►
From YouTube: Education & Workforce WG: Data Skills & Data Studies: A New Interdisciplinary Minor in Data Science
Description
Date: 03/05/21
Presenter: Ben Marwick
Institution: University of Washington
Title: "Data Skills and Data Studies: A New Interdisciplinary Minor in Data Science for Arts, Humanities and Social Sciences"
http://sbdh-prod.ideas.gatech.edu/resources/newsblog/education-and-workforce-working-group
A
Thank
you
so
much
for
the
chance
to
to
join
you
all.
My
name
is
ben
malik,
I'm
a
professor
in
the
anthropology
department
here
at
the
university
of
washington
in
seattle
and
just
recently
beginning
in
september
of
this
last
year,
which
is
the
beginning
of
our
academic
year.
Here,
the
director
of
a
new
interdisciplinary
minor
in
data
science,
and
although
it's
open
to
all
students
on
campus
we're
our
task
is
to
make
it
especially
available
and
welcoming
to
students
in
the
arts,
humanities
and
social
sciences.
A
So
I
just
want
to
take
a
couple
of
minutes
to
talk
about.
How
did
we
come
to
get
this
minor
together
and
what?
How
is
it
working?
What's
the
structure
of
and
what
are
the
challenges
we're
facing?
And
maybe
I
get
some
suggestions
from
you
on
how
we
can
manage
some
of
these
challenges.
I'm
sure
some
of
you
are
encountering
similar
things
in
undergraduate
education,
so
to
understand
how
we
could
put
this
thing
together.
A
It's
I
I'd
like
to
just
mention
the
e
science
institute
here
at
uw,
because
this
is
a
sort
of
hub
of
people.
Mostly
it's
all
people,
it's
the
main
asset.
Doing
data
science
across
campus
and
it
because
we
had
this
community
already
in
place
for
10
years
already
at
the
point
where
beginning
to
plan
the
data
science
minor,
it
was
easy
to
find
relevant
faculty
and
and
staff
with
expertise
who
already
sort
of
knew
each
other
and
had
an
understanding
of
data
science
to
bring
them
together
to
start
planning.
A
So
you
may
know
something
about
the
science
institute
already
or
have
a
similar
organization.
So
it's
it's
to
empower.
Researchers,
bring
them
together
and
and
the
most
valuable
thing,
especially
for
me
personally,
and
I
think
for
most
others-
is
creating
a
community
and
a
space
for
people
to
have
activities
and
do
work
together
and
get
to
know
other
like-minded
people.
And
so
it
has
these
three
roles:
education,
research
and
community.
A
Really,
I
think
community
is
kind
of
a
part
of
all
that
I'm
going
to
focus
mostly
on
the
education
role,
because
that's
from
which
the
the
minor
comes
out
of
so
our
goal
here
is
to
disseminate
data
science,
expertise
and
then
lead
educate
data
science,
education
across
campus.
So
some
units
are
very
strong
already
on
data
science
and
have
an
option.
So
you
may
know
you
know
an
option
with
a
major
minor
and
option
is
kind
of
the
smallest
undergraduate
credential
and
some
departments
have
had
those
for
some
time.
A
Thanks
to
the
work
of
the
science
institute,
particularly
my
colleague,
david
beck,
who
is
here
with
us,
also
and
he's
going
to
speak
in
another
talk
in
this
series
on
the
options,
the
graduate
undergraduate
options
so
they're
a
thing
that's
been
around
for
a
while,
but
we
and
so
here's
a
summary
of
what
these
science
institutes
put
together.
Both
in
terms
of
informal
educational
opportunities.
You
can
see,
there's
a
pretty
good
menu
of
hack
week
opportunities,
and
then
we
have
these
other
projects.
A
Sort
of
you
know
couple
of
days
or
week-long
workshops
that
are
very
data-intensive
or
programming
intensive,
the
software
carpentry
and
the
community
data
science
and
collective.
