator
out for any other person

1137
00:51:35,650 --> 00:51:39,770
and have any-- you could have
Siri from your phone narrate

1138
00:51:39,770 --> 00:51:42,240
the video for you and it
wouldn't be a completely

1139
00:51:42,240 --> 00:51:43,279
different experience.

1140
00:51:43,279 --> 00:51:45,320
I mean, it has its branding
because it was really

1141
00:51:45,320 --> 00:51:47,370
one of the first
channels to do that style

1142
00:51:47,370 --> 00:51:50,290
of hand-drawn animation,
so that's its thing.

1143
00:51:50,290 --> 00:51:53,770
But it doesn't have the
compelling sort of authenticity

1144
00:51:53,770 --> 00:51:55,930
that Crazy Russian
Hacker does, or Smarter

1145
00:51:55,930 --> 00:51:56,897
Every Day, or SciShow.

1146
00:51:56,897 --> 00:51:59,230
And I think a lot of it is
because you don't see someone

1147
00:51:59,230 --> 00:52:01,063
on screen, you don't
see a person on screen.

1148
00:52:01,063 --> 00:52:02,760
And maybe that's just
my personal taste,

1149
00:52:02,760 --> 00:52:05,560
but I do think that makes
a really big difference.

1150
00:52:05,560 --> 00:52:06,830
This video is from Vsauce.

1151
00:52:06,830 --> 00:52:09,350
Has anyone ever seen
that channel before?

1152
00:52:09,350 --> 00:52:09,850
Yeah.

1153
00:52:09,850 --> 00:52:12,990
So I actually haven't
watched all of this video

1154
00:52:12,990 --> 00:52:14,740
by myself because
I was scared to,

1155
00:52:14,740 --> 00:52:19,250
but this is why I
think it's creepy.

1156
00:52:19,250 --> 00:52:23,550
MICHAEL STEVENS: Hey,
Vsauce, Michael here.

1157
00:52:23,550 --> 00:52:27,340
Fear gives us life.

1158
00:52:27,340 --> 00:52:33,460
Being afraid of the right
things kept our ancestors alive.

1159
00:52:33,460 --> 00:52:37,110
It makes sense to be
afraid of poisonous insects

1160
00:52:37,110 --> 00:52:39,550
or hungry tigers.

1161
00:52:39,550 --> 00:52:46,360
But what about fear when there
is no clear and obvious danger?

1162
00:52:46,360 --> 00:52:52,458
For instance, a teddy bear
with a full set of human teeth.

1163
00:52:55,400 --> 00:52:56,400
ELIZABETH CHOE: I can't.

1164
00:52:56,400 --> 00:52:57,608
MICHAEL STEVENS: A smile.jpg.

1165
00:53:00,610 --> 00:53:03,750
There's something a little
off about these images.

1166
00:53:03,750 --> 00:53:06,970
Too much mystery
and strangeness.

1167
00:53:06,970 --> 00:53:09,060
But no obvious
threat the way there

1168
00:53:09,060 --> 00:53:10,824
is with a gun or a falling rock.

1169
00:53:10,824 --> 00:53:16,230
But yet they still incite
fear because they are creepy.

1170
00:53:16,230 --> 00:53:17,440
But why?

1171
00:53:17,440 --> 00:53:19,350
What gives us the creeps?

1172
00:53:19,350 --> 00:53:22,760
What causes something
to be creepy?

1173
00:53:26,120 --> 00:53:28,530
We are now in my
bedroom, the bedroom

1174
00:53:28,530 --> 00:53:30,893
I grew up in, in Kansas.

1175
00:53:30,893 --> 00:53:34,680
Like a lot of children my age,
I was terrified of scary stories

1176
00:53:34,680 --> 00:53:36,860
to tell in the dark.

1177
00:53:36,860 --> 00:53:39,480
But the very first book
that ever scared me

1178
00:53:39,480 --> 00:53:42,010
was the Curse of the Squirrel.

1179
00:53:42,010 --> 00:53:45,310
To this day I still
haven't finished the book,

1180
00:53:45,310 --> 00:53:46,960
but that's just me.

1181
00:53:46,960 --> 00:53:49,870
Psychologist James
Geer developed the Fear

1182
00:53:49,870 --> 00:53:53,540
Survey Schedule-II,
which he used to find out

1183
00:53:53,540 --> 00:53:55,700
what scared us the most.

1184
00:53:55,700 --> 00:53:58,880
Combined with the results of
a more recent Gallup poll,

1185
00:53:58,880 --> 00:54:04,420
these are the things that
scare most of us the most.

1186
00:54:04,420 --> 00:54:09,420
All of these things are
scary, but are they creepy?

1187
00:54:09,420 --> 00:54:10,960
Let's get more specific.

1188
00:54:10,960 --> 00:54:13,030
I love the way Stephen
King delineates

1189
00:54:13,030 --> 00:54:15,730
three types of scary stuff.

1190
00:54:15,730 --> 00:54:17,970
The first is the gross-out.

1191
00:54:17,970 --> 00:54:21,810
This is something
disgusting, morbid, diseased.

1192
00:54:21,810 --> 00:54:24,290
The second is horror.

1193
00:54:24,290 --> 00:54:27,080
Horror, to King,
is the unnatural;

1194
00:54:27,080 --> 00:54:30,990
a giant spider or being
grabbed in the dark when

1195
00:54:30,990 --> 00:54:33,300
you thought you were alone.

1196
00:54:33,300 --> 00:54:39,450
The third, terror, is
different, creepier.

1197
00:54:39,450 --> 00:54:42,550
He says terror is
coming home to find

1198
00:54:42,550 --> 00:54:46,200
that everything that
you own has been

1199
00:54:46,200 --> 00:54:50,290
replaced with an exact copy.

1200
00:54:50,290 --> 00:54:53,560
Terror is feeling
something behind you,

1201
00:54:53,560 --> 00:54:56,940
its breath on your neck, knowing
that you will be grabbed,

1202
00:54:56,940 --> 00:55:00,880
but then turning around to find
that there was never anything

1203
00:55:00,880 --> 00:55:04,950
there in the first place.

1204
00:55:04,950 --> 00:55:06,790
Not a lot of research
has been done

1205
00:55:06,790 --> 00:55:10,120
on that feeling, the creeps.

1206
00:55:10,120 --> 00:55:15,810
But many theories and ideas
involve vagueness, ambiguity.

1207
00:55:15,810 --> 00:55:21,340
For instance, masks, and
why clowns are creepy.

1208
00:55:21,340 --> 00:55:25,770
Claude Levi-Strauss wrote that
the facial disguise temporarily

1209
00:55:25,770 --> 00:55:27,880
eliminates from
social intercourse

1210
00:55:27,880 --> 00:55:31,500
the part of the body which
reveals personal feelings

1211
00:55:31,500 --> 00:55:33,320
and attitudes.

1212
00:55:33,320 --> 00:55:37,670
Part of the reason even
a neutral or happy mask

1213
00:55:37,670 --> 00:55:40,300
can be creepy may have
to do with ambiguity.

1214
00:55:40,300 --> 00:55:43,460
A mask hides the true
emotions and intentions

1215
00:55:43,460 --> 00:55:45,280
of the person underneath.

1216
00:55:45,280 --> 00:55:50,090
I don't know if the person
wearing that mask is a threat

1217
00:55:50,090 --> 00:55:52,450
or not.

1218
00:55:52,450 --> 00:55:56,340
Vagueness is creep when it
comes to the human form.

1219
00:55:56,340 --> 00:56:00,280
This is the famous
uncanny valley.

1220
00:56:00,280 --> 00:56:03,200
On a chart of humanness,
there's a zone

1221
00:56:03,200 --> 00:56:05,340
where something can
be almost entirely

1222
00:56:05,340 --> 00:56:07,910
human but off by just a little.

1223
00:56:07,910 --> 00:56:12,820
Not so wrong that it's clear
fake or funny, or so good

1224
00:56:12,820 --> 00:56:14,580
that it's indistinguishable.

1225
00:56:14,580 --> 00:56:18,280
Instead, it's just troubling.

1226
00:56:18,280 --> 00:56:20,090
The creepiness of
the uncanny valley

1227
00:56:20,090 --> 00:56:24,560
is wonderfully demonstrated
by John Bergeron's singing

1228
00:56:24,560 --> 00:56:25,980
androids.

1229
00:56:25,980 --> 00:56:28,280
Watch these videos
when you're alone.

