foreign
[Music]
welcome back I hope you all had an
excellent lunch
um before we get underway there's a
small piece of housekeeping a hotel Key
has been found and handed in at Rego so
if you are missing your hotel key uh reg
desk
um but we are now here to um to hear
about raising Heretics on a diet of open
data with Dr Linda McIver Linda is a
passionate educator researcher and
advocate for stem equity and inclusion
with a PhD in computer science education
her mission is to ensure all Australian
students have the opportunity to learn
stem and data science skills in the
context of projects that Empower them to
solve problems and make a positive
difference in the world
today Linda will talk about the
integration of data science into
education and the potential social
outcomes of using real world data when
teaching
[Applause]
thanks Fiona
um I would like to apologize for
delivering the talk standing sitting
down I'd like to be standing up
um unfortunately standing up for 45
minutes is not a function currently
offered by this API
um similarly I'm not going to be at much
of the conference
um much as I'd like to catch up with you
all and feel free to find me on any of
the
social things and and connect I really
like that
so I'd like to begin by acknowledging
the first scientists the first
environmentalists and the traditional
owners of these unseated lungs that will
run through people
um the warranty Warrior wrong people and
terrible at pronouncing that I apologize
of the cooling Nation we have much to
learn from them
so
GPT has the education world's Collective
underwear in a lot this is largely
because it threatens the validity of our
assessment it gives students the
possibility of dodging their assignment
work their
um writing their research and sometimes
even dodging setting their own exams
many State education departments in
Australia have banned it from schools
entirely and let's have a moment's
Collective silence for governments that
are naive enough to believe they can ban
something on the Internet
the truth says though that it only
threatens the validity of our assessment
because our assessments are already
wildly invalid we know that the way we
are assessing people doesn't work and
doesn't actually assess the
characteristics and skills and abilities
that we say we care about
our tasks for students are all too often
chosen for
ease of processing ease of marketing
ease of authentication it's very easy to
know if a student is sitting in front of
you writing on an exam paper that you
can be fairly confident that they're
writing that they're doing their own
work although even that's getting a
little dodgy these days
but there's very little evidence that
exams are actually a worthwhile form of
assessment in fact we know that they're
not they're not a good way of assessing
student learning and let's face it when
you choose a doctor you don't ask them
how well they did on their exams you
want to know how good they are at
communicating you want to have someone
who's an excellent diagnostician who's
fabulous at
collaborating with
uh professionals and and various Allied
Health Professions and also other
doctors you want to know that uh that
your doctor is good at choosing a
specialist who will actually treat you
like a human being and not like a speck
under a microscope
um you don't care about the Intel
but none of these things are effectively
assessed by exams and they're also not
replicable by things like chat cpg
if our assessment of students learning
and skills is based on assessments that
ask them to regurgitate facts and known
processes we're not actually assessing
anything of value there's just no
validity there at all so I'm hoping that
chat GPT will be the kick that we need
to push us into more authentic forms of
assessment into more engaging useful and
valid ways of Education
it's past time to transition into a
problem-based authentic form of
Education where students actually do
things that build their critical
thinking their problem solving and
indeed their ethical decision making
why am I telling you this in a
conference on open data
well when I started computer science
when I started teaching computer science
in a secondary school I arrived to find
a course that was
um very toy based we had year 10
students we were teaching them to teach
robots to push each other out of circles
to follow lines to draw pretty pictures
and scratch-based interfaces
and it failed it failed dismally the
students hated it and this was in a
science goal where you would think that
the kids were you know naturally
predisposed to enjoy technology and to
engage with it but they couldn't see the
point they couldn't see the relevance to
anything that they would want to do in
their future lives they were bored they
were disengaged and they were wholly
unwilling
now when we switched using data science
instead we were teaching the same coding
skills they were learning about
variables and functions and iteration
and basic code but now we were doing it
in the context of real data sets and
that that the word that second last word
there is key real data sets as soon as
you use data that is real and meaningful
it completely changes the nature of your
educational
so we were also teaching a large side of
data literacy but for me you know I'm a
computer scientist I want everyone to
learn to code for me this started out as
a quest to engage more kids with code
um
and sorry I was mildly distracted there
by the site of a helicopter going down
below the floor level it's gone now
um you don't see that very often
um so uh yeah we were using those data