They
are
working
on
things
like
analyzing,
large
amounts
of
wikipedia
data
and
this
kind
of
thing,
and
then
we
have
options
that
that
david
beck
is
our
specialist
on
they're,
the
sort
of
oldest
educational
program
and
the
master's
degree,
and
then
there's
a
certificate
and
our
newest
thing
that
I'm
talking
about
now
is
our
minor.
So
just
for
quickly
reviews
of
how
do
we
get
here?
A
What
is
it
doing
and
what?
How
are
we
sort
of
going
to
go
with
it
in
the
near
future?
All
right,
so
it
began
it's
sort
of
a
top
top-down
thing.
Our
provost
declared
that
that
he
wanted
a
a
science
credential
available
to
non-stem
students.
That
was
the
sort
of
simple
version,
the
brief
and
he
assembled
a
task
force
people
all
across
the
campus,
notably
so
there's
the
usual
suspects
in
here
and
then
you've
got.
A
You
know,
anthropology,
that's
me
and
faculty
from
english
design
and
arts
and
a
few
other
places,
political
science,
so
strong
representation
from
social
sciences
and
humanities.
We
also
had,
of
course,
some
students
in
their
phd
and
undergraduate
student
representatives
that
were
vital
for
giving
a
kind
of
reality
check
on
how.
How
is
this
going
to
look
to
students,
because
the
because
the
e
science
institute
is
so
well
established
at
uw?
A
It
was
relatively
easy
for
us
to
consult
with
other
faculty,
because
we
have
these
data
science
fellows
all
across
campus,
and
then
we
could
ask
them
like.
We
could
ask
them
for
input
on
the
program
and
how
does
the
demands
we
would
put
on
the
students
reflect
what
their
programs
can
offer
and
so
on?
We
were
put
the
provost
put
us
to
work
in
march
2019
and
the
first
students
registered
in
the
program
in
just
the
last
september,
so
I
think
pretty
good,
pretty
good
timeline
for
putting
the
whole
thing
together.
A
Of
course
we
had.
There
are
other
programs
that
we
looked
at
around
the
country
that
were
also
useful
for
inspiration.
So
this
was
the
scoping
you
can
see.
Non-Stem
mages
was
a
was
a
key
sort
of
target
audience
for
for
the
provost.
He
wanted
a
chance
for
them
to
get
some
exposure
to
data
science
to
make
them
competitive
in
going
into
employment
and
also
to
give
them
more
options
going
into
graduate
training.
A
So
we're
looking
at
providing
something
for
students,
high
school,
math
and
science
background
no
prior
coding
experience,
and
so
that
gave
us
the
idea
of
providing
several
possible
like
on-ramps
into
data
science,
one
or
two
underworld
classes.
They
have
no
prerequisites,
they're,
really
accessible,
gentle
introductions
to
data
science,
programming
and
other
sort
of
disciplines,
sub-disciplines
there
so
non-stem
majors,
who
don't
want
to
pursue
a
full
sort
of
degree
or
someone
in
the
topic.
A
A
So,
on
the
right
hand,
side
we
have
data
skills.
These
are
the
kind
of
conventional
things
I
think
most
people
will
easily
recognize
this
as
kind
of
core
data
science
skills,
knowledge
activities
and
just
I've
just
highlighted
a
couple
of
textbooks
that
might
be
used
in
classes
that
teach
data
skills
and
our
list
of
skill
of
classes
in
the
minor
has
36
classes
currently
on
data
skills
and
they're
teaching,
visualization
programming,
either
programming
purely
or
programming
in
a
certain
domain
like
python
for
oceanography
or
right.
A
A
It's
more
of
a
traditional
humanities
or
social
science
class
reading
seminar,
discussion,
kind
of
interpretation,
but
it's
really
focused
it's
on
data
intensive
work
and
that
doesn't
necessarily
mean
always
big
data,
just
a
focus
on
an
intensive
focus
on
the
data
itself
in
a
discipline-
and
this
has
been
a
real
challenge
in
the
minor-
is
identifying
like
what
is
it?
What
is
data
studies
and
what
is
just
regular
political
science
or
regular
psychology?
So
we
we.
This
is
such
an
involving
question
of
how
do
many
faculties
submit
their
courses
to
go
into
this?