1230
00:56:31,890 --> 00:56:36,230
A similar uneasy feeling
comes from Shaye Saint John,

1231
00:56:36,230 --> 00:56:38,730
a character created
by Eric Fournier.

1232
00:56:38,730 --> 00:56:43,580
Funny to some, nightmare
fuel to others.

1233
00:56:43,580 --> 00:56:47,060
Uncanny humanoids,
like all creepy things,

1234
00:56:47,060 --> 00:56:50,000
straddle a line
between two regions

1235
00:56:50,000 --> 00:56:53,850
that we can understand
and explain with language.

1236
00:56:53,850 --> 00:56:56,020
Francis T. McAndrew
and Sara Koehnke

1237
00:56:56,020 --> 00:57:00,240
describe being creeped out
as an adaptive human response

1238
00:57:00,240 --> 00:57:03,960
to the ambiguity of
threats from others.

1239
00:57:03,960 --> 00:57:07,540
Creepy things are kind
of a threat maybe,

1240
00:57:07,540 --> 00:57:10,570
but they're also kind
of not, so our brains

1241
00:57:10,570 --> 00:57:11,950
don't know what to do.

1242
00:57:11,950 --> 00:57:16,030
Some parts respond with fear
while other parts don't, and

1243
00:57:16,030 --> 00:57:17,320
they don't know why.

1244
00:57:17,320 --> 00:57:21,830
So instead of achieving a
typical fear response, horror,

1245
00:57:21,830 --> 00:57:24,850
we simply feel uneasy.

1246
00:57:24,850 --> 00:57:26,410
Terror.

1247
00:57:26,410 --> 00:57:28,270
Creeped out.

1248
00:57:28,270 --> 00:57:32,110
Between the mountains
of safety and danger,

1249
00:57:32,110 --> 00:57:35,420
there is a valley
of creepiness, where

1250
00:57:35,420 --> 00:57:38,850
the limits of our knowledge
and trust and security

1251
00:57:38,850 --> 00:57:40,950
aren't very clear.

1252
00:57:40,950 --> 00:57:46,324
Will looking at this cause
you to die one week later?

1253
00:57:46,324 --> 00:57:47,710
Impossible, right?

1254
00:57:50,490 --> 00:57:52,390
Maybe.

1255
00:57:52,390 --> 00:57:56,160
That's the terror of ambiguity.

1256
00:57:56,160 --> 00:57:59,300
We don't do well with ambiguity.

1257
00:57:59,300 --> 00:58:03,490
When it involves our own
intentions, it can make us lie.

1258
00:58:03,490 --> 00:58:04,760
And when it involves danger--

1259
00:58:04,760 --> 00:58:06,390
ELIZABETH CHOE: Can I stop or
you guys want to keep watching?

1260
00:58:06,390 --> 00:58:08,431
MICHAEL STEVENS: [INAUDIBLE]
recognizable threat,

1261
00:58:08,431 --> 00:58:10,473
it can make us think and
feel some pretty weird--

1262
00:58:10,473 --> 00:58:12,555
ELIZABETH CHOE: So he goes
on and talks more about

1263
00:58:12,555 --> 00:58:14,650
like the actual
psychology behind this.

1264
00:58:14,650 --> 00:58:17,670
The whole pop-up thing
is his trademark move.

1265
00:58:17,670 --> 00:58:20,885
He does that between
all of his transitions.

1266
00:58:20,885 --> 00:58:22,260
It's like a little
kitschy but it

1267
00:58:22,260 --> 00:58:24,910
works since he was
the first to do it.

1268
00:58:24,910 --> 00:58:27,260
But what did you guys
think about this one,

1269
00:58:27,260 --> 00:58:29,160
especially in comparison
to AsapSCIENCE?

1270
00:58:29,160 --> 00:58:33,380
Very similar format,
it's the why-what-how,

1271
00:58:33,380 --> 00:58:34,900
but executed very differently.

1272
00:58:37,600 --> 00:58:39,680
Or maybe was there
something about this video

1273
00:58:39,680 --> 00:58:41,600
that you liked better
than AsapSCIENCE

1274
00:58:41,600 --> 00:58:44,074
or that you disliked
compared to AsapSCIENCE.

1275
00:58:44,074 --> 00:58:44,574
Yep.

1276
00:58:44,574 --> 00:58:47,962
PAUL FOLINO: I think I got the
point maybe couple minutes in,

1277
00:58:47,962 --> 00:58:50,382
but it seemed like the
next three or four minutes,

1278
00:58:50,382 --> 00:58:53,300
he was just expounding on
that point that I already got.

1279
00:58:53,300 --> 00:58:54,787
ELIZABETH CHOE: Yeah, so it
dragged a little bit more.

1280
00:58:54,787 --> 00:58:57,172
PAUL FOLINO: Right, it never
really answered-- I mean,

1281
00:58:57,172 --> 00:58:58,880
you didn't finish the
video, but it never

1282
00:58:58,880 --> 00:59:00,770
seemed to answer the
question [INAUDIBLE].

1283
00:59:00,770 --> 00:59:01,350
ELIZABETH CHOE: Yeah.

1284
00:59:01,350 --> 00:59:02,810
I mean, he does
sort of eventually,

1285
00:59:02,810 --> 00:59:07,350
but it does take him a little
bit longer to get there.

1286
00:59:07,350 --> 00:59:07,850
Yes.

1287
00:59:07,850 --> 00:59:09,600
YULIYA KLOCHAN: It
still kept my attention

1288
00:59:09,600 --> 00:59:11,770
because he was very
close to the audience

1289
00:59:11,770 --> 00:59:14,220
and he was an
interesting character,

1290
00:59:14,220 --> 00:59:18,310
so I was interested
in knowing what

1291
00:59:18,310 --> 00:59:20,141
he would say next, [INAUDIBLE].

1292
00:59:20,141 --> 00:59:22,140
ELIZABETH CHOE: Yeah,
Michael Stevens definitely

1293
00:59:22,140 --> 00:59:24,930
is a very memorable
persona on screen.

1294
00:59:24,930 --> 00:59:26,820
And this is something
that we'll emphasize

1295
00:59:26,820 --> 00:59:27,770
throughout the course.

1296
00:59:27,770 --> 00:59:30,370
We don't want you
to feel like you

1297
00:59:30,370 --> 00:59:32,630
have to exaggerate
yourself or sort

1298
00:59:32,630 --> 00:59:35,417
of because this
persona on screen

1299
00:59:35,417 --> 00:59:36,500
that you're not naturally.

1300
00:59:36,500 --> 00:59:39,060
It's not about you
trying to adapt

1301
00:59:39,060 --> 00:59:41,460
into a Bill Nye personality
or into a Michael Stevens

1302
00:59:41,460 --> 00:59:42,394
personality.

1303
00:59:42,394 --> 00:59:44,060
A lot of people find
him super annoying,

1304
00:59:44,060 --> 00:59:45,740
and I don't blame them.

1305
00:59:45,740 --> 00:59:49,500
It's really about
how to best capture

1306
00:59:49,500 --> 00:59:51,510
who you are in real
life and just maintain

1307
00:59:51,510 --> 00:59:54,920
that as much as possible
in front of a camera,

1308
00:59:54,920 --> 00:59:57,550
because maybe he is a little
bit different in real life,

1309
00:59:57,550 --> 01:00:00,330
but it doesn't seem super
unnatural when you watch,

1310
01:00:00,330 --> 01:00:00,830
right?

1311
01:00:00,830 --> 01:00:02,770
You're not like, this
guy is acting just

1312
01:00:02,770 --> 01:00:04,660
like totally over the top.

1313
01:00:04,660 --> 01:00:07,990
It's just part of his
brand, part of his persona

1314
01:00:07,990 --> 01:00:10,750
to get his message across.

1315
01:00:10,750 --> 01:00:14,320
I do think that something
that was effective about that

1316
01:00:14,320 --> 01:00:16,960
video is it took all these
concepts that you learn

1317
01:00:16,960 --> 01:00:18,940
in cognitive
psychology, but again,

1318
01:00:18,940 --> 01:00:21,300
instead of doing
a video on here's

1319
01:00:21,300 --> 01:00:24,300
the definition of uncanny
valley or things like that,

1320
01:00:24,300 --> 01:00:26,060
he tapped into something
that resonates--

1321
01:00:26,060 --> 01:00:27,560
at least it resonates
a lot with me,

1322
01:00:27,560 --> 01:00:29,570
because I was super
creeped out by this video.