sets to answer meaningful questions and
the level of Engagement completely
changed suddenly instead of coming to me
saying why are you making me do this I
don't want to do this I hate this and
you know half of them to be honest
cheating to just get the assignment out
of the way and move on with it now they
were coming to me saying oh my God this
is so useful I used it in my science
project and to be honest those science
projects are half the reason I started
teaching data because every year there
were graphs in their science projects
made me cry
but now they're also coming to me saying
oh I used it in my maths exam and oh my
god there was a graph on the news last
night and there was no zero on the scale
and it was so outrageous it was social
so suddenly just because they're working
with real data and learning some data
literacy they were becoming critical
thinkers and that thread just grew and
grew and grew to the point where I
didn't care about the learning coding
anymore the critical thinking of the
problem solving was actually the
significant part
um so we talk a lot about boosting the
pipeline when we talk about getting more
women and non-binary folks into uh Tech
in general and data science in
particular the problem is we tend to
focus our efforts on
um late high school when the kids are
starting to as we normally call it
choose their careers although I'm sure
there are plenty of people in this room
who would who provide evidence that you
can change your career at any point
um myself included
um but we we focus on Lake High School
or university and the problem with that
is that we know that kids attitudes to
stem and maths in particular solidify in
mid to early to mid Primary School we've
lost them before they ever hit High
School
so kids interest in stem is really
caught or lost in those early years but
the trouble is they're often being
taught by teachers who've never learned
stem themselves who've never been taught
to teach stem and who are quite friendly
often terrified of it
coincidentally perhaps kids own
self-efficacy or their perception of
their self-efficacy
um solidifies around that time too so
you get kids coming out of primary
school saying I am no good at maths I am
no good at Tech I couldn't do anything
with those robots
and they're being taught by teachers who
are terrified of it there may be a
connection
um
so we need to stop aiming our
recruitment drives at high school when
we've already lost them because yes okay
it makes sense to aim at high school
when they're choosing their subjects and
things and they are choosing their path
at that point but the truth is I've
already pruned a lot of those paths
they're already saying I'm not doing
maths because I suck at maths and both
my kids by the way don't tell them I
told you this test is gifted in maths
but believe they suck at it because they
because they frequently misinterpret the
questions
um and they're badly worded questions
but that's a rant for another time if
you want to jump in at any point please
feel free there'll be plenty of time for
questions at the end but if you want to
jump in at some point just make yourself
known
um
yeah so
we need to teach these kids much earlier
that stem skills are meaningful that
they're useful and really importantly we
need to teach them that they're
accessible
that they can all do them
um this this kind of only a certain type
of person can code thing the the coding
DNA kind of myth is really pervasive
um not just in society but also in Texas
I'm sure you know
um but it's not anyone can learn to code
anyone can learn data science anyone can
learn stem skills now I'm not saying
that I'm going to turn all these kids
into Data scientists but they all need
to have enough data literacy to engage
with the meaningful conversations we all
need to have about where we're going as
a society because data science is
increasingly driving that in some
interesting directions
so we know that one way to engage kids
with stem is to use data science solving
real problems so clearly we need to
bring data science into schools from the
very beginning well I have good news and
for you I have great news
the good news is we're already building
that data science into education it's
why I started the Australian data
Science Education Institute and it is
starting to spread we're getting now
developing resources and sharing lesson
plans and doing teacher training and
getting out there into the world
um
but the great news is that open data
gives us the power to use School data
science projects to solve serious data
problems
we all know there's more data out there
than any
um than the field of data science can
analyze even if we collectively forego
sleep and food forever uh hands up if
you've heard of the Japanese term
sundoku
the stack of books that you have beside
your bed that you haven't got around to
reading yet now put your hands up if you
have your own personal data tsundoku
right we just can't get to it that's too
much
um so how about we throw kids some of
that data how about we get them
answering real questions and doing
meaningful stuff it's more than possible
I do it every day
so the challenge is
to do things like what if we taught
probability using gender pay data sets
instead of black and white and black and
white balls in and
Charlie is a non-binary software
engineer given that they've been working
in the field for three years what is the
probability that they are receiving the
same pay as James Asus hit weight man
doing the same job
but of course we need open pay data in
order to answer that question and the