A
A
We
have
a
third
sort
of
set
of
classes,
what
we
call
cross
cutting,
and
so
these
are
meant
to
be
kind
of
the
book
ending
of
a
student's
experience.
So
the
on-ramp
is
the
student
at
the
beginning,
no
prerequisite,
maybe
they're
coming
to
programming
for
the
first
time
and
the
synthesis
is
we're
expecting
a
student
to
be
like
right
at
the
end
of
their
program,
looking
for
maybe
a
project
style
experience
in
a
400
level,
class
or
or
something
that
is
like
in
the
domain,
a
class
that
maybe
does
like.
A
Let's
say
my
field
of
anthropology,
there's
a
little
bit
of
data
studies
in
there
a
bit
of
ethics
and
implications,
and
they
might
do
then
do
a
project
that
revolt
involves
some
collection
and
visualization
of
data
sort
of
all
the
things
coming
together.
So
we
have
this
beginning
and
ending
sort
of
book
book,
ending
experience
for
the
students
in
the
program,
and
so
they
need
to
take
one
one,
data
studies
and
one
data
skills
class
and
then
up
to
25
credits
of
either
of
these
and
from
the
cross-cutting
list.
A
So
it's
a
this
is
sort
of
a
typical
load
of
the
miner,
and
many
students
will
take
it
as
the
students
can
take
up
to
two
or
three
miners.
Even
so
it's
you
can
see
the
proportion
of
the
overall
degree
there
so
supporting
it.
Currently
provost,
I
probably
have
been
pretty
generous.
We
have
funding
for
hiring
some
faculty,
we've
hired
a
geography
professor
already
we're
now
in
the
middle
of
hiring
a
humanities
professor
and
next
year
we
will
hire
environmental
and
occupational
health.
A
So
this
is
like
a
competitive
process
where
departments
sort
of
tender
to
the
provost
and
say
we'd
like
to
hire
for
the
data
science
minor,
and
then
we
decide
who
has
the
most
compelling
need.
We
have
an
advising
staff
who's
been,
is
vital
and
excellent.
They're,
not
a
data
scientist
themselves.
They've
done
a
really
wonderful
job
of
like
catching
up
and
getting
up
to
speed
and
becoming
familiar
and
they're
really
central.
I
think
to
the
success
of
our
program.
A
We've
got
the
faculty
director,
that's
me,
and
the
executive
committee
david
beck
who's
right
here
is
on
the
executive
committee
and
a
professor
from
english,
and
then
we
have
a
much
bigger
curriculum
committee,
which
is
one
faculty
member
from
each
department.
That's
contributing
a
course
into
the
minor
and
they
help
make
decisions
about
what
courses
go
in.
When
do
we
take
a
course
out
and
sort
of
structural
questions
like
how
many
credits
can
you
take
from
one
department
into
the
minor
to
maintain
the
interdisciplinarity?
A
The
provost
has
also
given
us
funding
for
instructors
and
tas
to
expand
current
offerings
where
we've
identified
bottlenecks.
You
know
in
some
of
the
statistics,
classes
that
are
prerequisites
into
the
upper
level.
Computer
science,
engineering
classes
we've
been
able
to
expand
those
a
little
bit
and
we're
also
giving
out
in
a
competitive
way
course
release
funding.
A
So
faculty
can
develop
entirely
new
classes
to
be
part
of
the
minor
or
kind
of
re-redesign
existing
classes
to
make
them
more
relevant
to
the
to
either
data
studies
or
data
skills,
and
that's
been
a
a
really
wonderful
process.
A
lot
of
faculty
are
really
interested
in
doing
this,
and
we've
seen
some
amazing
classes
being
proposed
that
just
look
very
topical,
very
fascinating
and
and
really
appealing
to
students
going.
I
just
skipped
my
last
substantial
slide
here.
We
go
so
challenges
the
last
major
topic.
A
I
want
to
talk
about
and
fitting
for
a
data
science
activity
making.
This
visualization
took
me
easily.
