Computational Thinking for an Inclusive World: A Resource for Educators to Learn and Lead
In this episode I unpack Mills et al.’s (2021) publication titled “Computational thinking for an inclusive world: A resource for educators to learn and lead,” which is a white paper that provides strategies for integrating computational thinking into disciplinary learning and for developing capacity for computational thinking.
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Welcome back to another episode of the
csk8 podcast my name is jared o'leary
each week of this podcast is either an
interview with a guest or multiple
guests or a solo episode where unpack
some scholarship in relation to computer
science education in this week's
particular episode i'm unpacking a paper
titled computational thinking for an
inclusive world colon a resource for
educators to learn and lead this paper
was written by kelly mills marika conrad
patty ruiz quinn burke and josh weisgrow
apologies if i mispronounced any names
as always in the show notes you can find
a link to this particular paper as well
as a link to other resources such as
other podcasts relevant to this episode
and you can find the show notes by
clicking the link in the after listening
to the song or by simply going to
jaredaler.com and clicking on the
podcast tab while you're there you'll
find hundreds if not thousands of free
resources for computer science educators
as well as some content for gaming and
drumming because i stream on twitch and
create content on youtube so stop by
sometime and say hi speaking of stopping
by somewhere i highly recommend going to
bootup pd.org which is the non-profit
that i work for who powers this podcast
if you visit boot.pd.org you'll find a
ton of free computer science education
resources that i have created and you'll
also learn more about our paid
professional development all right so
here's the abstract for this particular
paper quote technology is becoming more
integral across professional fields and
within our daily lives especially since
the onset of the pandemic as such
opportunities to learn computational
thinking are important to all students
not only the ones who will eventually
study computer science or enter the
information technology industry however
large inequalities continue to exist in
access to equipment and learning
opportunities needed to build
computational thinking skills for
students that experience marginalization
we call all educators to integrate
computational thinking into disciplinary
learnings across pre-k 12 education
while centering inclusivity to equip
students with the skills they need to
participate in our increasingly
technological world and promote justice
for students and society at large this
report issues two calls to action for
educators to design inclusive computing
learning opportunities for students one
integrate computational thinking into
disciplinary learning and two build
capacity for computational thinking with
shared leadership and professional
learning inspired by the frameworks
strategies and examples of inclusive
computational thinking integration
readers can take away practical
implications to reach learners in their
new context end quote if i were to
summarize this paper into a single
sentence i'd say that this paper
includes strategies for integrating
computational thinking into disciplinary
learning and for developing capacity for
computational thinking right so this
paper is 66 pages long so i'm going to
go through it as quickly as i can while
just kind of hitting on the salient
points i do encourage you to read it got
a lot of resources and examples that are
worth exploring that i'm not going to
dive into but i do hope you take the
time to actually take a look at it and
again it's a free paper so you can find
a link to it in the show notes all right
so here is a very quick overview of what
they recommend this is from page five
quote to provide all learners especially
those experiencing marginalization
opportunities to engage in computational
thinking it is essential that educators
integrate computational thinking with
the topics they already teach like art
english language arts math science and
social studies end quote and so the
recommendations that they provide are
quote leverage synergies between
disciplinary learning and computational
thinking provide opportunities for
students to build computational thinking
skills in the younger grades and promote
student agency and purpose end quote and
right below that quote integrating
computational thinking into every
classroom is not something that can be
left to individual educators educational
leaders must prioritize the initiative
and build capacity for teachers to do so
end quote so here are three strategies
that can be done in order to do that so
quote promote shared leadership among
districts schools and teachers develop
sustained individualized professional
learning opportunities and integrate
computational thinking into pre-service
teacher education end quote from page
five all right so those are just the
recommendations and the rest of the
paper is gonna kind of unpack why it's
important to do that and how you can do
that so the first main section of this
paper is the introduction and so in this
introduction they're saying hey because
of kova 19 and just because of you know
the general purpose of computational
thinking we think this is an important
skill for students to develop in
particular because we don't want kids to
just consume technology want them to be