pay gap for gender pay Gap data that has
been released is not sufficient that's a
conversation for another time
the amazing thing about using real data
sets for classroom projects is that the
possibility exists for kids to find new
things so they can be looking at a data
set that no one's ever looked at or
asking that data set a question that no
one's ever asked that's not something I
get to do at school they normally get to
solve problems that have been solved
before and where they take it up to the
teacher and the teacher goes yes or no
yes it's right no it's wrong do some
more work that's the extent of it but
now they're doing real science with data
sets that haven't been fully analyzed so
they have the chance to ask questions no
one's asked before
the first style science project I ran
with my year 10s used a data search on
the Australian electoral commission and
we downloaded a CSV file which was over
three million lines every line in that
CSV file was a vote for the Senate in
Victoria for the federal election
and three million lines won't even open
in Excel so gosh tell it they had to
learn to code so sorry
um mind you the code they had to write
might have been 10 or 20 lines in the
end they were very simple
bits of analysis that most of them did
but being a real data set with endless
scope those who are ready for it could
do and did
insanely complicated and fabulous things
so they weren't learning a lot of code
where they were learning a manageable a
manageable amount that enable them to do
something real
imagine if everybody's first experience
with code was a small bit a small
program that did something meaningful
and enabled them to find something out
that they cared about
that would be a bit differential tree
Hello World
um
so the assignment was to find a question
the data set could answer now there were
just endless scope for that and
visualize the results now the
visualizations were mostly done by hand
um
partly because python visualization
libraries
setting kids new code is free on python
visualization libraries and tiers I mean
those libraries make me cry
but also because they could do much more
creative and compelling things if they
visualize it by hand
um so then you have to think about
whether the graph is still valid the
visualization is valid you know making
sure things are to scale and stuff but
they learn a lot more making the
visualizations more interesting
um to to their General audience
every student had to find a different
question now that's a problem really if
you think about it for for the way we
normally do education that's 180
different questions of this data set
none of which the teacher already knows
the answer to we'll talk about that in a
minute but some of the questions they
asked were how did the people at my
local polling week about compared to the
people in the electorate as a whole or
in Victoria as a whole uh what was the
proportion of women as candidates and
how much of the vote did they get
compared to the men and that was a
particularly interesting one because we
got to examine the thorny question of
gendering people by their first name and
whatever you could find out with Google
and it you know was a fabulous
introduction to the complexity and
ugliness of real data the messiness
um they asked which parties did people
vote for who voted above the line or
which parties did people mostly vote for
who voted below the line which parties
were more likely to receive the second
preference of people who voted one
before or any given party
um where are Paul enhances One Nation
voters Metro Urban or rural which
party's voters were more likely to
follow yeah that was not a big surprise
which party's voters were more likely to
follow they had vote cards uh won't
surprise you to know that Green's voters
were the most rebellious in that respect
um in short they got to take a large
data set and ask the questions that um
most interested them and that does that
had only just been released it was just
after the 2016 federal election so a lot
of these questions hadn't been asked at
all and and indeed would never asked by
anybody else because they were quite
specific
um and the focus was very much on the
data literacy aspects what questions can
they start the set answer because of
course the first thing they all want to
know is
um which is the best party and sadly I
don't think that Bible said answered
that question yes
this is absolutely fascinating research
in and of itself did you publish their
work anywhere
sadly there the question was did I
publish the work anywhere because it's
amazing research and it is amazing
research
um sadly there are real complexities
around publishing things with real kids
and blah blah blah no yes I'd love to
the former academic in me really wants
to research this but at the same time as
teaching it and spreading it and yeah
there's a rather I ran out of means
um
yeah so the focus was on how do we
communicate the answers to those
questions accurately and compellingly
like how do we get people to care about
this stuff that you found out
and I picked this data set because I had
a student who was really interested in
politics so I went and rummaged on the
aec website to see what I could find
it's like this one's great it was
particularly good because he had
explained the rules of Senate voting to
kids you know like you can vote above
the line or below the line but not both
and
um you know you can only use the number
one once and things like that and so
they go great so if I look at this this
string which contains the votes there'll
only be one number one I'm like
well the thing you have to also deal