Eighty
percent
of
preparing
this
whole
slideshow
because
of
the
nature
of
our
sort
of
campus
kind
of
student
database
situation.
So
these
are
all
of
the
miners
that
we
offer
at
the
university
of
washington
and
so
what
you're?
Looking
at
at
this
tall
bar
here
most
of
the
miners
have
a
very
small
number
of
students
so
that
you
know
60
or
70
miners
just
have
five
students
in
them.
You
know,
like
I,
don't
know
finnish.
A
You
know
or
sort
of
unusual
languages
that
I
was
spoken
by
a
relatively
small
number
of
people
compared
with
spanish,
for
example,
as
a
large
one,
just
to
show
you
where
we
are
with
the
data
science
minor
now.
So
we
are
the
newest
miner
on
campus
just
been
around
for
less
than
a
year,
and
already
you
can
see
in
terms
of
student
numbers,
we're
just
over
100
students
we're
in
what
I
call
the
mega
miners
at
the
university
of
washington.
So
this
is
kind
of
the
most
minors
over
here.
A
We
are
out
here
in
the
long
tail
of
big
miners
that
have
a
lot
of
students
in
them.
Informatics
clearly
way
out
here
with
about
500,
but
we
are
we're
proving
that
we've
addressed
a
need.
There's
a
demand
out
there
for
this
kind
of
credential
at
this
level.
That
is
not
a
computer
science
degree
and
not
a
major,
but
it's
just
allows
students
to
have
them,
have
a
major
in
their
domain
and
then
pick
up
some.
A
So
this
is
a
challenge
to
kind
of
bring
more
courses
on
on
the
catalog
for
students
to
get
into
and
maybe
increase
the
capacity
of
these
very
popular
courses
that
just
fill
immediately
with
majors
and
then
people
outside
of
the
major
you
know
like
a
student
who's
majoring
in
english
is
not
going
to
have
a
higher
chance
to
get
into
one
of
these
very
popular
computer
science
engineering
classes.
As
they
currently
are,
organized
coordination
is
proving
challenging.
Our
curriculum
committee
is
one
solution
to
that.
A
It's
a
place
where
we
bring
people
from
all
departments
together
to
talk
about
some
issues
and
try
to
come
to
common
definitions
of
what
is
a
data
skills
class
and
what
is
data
studies,
for
example,
if
a
class
is
all
about
doing
things
in
excel,
some
faculty
will
not
accept
that
as
a
data
skills
thing,
they
will
say:
no,
it
really
needs
to
be
a
scripted
thing
and
other
people
will
say
well
in
this
field.
Everything
is
done
in
excel,
there's
no
other
tool
for
working
with
data,
so
we
have
to
prepare
students
with
it.
A
So
this
these
kind
of
challenges
are
we're
dealing
with
them
gradually
through
our
larger
curriculum
committee,
they
just
meet
sponsor
quarter.
The
sense
of
a
common
experience
is
a
big
challenge
for
an
interdisciplinary
minor
where,
because
we're
not
housed
in
a
department
we're
in
the
e
science
institute,
which
is
not
really
a
department.
A
It's
just
this
sort
of
community
hub
we're
working
on
that
with
a
integrative
seminar,
sort
of
capstone
seminar,
which
will
be
have
a
chance
for
students
to
you,
know,
discuss
in
small
groups
and
share
their
relevant
experiences
through
the
lens
of
a
presentation
from
a
research
or
industry
worker,
and
then
also
we
have.
We
just
applied
for
the
nsf,
harnessing
the
data
revolution
data
science
core
program
to
to
see
if
we
can
get
some
funding
for
internships
for
undergraduates,
which
would
be
another
way.
A
That
will
be
a
sort
of
cohort
program
that
students
will
bond
through
their
internship
thing
and
obviously
the
internships
and
connecting
with
employers
can
go
together.
So,
and
even
I
mean
we
don't
know
the
chance
of
that
nsf
program.
But
many
of
the
the
ngos
and
local
government
agencies
that
we
contacted
to
bring
on
board
for
that
project
would
be
keen
to
take
on
interns
without
the
nsf
funding.