1323
01:00:29,570 --> 01:00:32,400
But it taps into something
that we experience every day,

1324
01:00:32,400 --> 01:00:36,580
that it's a very relatable
video, that it's contextual,

1325
01:00:36,580 --> 01:00:39,080
that I don't feel
like I'm watching

1326
01:00:39,080 --> 01:00:40,660
a lecture, necessarily, on it.

1327
01:00:40,660 --> 01:00:44,280
I don't feel like I'm even
watching a Khan Academy video.

1328
01:00:44,280 --> 01:00:46,580
That I just want to sit
there and learn more.

1329
01:00:46,580 --> 01:00:49,660
I wanted to learn more for the
first two minutes, at least.

1330
01:00:49,660 --> 01:00:52,770
I don't know if you
guys felt that way.

1331
01:00:52,770 --> 01:00:54,050
Yes, no?

1332
01:00:54,050 --> 01:00:54,688
Yeah.

1333
01:00:54,688 --> 01:00:59,560
JOSH CHEONG: I felt like
I got pretty much what--

1334
01:00:59,560 --> 01:01:01,646
after he showed me the
graph of the thing,

1335
01:01:01,646 --> 01:01:03,574
I didn't really
understand the graph,

1336
01:01:03,574 --> 01:01:06,466
but he kind of explained
it with like, oh,

1337
01:01:06,466 --> 01:01:10,322
you need to be in between
two points to be creepy.

1338
01:01:10,322 --> 01:01:14,696
Then after that, it's all about
trying to figure it myself.

1339
01:01:14,696 --> 01:01:16,632
He does this
connect-the-dots thing.

1340
01:01:16,632 --> 01:01:19,052
He doesn't really give
you the right answers.

1341
01:01:19,052 --> 01:01:21,535
He seems to be seeding you.

1342
01:01:21,535 --> 01:01:22,410
ELIZABETH CHOE: Yeah.

1343
01:01:22,410 --> 01:01:25,370
The payoff happened, but it
takes a long time to get there.

1344
01:01:25,370 --> 01:01:27,422
And maybe he loses
interest along the way.

1345
01:01:27,422 --> 01:01:28,880
Again, that's
something that you're

1346
01:01:28,880 --> 01:01:31,450
going to have to figure
out how to balance,

1347
01:01:31,450 --> 01:01:34,327
how much tension do you want
to build up for the audience.

1348
01:01:34,327 --> 01:01:36,910
Maybe you'll do it too much, to
the point where you lose them.

1349
01:01:36,910 --> 01:01:41,300
Maybe you do it to just create
the buildup to the final reveal

1350
01:01:41,300 --> 01:01:42,450
of your video.

1351
01:01:45,730 --> 01:01:49,250
In addition to being these
digestible, listicle type

1352
01:01:49,250 --> 01:01:51,470
chunks that are
shareable and contextual,

1353
01:01:51,470 --> 01:01:54,070
YouTube videos are also
super searchable, right?

1354
01:01:54,070 --> 01:01:56,710
So you can just go
on YouTube and search

1355
01:01:56,710 --> 01:02:00,570
for literally anything you
want, and you'll have suggested

1356
01:02:00,570 --> 01:02:02,340
videos that pop up at
the end, so there's

1357
01:02:02,340 --> 01:02:06,990
this sort of inherent--
what was the thing I put?

1358
01:02:06,990 --> 01:02:08,880
There's an inherent
vetting process

1359
01:02:08,880 --> 01:02:11,370
that happens on
YouTube, that you

1360
01:02:11,370 --> 01:02:15,070
have a compendium of
knowledge and compendium

1361
01:02:15,070 --> 01:02:17,130
of resources available
to you, and you

1362
01:02:17,130 --> 01:02:19,450
have things like
comments and suggested

1363
01:02:19,450 --> 01:02:23,420
views and subscriptions to
help you decide what to watch.

1364
01:02:23,420 --> 01:02:24,920
And everything's
at your fingertips.

1365
01:02:24,920 --> 01:02:28,335
You can get whatever you
want, whenever you want it.

1366
01:02:28,335 --> 01:02:30,210
Then there's this whole
trusted guide element

1367
01:02:30,210 --> 01:02:32,650
that is really-- it's
just as present on YouTube

1368
01:02:32,650 --> 01:02:33,690
as it is on TV.

1369
01:02:33,690 --> 01:02:36,770
You have people like
Vsauce and Michael Stevens.

1370
01:02:36,770 --> 01:02:38,850
Even with AsapSCIENCE,
you don't see the guy,

1371
01:02:38,850 --> 01:02:41,360
but it has a really
strong brand.

1372
01:02:41,360 --> 01:02:44,860
And it's one of
those things where

1373
01:02:44,860 --> 01:02:46,810
if you replaced a
successful YouTube

1374
01:02:46,810 --> 01:02:50,469
video with another person or
another narrator-- a litmus

1375
01:02:50,469 --> 01:02:52,510
test that I like to think
of is if you replace it

1376
01:02:52,510 --> 01:02:54,867
and it's just not really
a noticeable change,

1377
01:02:54,867 --> 01:02:56,700
then maybe there's
something with your video

1378
01:02:56,700 --> 01:02:58,460
that isn't very engaging.

1379
01:02:58,460 --> 01:03:01,580
That if you swapped out any
of your classmates for it

1380
01:03:01,580 --> 01:03:05,632
and it still sort of felt
like the same video, maybe

1381
01:03:05,632 --> 01:03:07,340
there's more of your
inherent personality

1382
01:03:07,340 --> 01:03:10,440
that you can highlight
more in the video.

1383
01:03:10,440 --> 01:03:14,050
And then, with YouTube, there's
no invisible college, right?

1384
01:03:14,050 --> 01:03:15,870
There's no gatekeeper
of knowledge.

1385
01:03:15,870 --> 01:03:21,010
You don't have to pay $100 to
access a lecture course, right?

1386
01:03:21,010 --> 01:03:22,510
Anybody can access
OpenCourseWare.

1387
01:03:22,510 --> 01:03:25,550
Anybody can go watch
a Vsauce video.

1388
01:03:25,550 --> 01:03:28,250
Anyone can comment, so
theoretically, anyone

1389
01:03:28,250 --> 01:03:32,110
can contribute to that community
and landscape, and its products

1390
01:03:32,110 --> 01:03:33,530
as well.

1391
01:03:33,530 --> 01:03:35,510
I think we're starting
to see more of it.

1392
01:03:35,510 --> 01:03:36,910
You see more female
creators, you

1393
01:03:36,910 --> 01:03:41,610
see a little bit more diversity
in the YouTube environment

1394
01:03:41,610 --> 01:03:43,110
than you do on TV, certainly.

1395
01:03:43,110 --> 01:03:48,870
But again, there's a lot of
room to grow in that regard.

1396
01:03:48,870 --> 01:03:51,060
And then finally,
for TV, TV is very

1397
01:03:51,060 --> 01:03:53,720
different from online
video, which is something

1398
01:03:53,720 --> 01:03:57,410
that I didn't actually realize
myself until fairly recently.

1399
01:03:57,410 --> 01:03:59,060
I always kind of
thought if I want

1400
01:03:59,060 --> 01:04:02,170
to make a good video online
then I should just sort of apply

1401
01:04:02,170 --> 01:04:04,860
the best practices of
making a good video on TV

1402
01:04:04,860 --> 01:04:07,180
and just shorten it to a
five-minute online video.

1403
01:04:07,180 --> 01:04:09,130
But that's not
necessarily the case,

1404
01:04:09,130 --> 01:04:11,350
because the priority
of TV, first of all,

1405
01:04:11,350 --> 01:04:13,320
is to hold your attention.

1406
01:04:13,320 --> 01:04:15,790
When you're watching TV, there
are going to be commercials,

1407
01:04:15,790 --> 01:04:17,370
you can flip the channel.

1408
01:04:17,370 --> 01:04:20,350
I guess you can do that
with online stuff as well,

1409
01:04:20,350 --> 01:04:26,840
but the distractions
aren't necessarily as huge.

1410
01:04:26,840 --> 01:04:28,560
When you go to a
commercial, you're

1411
01:04:28,560 --> 01:04:30,610
going to want to
change the channel.

1412
01:04:30,610 --> 01:04:33,720
So they really have to
hook your attention,

1413
01:04:33,720 --> 01:04:36,490
and they do that a lot with
some of the production styles.

1414
01:04:36,490 --> 01:04:40,990
On TV you'll tend to see a lot
more multi-camera type videos.

1415
01:04:40,990 --> 01:04:44,310
You'll see a lot of quick
cuts, a lot of effects

1416
01:04:44,310 --> 01:04:45,881
to sort of keep you engaged.