with is that people don't necessarily
follow the rules and boom their little
heads explode It's a Wonderful learning
experience
um
but uh the thing is that even the kids
who weren't interested in politics were
super interested
in the fact that this was real
and they could easily see the connection
to things that they did care about and
how they could use their skills that
they were learning for something that
mattered to them more
um
this turns out to be Central to
motivation kids who can't see the point
in learning something don't
it's as simple as that and making it fun
is very dependent on your definition of
fun
there is no single thing that every
student will find fun but also robots
um they are preaching to the converted
to the kids who love robots will love
robots the kids who don't a lot
I'm pretty straightforward but if you're
using real data they can see the
relevance and they can apply it to other
things even if that particular data set
doesn't do it for them
and the cool thing is when we use real
data sets there are a lot of questions
to ask before you even begin to analyze
them questions like how was the data
collected what are the problems or
limitations of the way the data was
collected well this is sample size what
biases are embodied in this data what
were the limitations of any sensors used
has the data been processed at all and
if so what what information was lost in
the processing what does each of the
fields mean how do the fields relate to
each other so you've got to understand
the domain of the data which is not the
way we typically teach maths we
typically teach maths with here are some
numbers here is a process applied the
process to the numbers and tell us the
result not well it depends on the type
of seagrass that you're measuring that's
not a part of math
um and this is my favorite and this has
particularly come out of my one of my
podcasts which I'll talk about a bit in
a minute but um what definitions
underpin this data because the devil is
absolutely in the definitions um I
mentioned the gender pay Gap Data before
um one of the issues with that data for
there are many I I love that it's
released right but it's not the Panacea
that some people have said it is because
part-timers are not included in that
data
now who is typically part-time
correct
so you know the assumptions that have
been made in the definitions and the you
know who's in and who's out can be very
significant in the results that you get
and that is
that's a bit mind-bending for people
who've been taught that things are black
and white and you know very
straightforward and you get the same
results every time
so already you're starting a data
literacy conversation that builds
critical thinking and problem solving
skills and we haven't even opened the
file yet
I love that that you know that they
really have to start thinking about
things before they even get down to work
we have a tendency as human beings to
kind of Bend at the knees when we see a
graph or some statistics but teaching
data science but teaching data science
using real data sets builds a culture of
rational skepticism that makes it normal
to ask what was the sample size how did
you collect that data where did it come
from how reliable is it what biases
might there be and we all need to be
asking Those Questions by default and we
tend not to
my kids and my students cursed me
because they can't look at things like
that without without asking those
questions anymore you know it's like
once your eyes are opened you can't
close them again which I love but it's
also kind of distressing
um of course yeah there are challenges
if you have 180 kids asking different
questions of a data set you have 1280
answers which aren't in the back of the
textbook that to me is an upside not a
downside because now instead of taking
it to the teacher and asking us if it's
correct or looking it up in the back of
the textbook or hitting the submit
button and finding out whether you've
got the right answer now what you have
to do
you have to check your own work
you have to critically evaluate your own
work you have to figure out why you
think it's valid challenge it test it to
see if it is valid figure out what other
explanations there might be for the
results that you got all of those
wonderful things that we don't normally
do in schools and in fact we don't
normally do them in real life either
um so not only are they learning to be
rationally skeptical about data but
they're also learning to be rationally
skeptical about their own work and to
assume that there will be flaws in their
own work because when you're using real
data sets and solving real problems
there is no such thing as a perfect
solution
so now you have to evaluate Your
solution and and I I think that's
magnificent and it wasn't something I
thought about when I started doing data
like I said when I started teaching data
science I just wanted them to make
better graphs and learn to code
that it turns out it's not the important
stuff
so when we give kids real things to do
and the power to create change they see
the purpose of tech and data science
skills and they're eager to learn black
and white balls in an urn or teaching
robots to push each other out of circles
just doesn't cut it doesn't have nearly
the same impact
and the more open data we have the more
data sets that kids can play with
themselves and figure stuff out with the
greater the potential for projects that
Empower kids to make change in their own
communities
so imagine kids exploring pedestrian
data in their local Town Center