So
we
feel
like
we're.
A
Making
some
good
steps
towards
that
there
so
they're
the
details,
they're
the
challenges-
this
is
just
our
attractive
website
for
the
program.
That's
that's
growing!
More
and
more
every
day
we
we're
able
to
to
increase
the
course
list.
Every
quarter,
pretty
much
new
courses
can
come
online,
which
is
helping
us
with
some
of
them
the
bottlenecks.
A
The
main
keyword
I
would
just
finish
on
is
this
idea
of
a
translator
like
this
is
a
sort
of
motivating
concept
for
thinking
about
students
coming
out
of
the
minors
to
be
in
between
a
team
that
are
dedicated,
programmers
or
statisticians
or
whatever,
and
then
another
group
of
people
that
might
be
marketing
or
policy
people
they're,
the
ones
who
understand
the
vocabulary
and
can
kind
of
communicate
and
and
so
on,
and
join
the
join
those
other
groups
together
to
be
super
effective.
So
that's!
B
Yeah,
thank
you
so
much
ben.
I
think
there
was
a.
It
was
a
quite
a
few
questions
in
the
chat
and
we'll
transfer
those
to
the
ether
pad
as
well.
If
we
can't
get
to
all
of
them
in
the
thing,
but
you
know
this
idea
of
data
studies
I
think,
is
very
unique
and
kind
of
understanding
what
that
means.
But
we
had
a
quick
question
about:
did
your
computer
science
department
from
cynthia
object
to
having
the
minor
outside
of
its
domain.
A
No,
I
think
they
were
probably
the
most
understanding
of
the
need
for
it
to
be
outside
of
the
domain.
Actually,
I
think
if
anyone
was
not
entirely
happy,
might
have
been
in
the
high
school
informatics,
a
lot
of
departments
thought
it
would
be
good
for
them.
They
would
give
them
a
chance.
We
have
a
budgeting
system
at
the
uw.
That's
basically
like
more
students
equals
more
money.
A
You
know
the
computer
science
engineering
is
a
bit
of
a
foreign
land
to
them,
and
so
we,
I
think
most
people
were
in
agreement
that
it
needed
to
be
outside
of
a
department
in
a
place,
that's
considered
neutral
and
the
east
science
institute.
That's
one
of
its
sort
of
strong
claims
and
valuable
elements
is
that
it's
kind
of
a
neutral
ground.
It's
not
really
geographically
away
from
anything
and
it's
sort
of
a
place
where
most
people
from
most
disciplines
can
feel
welcome
and
comfortable.
So
no,
they
were
quite.
A
I
think
they
were
pretty
fine
with
it
and
they
also
have
been
they've
been
quite
good
at
kind
of
not
insisting
that
every
computer
science
class
be
part
of
the
minor.
So,
for
example,
there's
a
an
intro.
There
are
two
intro
streams,
one
is
python
and
one
is
java
and
david,
and
I
and
our
other
committee
were
just
saying
how
the
java
one
we're
not
going
to
include
in
the
miner
it
just
doesn't.
Have
it's
just
not
applied
enough?
A
Is
not
data
centric
enough,
but
the
python
one
sounds
great
and
the
computer
science
engineering
faculty
that
are
involved
in
planning.
They
also
had
that
that
was
their
sort
of
view
as
well.
It's
like
not
every
computer
science
class
is
a
data
science
class,
so
they've
been
pretty
good
at
not
kind
of
claiming
the
whole
thing
for
themselves.
A
A
There's
some
some
that
are
already
there
so
sociology
and
anthropology
had
a
couple
of
classes
already
that
were
just
perfectly
suited,
and
then
some
of
the
others,
like
in
gender
studies
and
international
studies
that
are
completely
new
or
they've
been
so.
The
faculty
has
designed
an
entirely
new
class
or
they've,
taken
an
existing
class
and
substantially
revised
it
to
make
it
really
sort
of
data
intensive
and
and
we're
really
thrilled
about
how
faculty
are
sort
of
embracing
that
challenge
and
they're.