1417
01:04:45,881 --> 01:04:48,380
I noticed that about the Hobbit,
there was like an explosion

1418
01:04:48,380 --> 01:04:50,610
every other second.

1419
01:04:50,610 --> 01:04:53,640
And they do that
because they have

1420
01:04:53,640 --> 01:04:55,610
to have this really
big hold on you

1421
01:04:55,610 --> 01:04:58,600
for a much longer
period of time.

1422
01:04:58,600 --> 01:05:01,600
Whereas on online videos,
stuff like Smarter Every Day,

1423
01:05:01,600 --> 01:05:03,310
it's just kind of the
same camera set up

1424
01:05:03,310 --> 01:05:06,580
on a tripod that's shooting
you the whole time.

1425
01:05:06,580 --> 01:05:09,580
And TV is very much
about narrative,

1426
01:05:09,580 --> 01:05:10,920
about telling a story.

1427
01:05:10,920 --> 01:05:12,510
And I think that
that is something

1428
01:05:12,510 --> 01:05:15,570
that you should do in an online
video too, but it's not as much

1429
01:05:15,570 --> 01:05:16,780
of a necessity.

1430
01:05:16,780 --> 01:05:20,096
Things like-- I don't know,
any viral video that's

1431
01:05:20,096 --> 01:05:21,970
not necessarily
science-related, most of them

1432
01:05:21,970 --> 01:05:23,510
don't really have a story.

1433
01:05:23,510 --> 01:05:26,779
It's more just like,
here's a naked celebrity.

1434
01:05:26,779 --> 01:05:28,570
I guess you could create
a story out of it,

1435
01:05:28,570 --> 01:05:30,361
but it's not
narrative-driven, necessarily,

1436
01:05:30,361 --> 01:05:34,680
whereas TV very much is,
and movies are as well.

1437
01:05:34,680 --> 01:05:37,010
I wanted to show
you another video,

1438
01:05:37,010 --> 01:05:39,990
and this is from
Connections, which I never

1439
01:05:39,990 --> 01:05:43,472
heard of until Chris showed
us this show in his class.

1440
01:05:43,472 --> 01:05:44,180
But it's awesome.

1441
01:05:44,180 --> 01:05:48,740
It's like one of the first
science TV shows in the UK.

1442
01:05:48,740 --> 01:05:51,847
And this is from Connections 2,
and it's a whodunnit episode.

1443
01:07:02,540 --> 01:07:06,130
JAMES BURKE: I suppose a
detective catches a crook

1444
01:07:06,130 --> 01:07:09,980
because he follows a trail from
one uniquely relevant event

1445
01:07:09,980 --> 01:07:12,390
or person to another,
until he finds

1446
01:07:12,390 --> 01:07:14,320
a unique piece of
evidence that points

1447
01:07:14,320 --> 01:07:18,190
to the only person in the world
who could've done the deed.

1448
01:07:18,190 --> 01:07:21,672
And strangely
enough, the story I'm

1449
01:07:21,672 --> 01:07:24,724
about to tell you about
why modern detectives are

1450
01:07:24,724 --> 01:07:28,092
able to do that at all follows
exactly the same kind of tail,

1451
01:07:28,092 --> 01:07:32,174
from one unique character
to another through history.

1452
01:07:32,174 --> 01:07:35,570
Here's my first
unique character,

1453
01:07:35,570 --> 01:07:38,915
Steve Davis, one of the best
snooker players in the world.

1454
01:07:42,100 --> 01:07:44,750
ELIZABETH CHOE: Ah,
don't look at this.

1455
01:07:44,750 --> 01:07:47,550
So that is a show that
aired-- I don't know,

1456
01:07:47,550 --> 01:07:48,740
was that like the '70s?

1457
01:07:48,740 --> 01:07:50,260
CHRIS BOEBEL: It's the
late '70s [INAUDIBLE].

1458
01:07:50,260 --> 01:07:51,343
ELIZABETH CHOE: Late '70s?

1459
01:07:51,343 --> 01:07:53,670
And this is Connections 2,
so maybe it's early '80s.

1460
01:07:53,670 --> 01:07:56,970
I don't know about you, I
felt like that was so endless.

1461
01:07:56,970 --> 01:08:01,710
It took him two whole minutes
to even just introduce

1462
01:08:01,710 --> 01:08:04,110
the first character of
what he was talking about,

1463
01:08:04,110 --> 01:08:05,070
and it felt--

1464
01:08:05,070 --> 01:08:06,350
CHRIS BOEBEL: Isn't it
amazing how the pacing has

1465
01:08:06,350 --> 01:08:07,420
changed, and our expectations?

1466
01:08:07,420 --> 01:08:09,590
ELIZABETH CHOE: Right, it
felt agonizing, almost.

1467
01:08:09,590 --> 01:08:12,780
And I'm sure if I watched it
on TV and I saw the rest of it,

1468
01:08:12,780 --> 01:08:13,560
it would be fine.

1469
01:08:13,560 --> 01:08:17,779
But I mean, compare that to
AsapSCIENCE, for instance.

1470
01:08:17,779 --> 01:08:21,390
The priority of what
Connections producers were

1471
01:08:21,390 --> 01:08:24,080
doing with that video is very
different than AsapSCIENCE,

1472
01:08:24,080 --> 01:08:26,305
and you have a very
different effect.

1473
01:08:26,305 --> 01:08:28,390
I actually really
enjoyed Connections,

1474
01:08:28,390 --> 01:08:30,010
I really liked the show too.

1475
01:08:30,010 --> 01:08:32,649
So I'm not saying it's a
bad thing, necessarily.

1476
01:08:32,649 --> 01:08:35,979
But that's sort of what happens
when you're applying this best

1477
01:08:35,979 --> 01:08:37,870
practices in TV
or movies and you

1478
01:08:37,870 --> 01:08:41,300
think you can just move it
over to video on the web

1479
01:08:41,300 --> 01:08:42,359
and just shorten it down.

1480
01:08:42,359 --> 01:08:46,170
That's not necessarily going
to be the best approach,

1481
01:08:46,170 --> 01:08:47,790
because some of
the best practices

1482
01:08:47,790 --> 01:08:50,620
aren't going to
work, necessarily.

1483
01:08:50,620 --> 01:08:52,390
So what I would
like you guys to do

1484
01:08:52,390 --> 01:08:55,710
right now, if you can
access-- does everyone

1485
01:08:55,710 --> 01:08:59,779
have a laptop with them or can
share a laptop with someone?

1486
01:08:59,779 --> 01:09:05,590
If you go onto our class
site, it's mit219.tumblr.com.

1487
01:09:05,590 --> 01:09:08,560
You'll see a post that I
just put up earlier today,

1488
01:09:08,560 --> 01:09:13,072
and it has a link to a Google
doc that should look like this.

1489
01:09:24,640 --> 01:09:26,899
Should look like this.

1490
01:09:26,899 --> 01:09:31,670
And what I'd like you guys to
do for maybe the next like 20-25

1491
01:09:31,670 --> 01:09:35,271
minutes-- and feel free to get
up and stretch during this time

1492
01:09:35,271 --> 01:09:35,770
if you want.

1493
01:09:35,770 --> 01:09:37,979
If you need to use the
restroom, feel free to head out.

1494
01:09:37,979 --> 01:09:38,830
JAIME GOLDSTEIN: Can you
write the URL on the board?

1495
01:09:38,830 --> 01:09:39,871
ELIZABETH CHOE: Oh, yeah.

1496
01:09:43,060 --> 01:09:44,539
Can everyone see on this board?

1497
01:09:57,290 --> 01:09:59,850
There should only be
one post, and it'll

1498
01:09:59,850 --> 01:10:02,290
have a link to
the class syllabus

1499
01:10:02,290 --> 01:10:06,150
that, again, has all the
videos that we've watched today

1500
01:10:06,150 --> 01:10:09,617
and the assignments
for all the days.

1501
01:10:09,617 --> 01:10:11,700
And then it should have a
link to this Google doc.

1502
01:10:11,700 --> 01:10:13,210
And what I'd like
for you guys to do

1503
01:10:13,210 --> 01:10:16,700
is to watch the videos
that I've listed here,

1504
01:10:16,700 --> 01:10:19,930
and then record the exact
time code in which you

1505
01:10:19,930 --> 01:10:23,110
want to stop watching the video,
and just be completely honest.