able to create it and they explain that
it's especially important for kids who
are experiencing marginalization to
learn computational thinking because
they think it would be very helpful and
in particular it should be integrated
into every single class and that it
really needs support from administrators
to be able to do something like that
here's a quote from page 8 and this
gives a summary of like the rest of the
paper quote it is divided into three
sections first we present a brief
overview of computational thinking what
do we mean by the term and how do we
apply it in practice next we examine the
current state of k-12 computing
education and the persistent challenges
of providing students with access to
computational tools and addressing
systemic inequity and computer education
and the tech world more broadly to
combat these challenges we propose a
framework for computational thinking
integration with inclusive pedagogies at
the center finally we describe two
distinct needs for educators to create
inclusive learning opportunities for
computing one integrating computational
thinking interdisciplinary learning and
two building teachers capacity for
computational thinking we describe
strategies to address each need and
highlight examples of educators using
each strategy in action by the end of
the report we hope that readers will
have identified concrete next steps to
further inclusive computing education in
their context end quote that is an
excellent summary of the remainder of
this paper which is like 50 plus pages
after this so in the next main section
they talk about well exactly what is
computational thinking so the way they
situate computational thinking is within
the broader umbrella of computing and it
merges together and blurs together of
computer science and programming but all
of those fit within the bigger umbrella
of computing and they have a nice venn
diagram that kind of compares and
contrasts from
the past to right now in terms of how
computational thinking was viewed so on
page 10 there's a very important
clarification here quote while computer
science is an individual academic
discipline computational thinking is a
problem-solving approach that integrates
across activities the skills and
practices requiring computational
thinking are broader leveraging concepts
and skills from computer science and
applying them to other concepts such as
core academic disciplines for educators
integrating computational thinking into
their classrooms we believe
computational thinking is best
understood as a series of interrelated
skills and competencies end quotes from
page 10 and they describe it a little
bit further down so this is a very
important thing to consider having been
in cs education for several years now i
believe that we will never actually come
to a unified definition of computational
thinking spoken with many people about
it there's some very interesting
opinions about it in terms of thinking
like a computer or thinking like a
computer scientist etc and everybody
disagrees with everybody else about
whatever their definition is so it's
really important that we understand how
these authors are framing this so
they're saying that computational
thinking in this context in their
framing is a problem-solving approach
and it can be integrated across all
activities and these concepts and skills
are from computer science and they're
applying them into
other contexts to solve some kind of a
problem all right so on pages 11 and 12
they actually kind of talk about well
what are these skills and what are these
practices that make up computational
thinking and by the way the authors use
the terms concepts competencies and
practices and they kind of all
blend together so that's not just me
switching up the different terms and
whatnot so the first set of skills
include abstraction algorithmic thinking
debugging decomposition pattern
recognition and selecting tools and then
the computational thinking practices
include automation computational
modeling and data practices and so they
mentioned previously that these are all
interrelated and on pages 11 and 12 they
include not only like the list of these
skills but also a description for each
one and then an example for each one of
them so if you're curious well what do
they mean by selecting tools or
decomposition check out the descriptions
and the examples in there hopefully it
gives some clarification for you but
these are all interrelated with each
other and kind of work together to make
up what they are describing as
computational thinking now here's an
interesting quote from page 13. quote
although both plugged and unplugged
activities are valuable learning
experiences for students to build
computational thinking skills leveraging
technological tools where appropriate
can support learners to connect and
apply these skills to engage in
computational thinking practices in the
older grades end quote i totally agree
so yeah i think there are some like
really fun things that you can do with
unplugged but it often decontextualizes
things in ways that really don't make
sense in my opinion the way i've
described it before is like okay it's
like you're trying to teach somebody how
to play the drums without actually
giving them some drums to play on or
some sticks to use like yeah you can
learn some drumming concepts but you're
not going to become a good drummer
unless you actually have drums with you
trust me i know i played the drums for
well over 20 years and taught it for
just under 20 years so the same thing
with computational thinking if you want