A
Seeing
that
this
is
a
thing,
that's
that's
important
in
their
field,
and
students
need
to
be
have
a
chance
to
get
training
and
knowledge
in
it.
And
it's
working
quite
well,
but
it
is
yeah.
So
there
are
fewer
of
those
courses
immediately
available
for
us
to
use-
and
this
is
a
focus
of
our
funding-
is
to
encourage
faculty
to
to
develop
or
revise
their
course
to
make
it
fit
into
the
data
studies
thing.
A
Great
unique
strength
of
this
program
is
that
we
it's
kind
of
half
almost
like
thinking
about
ethical,
political,
historical
implications
of
working
with
data,
and
I
feel
like
we're
going
to
produce
some
really
great
graduates
who
are
going
to
be
really
useful
in
a
variety
of
places.
I'm
just
looking
through
the
question,
so
data
studies,
new
courses,
developers
exactly
yeah
new
ones.
We
and
we
just
open
a
call
for
funding
and
see
what
faculty
want
to
come
up
with
we're,
not
very
prescriptive
at
all.
A
But
and
then,
if
the
faculty
wants
to
get
guidance,
we
will
say:
okay.
These
are
sort
of
topics
that
we
feel
could
be
a
good
area
for
a
course
be
around
in
your
discipline,
based
on
just
our
knowledge
and
kind
of
just
to
discuss
what
we,
what
we
would
like
to
see
and
let
them
design
the
course.
I
guess-
and
let's
see
another
question:
are
you
reusing
credits
in
the
mind
to
satisfy
requirements
for
major?
There
is
some
limitation
about
that.
A
B
Yeah,
that's
yeah:
what
are
the
concept
of
data
studies?
This
is
just
because
you
know
this
idea
of
producing
translators,
I
think,
is
unique.
We
have
that
that
concept
comes
up
in
industry
more
than
I
think
it
comes
up
in
academia,
and
so
what
the
the
piece
about
data
studies
did
that
come
from
conversations
with
more
industry
partners,
or
does
that
come
internally
from
your
different
departments?.
A
Yeah,
I
think
it
came
internally
our
so
the
task
force
that
designed
the
miner
was
entirely
faculty
and
a
couple
of
student
representatives,
but
I
think
most
people
they
had
a
pretty
strong
sense
that
you
know
ethics
and
context
needed
to
be
a
major
part
of
the
student's
experience
here
and,
and
then
it
just
was
just
a
matter
of
formalizing.
How
do
we
do
that
and
the
notion
data
studies
kind
of
evolved
out
of
the
task
force?
Conversation?
It's
like
okay,
we
all
can
recognize
data
skills.
A
Well,
what
do
we
call
this
other
thing
and
then
we-
and
then
we
that
was
the
label
that
we
came
up
with.
So
it's
pretty
much
emerge
out
of
the
disciplines
involved.
I
think-
and
even
and
so
we
had
plenty
of
you
know
the
humanities
and
social
science
who
recognize
they
will
do
more,
be
doing
most
that
work,
but
even
the
computer,
science,
engineering
and
the
sort
of
natural
physical
science
faculty.
I
think
agreed
that
that
we
needed
a
solid
kind
of
component.
A
That
was,
you
know,
making
good
decisions
with
the
skills
that
you
have
working
with
data
science,
and
I
think
the
e
science
institute
is
very
well
connected
with
industry
and
and
so
most
faculty
that
have
a
affiliation
with
these
heights
institute
have
a
sense
of
what
our
industry
you
know
what
they're
looking
for
in
in
prospective
employees
yeah
so
yeah.
It's
a
detail
that
I
feel
very
excited
about,
I
think,
is
a
really
an
elegant
solution
to
getting
humanities
and
social
science,
faculty
and
departments
kind
of
involved
and
invested
in
in
data
science.
A
Just
a
couple
other
questions,
cross-cutting
courses.
So
these
are
the
the
either
ones
that
start
that
we
imagine.
A
student
will
start
their
program
on
no
prerequisites,
perhaps
in
a
domain
like
a
mixture
of
a
certain
field
like
sociology
and
r
programming,
for
example,
but
with
no
prerequisites
and
then
at
the
other
end,
the
other
sort
of
set.