1506
01:10:23,110 --> 01:10:26,580
And then afterwards we'll talk
about maybe some of the reasons

1507
01:10:26,580 --> 01:10:29,360
why you thought certain
videos were more engaging.

1508
01:10:29,360 --> 01:10:35,610
Think about why you might still
think that a video is good even

1509
01:10:35,610 --> 01:10:38,040
if you wanted to turn it off.

1510
01:10:38,040 --> 01:10:39,249
And we'll convene at the end.

1511
01:10:39,249 --> 01:10:40,873
But again, feel free--
if you guys need

1512
01:10:40,873 --> 01:10:43,610
to get up and stretch or go to
the bathroom during this time,

1513
01:10:43,610 --> 01:10:44,690
feel free to do that too.

1514
01:10:44,690 --> 01:10:46,523
And you guys can talk
to each other as well.

1515
01:11:09,440 --> 01:11:11,750
All right, let's
go ahead and talk.

1516
01:11:11,750 --> 01:11:14,840
I know you guys
are finishing up.

1517
01:11:14,840 --> 01:11:18,310
Just so you know, every day
you'll do blog reflections,

1518
01:11:18,310 --> 01:11:21,200
and if you want to talk a little
bit more about your thoughts

1519
01:11:21,200 --> 01:11:23,780
on these videos in your blog
today, that's totally fine.

1520
01:11:23,780 --> 01:11:25,690
I know we're not going
to get everything.

1521
01:11:25,690 --> 01:11:27,950
But did anyone have
a favorite video?

1522
01:11:33,357 --> 01:11:35,526
Yes.

1523
01:11:35,526 --> 01:11:37,109
ANDREA DESROSIERS:
The Veritasium one.

1524
01:11:37,109 --> 01:11:38,640
ELIZABETH CHOE: Oh, Veritasium,
you like that one the best?

1525
01:11:38,640 --> 01:11:40,804
Yeah, actually, that
one's my favorite too.

1526
01:11:40,804 --> 01:11:41,970
ANDREA DESROSIERS: And Asap.

1527
01:11:41,970 --> 01:11:43,400
ELIZABETH CHOE: And Asap.

1528
01:11:43,400 --> 01:11:46,070
What about those two videos
did you like, or maybe

1529
01:11:46,070 --> 01:11:49,280
can you hit upon one thing
that you found particularly--

1530
01:11:49,280 --> 01:11:53,462
ANDREA DESROSIERS: Veritasium,
very charismatic host,

1531
01:11:53,462 --> 01:11:57,454
and kept the pace
not going so quickly,

1532
01:11:57,454 --> 01:12:00,448
but not going too slowly.

1533
01:12:00,448 --> 01:12:03,000
Then for AsapSCIENCE,
it was very crisp

1534
01:12:03,000 --> 01:12:07,572
and conveyed the point very
succinctly and clearly.

1535
01:12:07,572 --> 01:12:09,780
ELIZABETH CHOE: That's
interesting because I actually

1536
01:12:09,780 --> 01:12:12,680
thought that those were the
two videos that I personally

1537
01:12:12,680 --> 01:12:14,410
watched most of myself.

1538
01:12:14,410 --> 01:12:17,490
And I'm not necessarily the
biggest fan of AsapSCIENCE,

1539
01:12:17,490 --> 01:12:19,941
but I did want to
watch the whole thing.

1540
01:12:19,941 --> 01:12:21,690
The thing about
Veritasium is interesting,

1541
01:12:21,690 --> 01:12:26,310
because he's not using super
fancy equipment, per se.

1542
01:12:26,310 --> 01:12:28,360
His stuff looks a lot
better than a lot of what's

1543
01:12:28,360 --> 01:12:33,460
on YouTube, but he's using just
basic DSLR cameras, I think.

1544
01:12:33,460 --> 01:12:37,290
But his background, he's a
physicist, that's his PhD.

1545
01:12:37,290 --> 01:12:39,730
But he does physics
education as well,

1546
01:12:39,730 --> 01:12:43,670
so he's very cognizant of the
role of video in education,

1547
01:12:43,670 --> 01:12:45,920
and that's going to be one
of your reading assignments

1548
01:12:45,920 --> 01:12:48,110
tonight, is watching
one of his videos.

1549
01:12:48,110 --> 01:12:51,180
But I do think that he does a
very interesting job and a very

1550
01:12:51,180 --> 01:12:54,490
good job of being very natural
on screen, charismatic,

1551
01:12:54,490 --> 01:12:55,430
like you were saying.

1552
01:12:55,430 --> 01:12:56,930
There's something
about his delivery

1553
01:12:56,930 --> 01:13:00,410
that is-- he talks the way that
you would think he would just

1554
01:13:00,410 --> 01:13:03,120
talk in real life,
which is actually

1555
01:13:03,120 --> 01:13:05,490
really hard to do on video.

1556
01:13:05,490 --> 01:13:08,070
Did anyone else-- let's
see what you guys thought

1557
01:13:08,070 --> 01:13:11,310
about the Veritasium video.

1558
01:13:11,310 --> 01:13:15,627
It looks like a lot of people
actually finished that one.

1559
01:13:15,627 --> 01:13:17,960
And I didn't mention this
before, but maybe you noticed.

1560
01:13:17,960 --> 01:13:20,050
All these videos are
talking about evolution

1561
01:13:20,050 --> 01:13:22,460
or natural selection
in some way or another,

1562
01:13:22,460 --> 01:13:25,810
but they're doing it
very different ways.

1563
01:13:25,810 --> 01:13:27,830
What about anyone
else, let's see.

1564
01:13:31,090 --> 01:13:33,480
Nathan, you finished SciShow.

1565
01:13:33,480 --> 01:13:37,100
What was it about
SciShow that you liked?

1566
01:13:39,325 --> 01:13:40,700
NATHAN HERNANDEZ:
I'd say I liked

1567
01:13:40,700 --> 01:13:43,820
that there's a little bit
of humor in his video.

1568
01:13:43,820 --> 01:13:45,420
I think that's
something that tends

1569
01:13:45,420 --> 01:13:47,689
to keep my attention better.

1570
01:13:47,689 --> 01:13:49,230
ELIZABETH CHOE:
Sorry, that you what?

1571
01:13:49,230 --> 01:13:50,730
NATHAN HERNANDEZ:
Just when you have

1572
01:13:50,730 --> 01:13:53,617
a little bit of humor inserted,
that keeps my attention better.

1573
01:13:53,617 --> 01:13:56,200
ELIZABETH CHOE: And Hank Green
is a very neurotic host, right?

1574
01:13:56,200 --> 01:13:58,650
He talks like this
and he has quick cuts

1575
01:13:58,650 --> 01:14:01,110
and he's very
hyper all the time,

1576
01:14:01,110 --> 01:14:03,110
and it works for him
because that's just

1577
01:14:03,110 --> 01:14:04,400
who he is in real life.

1578
01:14:04,400 --> 01:14:08,970
So again, being Hank Green
doesn't make you successful,

1579
01:14:08,970 --> 01:14:11,510
it's that he's able to just be
himself on camera that works.

1580
01:14:15,610 --> 01:14:20,540
Did anyone have a least favorite
video or one-- let's see,

1581
01:14:20,540 --> 01:14:24,610
a lot of people
ended the TED-Ed one,

1582
01:14:24,610 --> 01:14:26,820
or maybe a couple people
ended that one early,

1583
01:14:26,820 --> 01:14:30,800
and the Khan Academy one early.

1584
01:14:30,800 --> 01:14:33,090
Any thoughts about those?

1585
01:14:33,090 --> 01:14:36,400
What is it that made
you-- I keep doing that.

1586
01:14:36,400 --> 01:14:38,140
What is it about
those videos that

1587
01:14:38,140 --> 01:14:39,415
made you turn them off early?

1588
01:14:52,300 --> 01:14:56,750
Paul, you turned that
one off at 17 seconds.

1589
01:14:56,750 --> 01:14:58,374
That's pretty early.

1590
01:14:58,374 --> 01:14:59,290
PAUL FOLINO: What one?

1591
01:14:59,290 --> 01:15:00,712
ELIZABETH CHOE: The
Khan Academy one.

1592
01:15:00,712 --> 01:15:01,696
PAUL FOLINO: Oh, yeah.

1593
01:15:01,696 --> 01:15:07,600
I just thought that was a bad
way of portraying evolution.

1594
01:15:07,600 --> 01:15:11,044
I usually use Khan Academy
for math or something

1595
01:15:11,044 --> 01:15:14,000
like that, because he is going
through all the hand motions

1596
01:15:14,000 --> 01:15:15,470
and how to do an equation.