um or tracking covert cases in their
Community if that data were available
which it no longer is
um imagine them evaluating the impact of
nearby development on threatening
species or looking at the impact of
dredging in Port Phillip Bay on Dolphin
numbers and behavior imagine them
analyzing traffic around their school
and devising safer traffic management
processes for drop off and pickup time
or using Google Mobility data to analyze
covert lockdowns and figure out
which country really have the longest
and strictest lockdowns in the world
or um or using public health and Road
accident data to try and figure out
which is really the most dangerous to
the population in the long-term cycling
or inactivity
imagine well imagine exploring real
current data and anything the kids care
about
it's as simple as that
and as someone who's currently Mobility
impaired I'm fascinated and enraged by
how much further all the accessible
stuff is you have to walk further for
the lift you have to walk further to
press the button to make the automatic
door open
um the ambulance toilets and and the
lows are always way down the other end
like it just every step some days is
incredibly painful and I have to take
way more of them to use the stuff that's
going to make my life easier so imagine
if we had kids doing a project just
around their school or around their
local Shopping Center or park to figure
out how much further people in
wheelchairs have to go to access the
same things that the rest of us take for
granted
or um what about a project where kids
measure track or try to fix anything
that is gets in the way of people who
are vision impaired
uneven footpaths low hanging signs which
by the way are also a problem for the
clumsy I told people among us hi
um or measure and track accessibility on
websites what about a project to track
the use of alt tags on lasted on and
compare it with Twitter
um
really when you start thinking this way
there's just no end to the kinds of
projects that kids can do and the topics
that they can take on and the cool thing
is kids want to do something real they
want to make a difference
um
when they ask why do I learn this they
don't actually want the answer because
it's on the exam they they want to know
how it's meaningful unless it's
fundamentally meaningful it's just built
in
um so every project when the kids come
up with Solutions because there's no
textbook answer and they can't look it
up at the back of the book called
compare it with the teachers answer
sheet they have to evaluate their own
solutions they have to ask how does that
help
how does it harm
does it actually make things better how
could we improve it imagine if that was
a certain approach to programs in
government a bit radical
none of these are easy questions none of
them have easy answers but that's
fantastic preparation for the real world
where easy questions and obvious answers
are conspicuous by their absence or
deeply suspicious when they're presented
to you
um and the Australian data Science
Education Institute is building these
kinds of projects and using open data or
getting kids to collect their own data
about problems in the local area for
kids as young as five years old
you can do stuff the kids they're
graphing by stacking blocks it's it's
great fun
um we're building their critical
thinking rational skepticism and stem
skills from the very start of their
education and we're teaching them that
they have the power to change the world
and that stem skills
enhance that power
a friend of mine recently hired a newly
graduated data scientist and he came to
her deeply distressed at one point
saying
my data set like I don't understand
what's going wrong the curve is really
wonky and my friends looked at it
fortunately she's an experienced
statistician she was like yeah that's
that's how real data comes out this guy
had a masters in data science and had
never seen a curve that didn't come out
perfectly I mean that's an outrageous
indictment on that master's program and
I don't know which university it is but
could probably be any of them
um no wonder is Paul Brayton exploded on
contact with real data like that's just
we should
you should never be using textbook data
sets because they don't exist in the
real world it's it's just outrageous so
you have to bear in mind of course that
not every school project will produce
tangible great outcomes or usable
outcomes sometimes a school project you
know disappears at the end of the
semester and that's all there is to it
which is fine
the fascinating thing is that just
knowing that they're working on
something real
um and meaningful give gives kids a
mind-blowing level of motivation and
engagement and it makes it easier for
them to imagine how the skills that
they're learning could be used elsewhere
even though they're learning the same
essential skills
at least where coding is concerned
um they just
they can transfer them much more easily
and also you know they're using python
not Mindstorm so the the transference is
easier because there's a lot of stuff
happening in Python
open data combined with this kind of
data Science Education gives students
the power to change the world and ask
all those really difficult questions
that's why I called it raising Heretics
and I have a book by the same name it's
we're really teaching kids to ask
difficult questions which a lot of
people don't like I was I was in a
teacher conference and I talked about
how you know we we should be challenging
the validity with the assessments and
one of the teachers was like oh you
better not tell the kids that they might
start challenging the validity