So
there's
two
classes
of
on-ramp
of
cross-cutting,
sorry,
on-ramp
and
then
the
synthesis
ones
are
the
end.
A
So
we
imagine
a
student
will
take
them
in
their
senior
year
and
they
will
be
again
in
their
domain
like
in
psychology
or
something
like
that,
usually
ideally
project-based,
with
a
mixture
of
looking
at
implications,
ethical
questions
and
doing
some
applied
work
to
produce
a
project
that
uses
data
skills
as
well.
So
this
kind
of
capstone
style
experience,
I
guess
for
the
cross,
cutting
and
mark's
question
is
the
minor
design
for
non-stem
majors.
A
Let's
say:
historically,
students
in
the
arts,
humanities
and
social
sciences
are
not
drawn
to
these
topics
and
it's
not
obvious
to
them.
What's
how
to
get
involved
like
where's
the
entry
point,
so
we've
tried
to
make
it
particularly
accessible
to
those
students,
so
they
can
see.
This
is
a
thing
that
that
I
can
get
into.
A
This
is
the
thing
I
can
do,
because
we,
our
view,
is
that
students
in
the
natural
physical
sciences,
they've
sort
of
feel
that
this
is
a
normal
thing
for
them
to
do,
and
there
are
many
pathways
for
them
to
catch
some
data
science,
education,
but
for
arts,
humanities
and
social
sciences,
not
not
at
all
obvious
and
so
we're
trying
to
make
it
the
the
the
entry
point.
Several
entry
points
is
as
inviting
as
possible
to
sort
of
meet
them
in
their
field
so,
and
that
seems
to
be
working
quite
well.
A
I
think,
looking
at
the
the
data
so
far,
we
just
have
115
students
and
political
science
and
economics
and
biology,
I
think,
are
our
main
majors
that
are
taking
this
as
a
minor.
So
so
that's
a
that's
a
good
result.
I
think
it's
we're
showing
that
we
accessibility
to
social
science
students
is
working.
B
A
A
A
So
that's
not
something
we
have
yet
patricia.
Have
you
influenced
cs?
So
it's
a
good
question.
I
don't
think
they're
a
large
part
of
our
students,
those
computer
science
students,
I
think,
probably
they
are
they've,
got
their
major
and
then
they
will
minor
in
their
humanities
and
social
science
to
to
do
an
equivalent
kind
of
thing.
So
our
target
student
is
really
someone
who
wants
to
who
know
who
wants
to
major
in
a
certain
domain.
A
Let's
say
public
health,
for
example,
but
then
feels
that
it
would
be
important
for
them
to
catch
a
pick
up
on
some
data
science
skills
to
be
to
do
something
to
fulfill
their
interests
in
the
topic.
They
want
to
do
a
data,
intensive
work
on
global
health
or
on
health
inequities,
or
something
like
that,
and
so
they
will
do
their
major
in
that
public
or
global
health.
And
then
they
will
do
the
minor
in
data
science
to
to
have
a
credential.
A
A
B
A
Classes
do
have
some
some
component
where
the
students
are
exposed
to
ethical
questions
and
issues
so
they're,
aware
of
that
within
their
own
programming,
but
yeah,
I'm
not
sure,
quite
how
it's
perceived
by
the
students
in
that
major
there.
I
definitely
agree
it's
important
to
know
capstone
courses
with
projects
into
the
disciplinary
teams.
We
haven't
formalized
that
yet,
but
some
students
have
been
able
to
organize
that
kind
of
thing
like
like
do
a
a
two-core
two-term
project
that
is
across
two
departments,
for
example
just
on
their
own
volitions
student.
A
B
B
B
Yeah,
so
we
we
will
transfer
these
questions
again
to
the
ether
pad
if
there
are
other
ones
in
there,
ben
or
john.
If
you
could
take
a
look,
if
you
don't
mind,
you
know
answering
them
or
after
the
fact,
if
there
are
further
questions
or
at
least
how
to
get
in
touch,
I
would
actually
love
to
see
like
one
of
the
data
studies,
people
come
and
present
here
to
talk
about.