1597
01:15:15,470 --> 01:15:15,765
ELIZABETH CHOE: Right.

1598
01:15:15,765 --> 01:15:17,806
PAUL FOLINO: But I think
something like evolution

1599
01:15:17,806 --> 01:15:21,160
that's kind of nebulous to begin
with, I'd like to see pictures,

1600
01:15:21,160 --> 01:15:24,173
not really-- I don't know.

1601
01:15:24,173 --> 01:15:25,985
That's just my personal opinion.

1602
01:15:25,985 --> 01:15:27,750
ELIZABETH CHOE: Well,
yeah, I personally

1603
01:15:27,750 --> 01:15:28,750
agree with that as well.

1604
01:15:28,750 --> 01:15:31,440
I mean, I also feel
like Khan Academy works

1605
01:15:31,440 --> 01:15:32,890
for a very certain
type of video,

1606
01:15:32,890 --> 01:15:35,872
and that tends to be a
numbers and graph-driven one.

1607
01:15:35,872 --> 01:15:37,830
And we'll talk about this
more in a little bit,

1608
01:15:37,830 --> 01:15:41,030
but when you think about why
you want to make a video,

1609
01:15:41,030 --> 01:15:44,460
you have to consider quite
a bit about the visuals

1610
01:15:44,460 --> 01:15:46,380
that you're going to
use and how that's

1611
01:15:46,380 --> 01:15:48,740
going to motivate the story
that you're going to tell,

1612
01:15:48,740 --> 01:15:52,095
or trying to convey the message
that you're trying to convey.

1613
01:15:52,095 --> 01:15:54,220
And I know-- I wish we
could talk a little bit more

1614
01:15:54,220 --> 01:15:57,440
about this, but we are running
a little bit short on time

1615
01:15:57,440 --> 01:15:59,320
and I want to leave
enough room for Chris.

1616
01:15:59,320 --> 01:16:02,400
So if you can respond
a little bit more

1617
01:16:02,400 --> 01:16:04,909
in your blog reflection tonight
about some of these videos,

1618
01:16:04,909 --> 01:16:05,825
that would be awesome.

1619
01:16:09,900 --> 01:16:14,570
So we've hit upon
some qualities of what

1620
01:16:14,570 --> 01:16:16,990
makes a good video, a
good educational video,

1621
01:16:16,990 --> 01:16:21,100
a good YouTube video,
a good TV video.

1622
01:16:21,100 --> 01:16:23,620
But the question of
what is good, right?

1623
01:16:23,620 --> 01:16:25,560
Because ultimately
we have to figure out

1624
01:16:25,560 --> 01:16:28,700
what we're going to define
as success in this class,

1625
01:16:28,700 --> 01:16:33,370
because otherwise there's going
to be no impetus to improve.

1626
01:16:33,370 --> 01:16:37,130
It's a really hard question,
because what is good

1627
01:16:37,130 --> 01:16:38,940
is really intangible.

1628
01:16:38,940 --> 01:16:42,280
It's really inaccessible, at
least in the field of video,

1629
01:16:42,280 --> 01:16:45,870
or whatever we're going to try
to do, because what is good

1630
01:16:45,870 --> 01:16:49,060
is very much a matter of
personal taste, right?

1631
01:16:49,060 --> 01:16:53,380
Like I personally don't really
like the AsapSCIENCE videos,

1632
01:16:53,380 --> 01:16:56,197
but I recognize them as
being successful in what

1633
01:16:56,197 --> 01:16:56,780
they're doing.

1634
01:16:56,780 --> 01:17:00,790
They're engaging people,
they're spreading STEM literacy,

1635
01:17:00,790 --> 01:17:02,544
they're getting
people to be curious.

1636
01:17:02,544 --> 01:17:04,960
I'm not sure how much they're
opening the door to science,

1637
01:17:04,960 --> 01:17:06,890
but I mean they're doing
good things even if I

1638
01:17:06,890 --> 01:17:09,800
don't personally enjoy them.

1639
01:17:09,800 --> 01:17:13,290
And a lot of people love
Hank Green from SciShow

1640
01:17:13,290 --> 01:17:15,420
and a lot of people think
he's super annoying.

1641
01:17:15,420 --> 01:17:19,100
So again, it's really hard
to define what is good.

1642
01:17:19,100 --> 01:17:22,580
We often try to approximate
what is good by other measures,

1643
01:17:22,580 --> 01:17:25,200
so a lot of times
we'll look at virality,

1644
01:17:25,200 --> 01:17:27,635
how many views it has, how
many subscribers they have.

1645
01:17:27,635 --> 01:17:32,840
But again, virality is something
that you can sort of assess

1646
01:17:32,840 --> 01:17:35,390
in retrospect but
it's not necessarily

1647
01:17:35,390 --> 01:17:38,240
the most predictive measure,
because so much of it

1648
01:17:38,240 --> 01:17:40,252
rests on confounding
variables like what

1649
01:17:40,252 --> 01:17:42,460
are the current events that
are happening at the time

1650
01:17:42,460 --> 01:17:46,960
that the video comes out,
what's the personality like.

1651
01:17:46,960 --> 01:17:50,940
Have you guys ever seen
the OK Go music videos?

1652
01:17:50,940 --> 01:17:54,260
So they're this popular
alternative band,

1653
01:17:54,260 --> 01:17:57,420
and their big breakout
video was them

1654
01:17:57,420 --> 01:18:00,460
doing this huge choreographed
dance on four treadmills.

1655
01:18:00,460 --> 01:18:02,160
And ever since then
they've sort of

1656
01:18:02,160 --> 01:18:04,832
tried to do this similar
thing of a single take shot.

1657
01:18:04,832 --> 01:18:06,540
I didn't actually show
any of the videos,

1658
01:18:06,540 --> 01:18:09,060
but I can send you
guys the links later.

1659
01:18:09,060 --> 01:18:12,600
They do these single cam,
continuous shots of just

1660
01:18:12,600 --> 01:18:15,777
like outrageous dances,
and I don't even

1661
01:18:15,777 --> 01:18:16,860
know how to describe them.

1662
01:18:16,860 --> 01:18:19,530
But the first one was the
one where they struck gold.

1663
01:18:19,530 --> 01:18:22,230
And they repeated the same
thing, it was the same people,

1664
01:18:22,230 --> 01:18:24,300
but their later ones,
which are successful,

1665
01:18:24,300 --> 01:18:26,650
aren't nearly as successful
as that treadmill one.

1666
01:18:26,650 --> 01:18:29,610
So there are qualities
about viral video

1667
01:18:29,610 --> 01:18:32,430
that are universal,
things like authenticity.

1668
01:18:32,430 --> 01:18:34,570
A naked celebrity is
always going to go viral.

1669
01:18:34,570 --> 01:18:37,660
But it's very hard to build
a predictive model based off

1670
01:18:37,660 --> 01:18:41,549
of a regression that you're
looking at in the past.

1671
01:18:41,549 --> 01:18:43,590
And then you have things
like learning objectives

1672
01:18:43,590 --> 01:18:47,440
that you can use to
qualify something as good.

1673
01:18:47,440 --> 01:18:51,350
You can say, oh, this video
hit upon all to the standards

1674
01:18:51,350 --> 01:18:54,060
that seventh graders in the
US need to know about biology

1675
01:18:54,060 --> 01:18:55,930
so it's a good video,
and maybe that's

1676
01:18:55,930 --> 01:18:57,850
why Bozeman Science--
maybe that's

1677
01:18:57,850 --> 01:18:59,040
why he makes good videos.

1678
01:18:59,040 --> 01:19:01,300
But it only tells so
much of the picture.

1679
01:19:01,300 --> 01:19:05,160
So what is going to be
our definition of good?

1680
01:19:05,160 --> 01:19:08,390
And this is a question that
I still am struggling with

1681
01:19:08,390 --> 01:19:11,300
and I am totally
open to us discussing

1682
01:19:11,300 --> 01:19:13,230
as the class progresses.

1683
01:19:13,230 --> 01:19:16,360
But I do think that
there are going

1684
01:19:16,360 --> 01:19:19,380
to be certain qualities that we
should strive for, regardless

1685
01:19:19,380 --> 01:19:22,690
of if your taste is in
really rapid delivery

1686
01:19:22,690 --> 01:19:29,640
or if it's in very sort of
philosophical, grandiose type

1687
01:19:29,640 --> 01:19:32,180
videos.