assessments I'm like yes
so another one's ready for it
um but as open data enthusiasts I charge
you with a few things that will help us
turn your data into school projects
number one please annotate your data for
non-experts if you have a CSV file with
Fields labeled things like
f6642g it may be open but it's not
really accessible so please provide a
data dictionary if you can that that
explains every field in a clear and
non-specialist language together with as
much information as you can about how
the data was collected and
um
and any processing that's been done to
it
use uh non-proprietary formats if you
possibly can CSV is ideal we can't make
any assumptions about available software
Hardware or even internet in schools
sometimes we are reduced to sneaker net
which brings me to if your data set is
massive if you can provide meaningful
subsets that's super helpful so for
example I wrote the Google Mobility data
down for Australia into states which is
a you know simple super simple python
script for me but it's out of the reach
of a lot of teachers and a lot of
students so it just makes it a little
easier for them to dive in without
having to do all the prep work and the
thing about the prep work is I had time
to do it when I was teaching because I
was half time also I already had the
skills most teachers full-time teachers
don't have that time they don't have
time to find the data make sense of it
build a project that's one of the
reasons I created Etsy to try to Short
Circuit that for them so they can just
grab the data that's pre-annotated grab
lesson plans and things like that
uh number four be open and explicit
um about the issues and limitations of
her data that's super helpful and also
this is going up on my blog as soon as
I've done here so um you don't have to
write it down if you wouldn't look for
it it'll be up on the ADC website which
I will give you the link to in a minute
it's up there in fact
um yeah talk about patches where there's
data missing or where census filed over
the Internet uh went down or biases in
the sample anything like that is super
helpful to know and please please please
do not clean your data
I want kids to be working with the messy
stuff to understand that people don't
always follow the rules when they're
voting for the same act don't you know
all that stuff
um real messy complicated data sets are
the best possible preparation for the
real messy complicated real world
um we need to really stop teaching kids
that questions have simple answers
this is my thing
instead we want to equip them to handle
real life
so uh number six provide contact
information if you can if you're
uncomfortable with doing that or your
data set is so exciting that you feel
you're going to be inundated please feel
free to use me as an intermediary
um contact me first
um but I'm happy for you to put my
contact details this is part of what I
do right it's part of what ANSI does put
we'll put up answer as a contact and um
then you at least will only have to
answer the questions that I can't answer
and only answer them once so that's
always an option when I was working with
the aec data I spent hours on the phone
to the aec trying to find someone who
could confirm for me the mapping of the
one-dimensional string to the
two-dimensional ballot paper and I could
not find anyone there who knew
presumably there is somebody
but I couldn't find them and it took me
hours and teachers don't have that kind
of time
um
yeah
a key part of etsy's mission thank you
is to relieve teachers of the burden of
finding those interesting data sets and
figuring them out as well as helping
teach them how to do this stuff long
term the goal is to put Etsy out of
business because it'll be the way
teachers teach and if we the way
teachers are trained to teach and it'll
be the way the curriculant has written
it's going to take a minute or two so in
the meantime adsey is a charity because
funding must never be a barrier to
access the road to social equality is
educational equality
which means that we do charge for those
who can't afford to pay don't and it
also means that we're always structure
cash so uh
please feel free
to sling us some money if you can
there we go
um
the more authentic and meaningful data
that we have access to the more kids we
can Empower to change the world using
data science so please put them up on
all the data repositories you can find
send them straight to me or send me a
link to let me know that they're there
it's super helpful and gives kids access
to much more interesting projects
um
I do have a book where you can read more
of this stuff it's free as a podcast
um which is really just an audio book
but with lower sound quality
um and it's also you can buy it all over
the place
um
I also have a podcast called make me dot
electric if you do funky stuff with data
singer and I'll have you on because it's
it's really fun
um and it's a it's just interesting
chats with people who do cool stuff with
data and there's a few new living
audience here I'm like oh I have a catch
you one there you go
um
um one more thing
talk to me
questions
Fiona's gonna come around with a
microphone so we can all hear
on your website do you have a
some links to data that you've
previously used that you would like or I
think we can get a kick start with yes
uh the website is severely in need of
updating like all good websites but yes
there are there's projects and existing
data sets on there there will be more
I'm actually
since I try to myself
this sounds really exciting for kids I
was wondering if you have any advice for