You
know
how
they're
they're
doing
and
setting
up
those
types
of
courses
and
because
there's
a
lot
of
interest.
B
You
know
around
the
country
about
this
idea
of
how
to
teach
not
only
to
stem
non-stem
students
but
to
connect
data
to
more
of
the
real
life
projects
and
doing
that
capstone
area.
So
if
there
are
questions,
there's
also
some
people,
I
might
get
you
in
touch
with
john
as
well,
that
are
doing
middle
school
education.
B
To
make
those
connections
so
just
quickly,
if
you
have,
if
you
want
to
get
in
touch
or
or
stay
connected
with
the
speakers,
you
can
put
your
contact
information
or
if
you
are
willing
to
put
your
contact
information
in
the
ether
pad
people
may
reach
out
just
in
how
you're
doing
and
looking
at
the
programs
and
if
there's
any
other
programs,
we
leave
the
ether
pads
up
for
the
rest
of
today.
So
people
could
add
things
for
through
the
end
of
the
day,
and
then
we
do
keep
them.
B
So
there's
a
couple
of
questions
these
are
recorded
and
we
do
set
up
a
playlist,
that's
on
our
youtube
channel,
so
we're
going
to
be
getting
more
of
these
up
from
across
the
years.
So
it's
the
south
big
data
hub
at
youtube.
So
we
have
several
other
working
groups
as
well
as
well
as
some
of
our
workshops
and
events
that
are
up
there
on
the
youtube
channel,
and
so
this
one
will
be
its
own
playlist
for
the
education
working
group.
So
if
you
miss
them,
we
have
the
discussion
here
and
the
ether
pads
here.
B
So
it's
always
better
to
come
in
person,
but
if
you
can
go
back
and
look
at
them
and
and
keep
and
keep
a
sense
of
what's
of
what's
going
on
and
what
people
are
doing
across
the
country.
So
that's
where
I
wanted
to,
and
yet
I
see
josh
you
put
you
put
in
your
twitter.
So
if
people
connect
on
twitter,
you
can
connect
there
too.
We
have
that
same
thing
as
well.
You
know
the
for
the
for
the
hub,
and
so
we
do
want
to
keep
this
together.
B
So
as
you
as
I
was
talking
about
at
the
beginning
for
those
that
weren't
here
as
we
transition
to
the
end
of
the
year,
but
we
have
a
full
year
in
september
for
the
this
version
or
with
the
education
working
group.
If
there
are
particular
subtopics
that
you'd
be
interested
in
working
on
we're,
gonna
be
looking
for
nominations
of
subtopics
starting
closer
to
the
end
of
spring,
I'm
so
just
putting
it
in
seating,
the
idea
and
then
having
people
self-identify.
B
If
they
want
to
join
those
topics
through
the
summer
so
that
next
fall,
we
would
have
some
subgroups
that
would
be
working
on
particular
topics
that
could
be
cross-cutting.
You
know
in
areas
of
k-12
or
undergraduate
education,
or
you
know
different
types
of
resources,
maybe
resource
lists
of
for
these
types
of
programs.
B
So
I'm
going
to
be
saying
it
at
the
end
of
the
working
groups
so
that
you
can
think
about
it
and
then,
when
we
open
up,
you
can
put
in
your
own
subtopics
and
we'll
just
open
it
up
to
the
group
to
see
those
that
want
to
might
they
want
to
join
or
do
that
type
of
work.
We'll
still
keep
this
format
where
we
have
speakers,
but
the
subgroups
would
be
able
to.
You
know,
really
work
on
specific
topics.
B
So
I'd
like
to
thank
the
speakers,
if
you
have
other
things
that
you
want
to,
please
feel
free
to
put
them
in
the
ether
pad.
We
will
be
looking
and
consolidating
those
over
the
course
of
this
year,
which
has
been
really
great,
and
so
we
do
take.
We
do
take
a
look
at
those
and
look
for
best
practices.