1688
01:19:32,180 --> 01:19:34,280
This is a quote from a
reading that you guys

1689
01:19:34,280 --> 01:19:37,259
are going to annotate on
tonight for your homework,

1690
01:19:37,259 --> 01:19:39,050
from Hank Green, who's
the host of SciShow.

1691
01:19:39,050 --> 01:19:42,030
But he says, "People who are
new to the medium are starting

1692
01:19:42,030 --> 01:19:44,980
to think that online video is
not 'Just a little bit better

1693
01:19:44,980 --> 01:19:48,050
than everything else on YouTube'
but 'Just a little bit worse

1694
01:19:48,050 --> 01:19:50,140
than everything
that's on TV.'" And,

1695
01:19:50,140 --> 01:19:53,000
"That perspective is a super
dangerous road to go down on."

1696
01:19:53,000 --> 01:19:56,090
That's sort of hitting upon
what I was saying earlier about

1697
01:19:56,090 --> 01:20:00,140
you can't take necessarily the
best practices in the realms

1698
01:20:00,140 --> 01:20:04,380
that we're trying to combine and
transfer them over and expect

1699
01:20:04,380 --> 01:20:05,920
great results, right?

1700
01:20:05,920 --> 01:20:07,810
You can't try to
make a video like you

1701
01:20:07,810 --> 01:20:10,260
would TV show, necessarily.

1702
01:20:10,260 --> 01:20:11,310
So what is good?

1703
01:20:11,310 --> 01:20:16,140
If good isn't the combined
practices of TV, education,

1704
01:20:16,140 --> 01:20:19,950
YouTube, what is
good going to be?

1705
01:20:19,950 --> 01:20:22,370
So this is a viral
video manifesto that's,

1706
01:20:22,370 --> 01:20:24,117
again, optional reading.

1707
01:20:24,117 --> 01:20:25,200
It's actually pretty good.

1708
01:20:25,200 --> 01:20:28,590
It's from the guys who made
the Diet Coke and Mentos video?

1709
01:20:28,590 --> 01:20:30,600
Have you ever seen
it, where they combine

1710
01:20:30,600 --> 01:20:33,190
Mentos and Diet Coke and
there's this huge, choreographed

1711
01:20:33,190 --> 01:20:34,550
explosion?

1712
01:20:34,550 --> 01:20:35,980
They talk about four points.

1713
01:20:35,980 --> 01:20:39,270
Be true, be authentic.

1714
01:20:39,270 --> 01:20:40,740
Don't waste our time.

1715
01:20:40,740 --> 01:20:42,460
On an online video,
you can't afford

1716
01:20:42,460 --> 01:20:45,260
to do what Connections did
and take two whole minutes

1717
01:20:45,260 --> 01:20:47,910
to set up the premise,
because that's sometimes

1718
01:20:47,910 --> 01:20:49,140
the entirety of a video.

1719
01:20:51,670 --> 01:20:53,890
Be unforgettable,
show us something

1720
01:20:53,890 --> 01:20:55,420
that we've never seen before.

1721
01:20:55,420 --> 01:20:58,360
And that honestly might be
the hardest thing for us

1722
01:20:58,360 --> 01:21:00,380
here, at least it
was the hardest thing

1723
01:21:00,380 --> 01:21:03,290
for a lot of the students that
we worked with on the first two

1724
01:21:03,290 --> 01:21:06,370
seasons of Science Out Loud,
that it's very hard to take

1725
01:21:06,370 --> 01:21:09,220
yourself out of the perspective
of being an MIT student,

1726
01:21:09,220 --> 01:21:12,016
or being a student involved
in science and engineering.

1727
01:21:12,016 --> 01:21:13,890
And remember that some
of the things that you

1728
01:21:13,890 --> 01:21:16,240
take for granted and are
part of your everyday life

1729
01:21:16,240 --> 01:21:20,060
are actually really awesome
and really cool, and things

1730
01:21:20,060 --> 01:21:22,320
that most people
don't see every day.

1731
01:21:22,320 --> 01:21:24,400
You may work at
the nuclear reactor

1732
01:21:24,400 --> 01:21:27,240
here and think that it's
just another everyday thing,

1733
01:21:27,240 --> 01:21:29,960
but that's a window
that you can create

1734
01:21:29,960 --> 01:21:35,750
for people who would have
never, ever had access to it.

1735
01:21:35,750 --> 01:21:38,019
And then ultimately,
it's about humanity,

1736
01:21:38,019 --> 01:21:39,310
about the emotional connection.

1737
01:21:39,310 --> 01:21:42,840
A lot of that comes
from the authenticity,

1738
01:21:42,840 --> 01:21:49,500
that if we can swap you out
with just the computer voice

1739
01:21:49,500 --> 01:21:51,890
and there's not that much
of a difference, then

1740
01:21:51,890 --> 01:21:54,350
really rethink how you're
structuring and writing

1741
01:21:54,350 --> 01:21:55,710
and producing your video.

1742
01:21:58,530 --> 01:22:01,930
So there are going to be
four course values that'll

1743
01:22:01,930 --> 01:22:05,390
guide all of the assignments
and all the things that we do.

1744
01:22:05,390 --> 01:22:10,980
And the rubric is listed in the
syllabus that's on the website.

1745
01:22:10,980 --> 01:22:13,760
We don't really
assign point values

1746
01:22:13,760 --> 01:22:17,290
to did you do correct
lighting, did you do this,

1747
01:22:17,290 --> 01:22:20,187
did you set up your
camera the right way,

1748
01:22:20,187 --> 01:22:22,020
because we don't want
you guys to get bogged

1749
01:22:22,020 --> 01:22:23,430
down in the minutia of it.

1750
01:22:23,430 --> 01:22:27,550
Instead, there are going to be
these four overarching values

1751
01:22:27,550 --> 01:22:31,471
that'll dictate what
is good, I guess,

1752
01:22:31,471 --> 01:22:32,720
as we move along in the class.

1753
01:22:32,720 --> 01:22:36,060
The first one is Spark.

1754
01:22:36,060 --> 01:22:38,060
There's this quote, and
I think it's by Fellini,

1755
01:22:38,060 --> 01:22:40,610
but something along
the lines of it's

1756
01:22:40,610 --> 01:22:42,360
not what's inside the
camera that matters,

1757
01:22:42,360 --> 01:22:45,020
so much as what's in
front of and behind it.

1758
01:22:45,020 --> 01:22:47,610
So are you promoting curiosity?

1759
01:22:47,610 --> 01:22:50,820
Is there a perceived love
of learning in your product?

1760
01:22:56,060 --> 01:22:59,100
Right, is there a perceived love
of learning in your product?

1761
01:22:59,100 --> 01:23:02,870
Is your passion and joy
evident in your delivery?

1762
01:23:02,870 --> 01:23:06,516
This can be seen in your
script, in your final video.

1763
01:23:06,516 --> 01:23:08,640
This doesn't mean that you
need to go over the top.

1764
01:23:08,640 --> 01:23:11,120
It doesn't mean that you
have to pretend to be someone

1765
01:23:11,120 --> 01:23:14,150
that you're naturally not or you
don't feel comfortable being.

1766
01:23:14,150 --> 01:23:16,260
But I'm sure all
of us in this room

1767
01:23:16,260 --> 01:23:18,010
have something that
they're excited about,

1768
01:23:18,010 --> 01:23:22,790
so can we perceive that
excitement in your product?

1769
01:23:22,790 --> 01:23:23,290
Clarity.

1770
01:23:23,290 --> 01:23:26,270
So "Kill all of your darlings"
is one of my favorite sayings

1771
01:23:26,270 --> 01:23:29,770
and something that dictates
a lot of the work that I do.

1772
01:23:29,770 --> 01:23:34,950
But this will be learning how to
navigate the material you have

1773
01:23:34,950 --> 01:23:37,440
and getting rid of stuff, maybe
getting rid of explanations

1774
01:23:37,440 --> 01:23:39,920
that don't need to be there.

1775
01:23:39,920 --> 01:23:41,940
Editing is going to
be a lot about this,

1776
01:23:41,940 --> 01:23:45,390
and the last lecture is
a lot about this quote.

1777
01:23:45,390 --> 01:23:49,340
But it's also about can
you convey your message

1778
01:23:49,340 --> 01:23:50,640
in the most clear manner?

1779
01:23:50,640 --> 01:23:52,890
Is your script tightly written?

1780
01:23:52,890 --> 01:23:55,570
Is your delivery engaging?

1781
01:23:55,570 --> 01:23:58,710
Have you realized your vision
as effectively as possible?