the adults who got left behind who want
to learn this stuff
um
there's a whole bunch of ways to learn
data science online
um but but again I would say find
yourself a problem
that that is Meaningful to you and try
to figure that out and build your skills
that way
um because you're more likely to stick
to it first out because it's interesting
to you
um I'm working with a company called
grock Academy who build
um a whole bunch of uh online coding
courses and stuff they are building some
data science courses as well which I am
involved with and so there's some useful
sort of data literacy and data science
skills coming online they're not there
yet but they will be
they're free now
um because they've got a whole bunch of
funding so
um
it's not a bad place to start but really
find something you're interested in and
sort of dig into it that way also there
is a Facebook group called teachers
using data science which you can jump
into even if you're not a teacher and
ask questions in there and teachers love
to tell people stuff
interesting
are there any more questions for Linda
um one other thing I hear from teachers
all the time is but how do I fit this
into the curriculum
and the curriculum is
the slow movie
um thing and
do you have any interesting stories or
anecdotes about things you've been able
to get teachers to do to
make it
the simplest thing is that all the
projects are curriculum linked so
actually any one of those real projects
you can hit curriculum points from like
50 different subjects
and so I did a bunch of projects for the
education department in Victoria a few
years ago and we literally had five or
six different rubrics for you know
English and maths and Science and
geography and because they you know
since you're using a real data set
you're covering a lot of different
points so it's not hard to build it into
the curriculum that they need to teach
anyway
the the real challenge is persuading
teachers that they have the skills they
need to do this which is why most of
what I do is in spreadsheets when I'm
training teachers because if I walk into
a room of teachers and so I'm going to
teach you all the code in Python
there'll be a whisking noise
um it's there's there are teachers out
there doing amazing stuff in Python but
they're very very outnumbered and so if
I'm trying to engage science teachers
and Math teachers and history teachers
and geography teachers actually
geography teachers are all over this
stuff they're amazing
um but I need to show them they've
already got the skills and you can do
really simple stuff in spreadsheets
which is again where the subsets of data
come in handy
because we can do stuff in spreadsheets
and not have to code ultimately everyone
will code but one step at a time
so in addition to the whisking noise the
teachers make when they're scurring out
of the room what other type of
resistance or sort of refusal have you
encountered throughout this entire
Journey that you've been on
uh the biggest thing is if I label my
workshops as data science workshops I
get no signups I'm going to label them
as stem workshops and they sell out
same contact it is the Fear Factor but
also you know I I sometimes worked with
schools where a head of department head
of science has said everyone must work
with lender and there's crickets and
then he says please contact Linda and
set up a time crickets and then one
person does it and the first time I did
that the person who came to me came
looking like she was gonna die like she
was like
you know lamb to the slaughter you know
she's pretty sure what she was walking
into a bloodbath and I sat sat her down
and went through what she was already
doing she's a chem teacher an excellent
cam teacher and I was like so when
you're doing errors we could do this and
she said
I do that and you know just the the
weight fell off her shoulders and she
kind of set up straight again
um it really is the Fear Factor is just
the big thing
um so it's it's getting past that and
that's you know as much as sociology and
marketing exercises it is anything else
um and it kind of helps to have
um a mole in the school you know someone
who's already you know a double agent
spreading the word kind of thing that
works really well
there's a
sort of touring curriculum there's
there's a kind of technology is
something that we use as a tool and it's
everywhere and then there's the
technology curriculum where do you
do you find that
complicates it or do you have a way of
dealing with both of them I think that's
a really weird setup and I always have
but I don't I don't particularly care
about the faculties or the divisions
because this stuff should be in all of
the subjects you can I've seen a really
cool project that analyzes
um different characters appearing in
Harry Potter books I wouldn't do Harry
Potter now but you know you could like
just it's just it's like a kind of
visual display of where the characters
are most likely to appear in the books
and which characters appear on the same
page and things like that like there's
all kinds of stuff you can do there's a
wonderful history project using the
Titanic data set which is a readily
available text file which has the the
name the age the sex the um
class and in some cases the occupation
of the passengers and crew on the
Titanic or whether they lived or died so
you can analyze it and say well did
women and children really go first
um things like that that's history
and it doesn't require a lot of maths
either
okay I think we're at time so would you
all join with me please in thanking
Linda for a very thought-provoking
session
thank you