1782
01:24:02,750 --> 01:24:04,500
Then we have
thoughtfulness, which

1783
01:24:04,500 --> 01:24:06,330
is that every decision matters.

1784
01:24:06,330 --> 01:24:08,250
Whether it's deciding
what background you're

1785
01:24:08,250 --> 01:24:11,520
going to stand in front of to
deliver one of your scenes,

1786
01:24:11,520 --> 01:24:15,600
or deciding what facts to
include in your final script,

1787
01:24:15,600 --> 01:24:16,980
every single decision matters.

1788
01:24:16,980 --> 01:24:18,830
And it's thoughtfulness
about what

1789
01:24:18,830 --> 01:24:20,710
you decide to put in
front of the camera,

1790
01:24:20,710 --> 01:24:24,630
but also how you decide
to talk to your audience.

1791
01:24:24,630 --> 01:24:26,760
And again, it's outlined
more in the rubric.

1792
01:24:31,710 --> 01:24:34,340
And then go big or go home.

1793
01:24:34,340 --> 01:24:37,630
This is a hard one for
people, understandably.

1794
01:24:37,630 --> 01:24:39,380
This is probably the
hardest one for me.

1795
01:24:39,380 --> 01:24:42,170
But learning how to step
outside your comfort zone

1796
01:24:42,170 --> 01:24:43,840
and getting creative.

1797
01:24:43,840 --> 01:24:46,910
We do you want to
reward creative risks,

1798
01:24:46,910 --> 01:24:52,460
so don't feel like you
can't try something new.

1799
01:24:52,460 --> 01:24:55,910
Again, hopefully it's
an educated risk.

1800
01:24:55,910 --> 01:24:57,990
But these are all
qualities that we're

1801
01:24:57,990 --> 01:25:00,510
going to assess, not only
through your final products

1802
01:25:00,510 --> 01:25:02,590
but through your
daily reflections,

1803
01:25:02,590 --> 01:25:05,620
through a lot of the
iterative processes that

1804
01:25:05,620 --> 01:25:09,589
will be happening on the
way to your final products.

1805
01:25:09,589 --> 01:25:11,630
And this is where we're
going to integrate things

1806
01:25:11,630 --> 01:25:16,060
like are things clearly lit,
but in the context of was

1807
01:25:16,060 --> 01:25:17,180
this a clear message.

1808
01:25:17,180 --> 01:25:18,596
Does that makes
sense to everyone?

1809
01:25:22,000 --> 01:25:26,550
So if you want to make a
video, where do you start?

1810
01:25:26,550 --> 01:25:29,140
The first thing is deciding
if you should make a video.

1811
01:25:29,140 --> 01:25:31,231
And I think this
list of questions

1812
01:25:31,231 --> 01:25:32,980
is one that everyone
should ask themselves

1813
01:25:32,980 --> 01:25:34,120
before they make a video.

1814
01:25:34,120 --> 01:25:36,400
Why am I making a video
in the first place,

1815
01:25:36,400 --> 01:25:41,310
versus a BuzzFeed article
or versus a radio piece?

1816
01:25:41,310 --> 01:25:42,980
Who is going to
watch this video?

1817
01:25:42,980 --> 01:25:44,600
This will make a
very big difference

1818
01:25:44,600 --> 01:25:47,120
in how you decide to
write your script,

1819
01:25:47,120 --> 01:25:49,310
how you decide to deliver.

1820
01:25:49,310 --> 01:25:51,740
For the most part,
our assignments

1821
01:25:51,740 --> 01:25:55,600
will be assuming sort of a
middle school type science

1822
01:25:55,600 --> 01:25:57,910
background.

1823
01:25:57,910 --> 01:25:59,970
What visuals will I show?

1824
01:25:59,970 --> 01:26:01,860
Again, this makes a
really big difference.

1825
01:26:01,860 --> 01:26:06,460
As Paul was saying, the Khan
Academy video didn't really

1826
01:26:06,460 --> 01:26:09,640
have the visuals that motivated
the lesson that he was wanting

1827
01:26:09,640 --> 01:26:12,320
to learn, so thinking about what
visuals you're going to show

1828
01:26:12,320 --> 01:26:14,230
are super important.

1829
01:26:14,230 --> 01:26:17,010
What is the fact or
piece of information

1830
01:26:17,010 --> 01:26:19,260
that the audience is really
going to remember the most

1831
01:26:19,260 --> 01:26:20,750
or surprise them?

1832
01:26:20,750 --> 01:26:23,740
In the Smarter Every Day
video about the cat flipping,

1833
01:26:23,740 --> 01:26:26,480
it's just that whole
concept of a cat

1834
01:26:26,480 --> 01:26:29,600
can seemingly defy
the laws of gravity,

1835
01:26:29,600 --> 01:26:35,570
but it's really just a
modification of their torque

1836
01:26:35,570 --> 01:26:37,760
or something that
actually makes them

1837
01:26:37,760 --> 01:26:39,590
able to flip the way to do.

1838
01:26:39,590 --> 01:26:43,020
And the biggest one is what
is the point of this video?

1839
01:26:43,020 --> 01:26:45,410
Now, the guys who wrote
the viral video manifesto,

1840
01:26:45,410 --> 01:26:48,040
they used to be circus
performers, so in their book

1841
01:26:48,040 --> 01:26:52,220
they talk about how there's a
slideshow circus pitch, which

1842
01:26:52,220 --> 01:26:54,610
is when you have the
ringleader around the side

1843
01:26:54,610 --> 01:26:56,900
and he's like step right
up, step right up, come

1844
01:26:56,900 --> 01:27:03,200
see the world's smallest person
next to the world's giant man

1845
01:27:03,200 --> 01:27:04,450
or something like that, right?

1846
01:27:04,450 --> 01:27:06,490
There should be some
sort of circus sideshow

1847
01:27:06,490 --> 01:27:08,350
pitch to your video idea.

1848
01:27:08,350 --> 01:27:11,070
So one of the
episodes we made was

1849
01:27:11,070 --> 01:27:13,910
on farts, which
maybe our motivation

1850
01:27:13,910 --> 01:27:16,610
was just that we wanted to
make a video about farts.

1851
01:27:16,610 --> 01:27:20,320
But on the other hand, there's
this amazing biochemical

1852
01:27:20,320 --> 01:27:22,630
process that's associated
with all of that,

1853
01:27:22,630 --> 01:27:26,300
and it really reflects just
this incredible diversity

1854
01:27:26,300 --> 01:27:30,450
of microbiomes that
exist in your body.

1855
01:27:30,450 --> 01:27:33,359
And so it's not just step
right up, step right up,

1856
01:27:33,359 --> 01:27:34,650
come watch a video about farts.

1857
01:27:34,650 --> 01:27:36,030
It's like step right
up, step right up--

1858
01:27:36,030 --> 01:27:37,071
what's the thing I wrote?

1859
01:27:41,130 --> 01:27:43,850
Witness your body's countless
armies of lowly bacteria

1860
01:27:43,850 --> 01:27:45,660
squeeze every drop of
energy from your gut

1861
01:27:45,660 --> 01:27:48,480
and create horrendous
sounds and smells.

1862
01:27:48,480 --> 01:27:52,150
So there should be some
sort of circus sideshow

1863
01:27:52,150 --> 01:27:54,740
pitch to your
video, and Chris is

1864
01:27:54,740 --> 01:27:59,620
going to help us realize
that in the actual way of how

1865
01:27:59,620 --> 01:28:02,570
do I actually make that
video, how do I actually

1866
01:28:02,570 --> 01:28:04,370
create that vision.

1867
01:28:04,370 --> 01:28:07,180
So that's what we're going to
do for the last part of class.

1868
01:28:07,180 --> 01:28:10,600
But be thinking about maybe
what your circus sideshow

1869
01:28:10,600 --> 01:28:11,690
pitch is going to be.

1870
01:28:11,690 --> 01:28:14,580
And eventually
tonight everyone is

1871
01:28:14,580 --> 01:28:17,900
going to need to create
a very short, maybe

1872
01:28:17,900 --> 01:28:20,070
two-minute video, one
to two-minute video,

1873
01:28:20,070 --> 01:28:22,540
a science, technology,
engineering,

1874
01:28:22,540 --> 01:28:26,190
math topic that
you're basically going

1875
01:28:26,190 --> 01:28:27,560
to pitch through this video.

1876
01:28:27,560 --> 01:28:31,145
It's going to be sort of a
trailer for your final project.

1877
01:28:31,145 --> 01:28:35,070
All right, Chris, I
will let you take over.