to learn these skills and these concepts
and be able to apply it especially like
coding and whatnot you need a code yes
you can learn concepts but when you do
it outside of application especially in
ways that are driven by students
interests all right so there's more
information in this section as with all
the other sections i'm going to cover
this is a very quick introduction i'm
encouraging you to actually read it but
i hope this podcast will like highlight
some sections that you might be like oh
i really want to check out the section
titled the current state of computing
education which is the next section
starting on page 15. here's an
interesting quote on that page quote
well all 50 states have some policy in
place promoting computer science the
role of computational thinking within
these initiatives is ambiguous the k-12
computer science framework which many
states use to develop standards
integrates computational thinking into
four of the core practices reasoning
that the most effective context and
approach for developing computational
thinking is learning computer science
they are intrinsically connected
consequently most data points for
participation and achievement in
computing education are directly related
only to computer science such as
enrollment and elective computer science
classes in high school and associated
test scores end quote page 15. that's
really interesting and the reason why i
think that's interesting is because it's
saying that the framework says the best
way to basically learn computational
thinking is to learn it through computer
science and why i find that interesting
is because so many people are trying to
integrate compositional thinking into
subject areas that are not computer
science or putting it into ela or social
studies or math or science or whatever
so
what i don't understand is just me
thinking out loud this is not a
criticism or anything i enjoyed reading
this paper my thought is well if the
best way to learn computational thinking
is in computer science context and we
think that all students should learn how
to do this then shouldn't we focus on
efforts that makes computer science
mandatory as opposed to hey instead of
making computer science mandatory let's
just integrate computational thinking
into a potentially less effective domain
i.e not computer science so like ela or
something but that's just me thinking
out loud and i'll share more thoughts a
little bit later at the end of this
episode because that's what i do later
on the authors do note a little bit
further down that the resources and the
amount of time required to do like its
own standalone cs course are not always
feasible and i totally get that but i'd
also argue if computer science or
computational thinking either of them
are so important for every single
student to learn then we need to make
time for it no excuses but instead many
administrators are forced with these
time crunches of well computer science
is not tested computational thing is not
tested it's not part of the core
curriculum reading right and arithmetic
so let's just embed it in there and then
cool we can have our caking eat it too
but in my own opinion i think that's a
disservice i've seen some schools say oh
yeah we offer and teach computer science
to our all of our students and by that
what they mean is they do like an hour
of code great that's awesome that you
spent an hour throughout the year
working on computer science happy for
that but to say that you have a computer
science program is a bit misleading if
you're only spending that amount of time
so if you are embedding just
computational thinking into other areas
with the hopes of being able to check
off some standards that to me is saying
hey we think this thing is really
important but not as important as all
these other things so if we're going to
engage in discussions or discourse
around computational thinking the way
that this is framed is hey this is an
extremely important set of skills and
practices to learn but not as important
as you know every other subject area
that we're going to integrate into but
those are my two cents now there's a
subsection here starting on page 16
that's talking about how we tend to
measure the success of computer science
through the ap computer science course
and how this is pretty problematic one
this is only offered in high schools as
far as i'm aware none of the kids i
worked with in the elementary schools
took ap classes that i know of but two
there's a certain demographic cluster
that tends to take ap tests over others
and marginalized communities tend to not
take as many ap courses especially if
they
have a lower socioeconomic status and
don't have the intention of going on to
college so if all of our experiences
related to computer science are being
assessed by something that not every
student is going to participate in we're
not really going to have a good
understanding of how successful we are
at broadening participation in computer
science or computational thinking again
because of my background in music
education here's an example from music
it's like saying well how many kids are
enrolled in the orchestra and using that
to figure out how diverse the music
program is when there's also a band
acquire a percussion ensemble music
production studio etc so yeah you could
look at ap test scores but that's going
to give you a very narrow slice of the
pie because ideally your school is
offering more than just aap computer
science and ideally you're also offering
it below
high school so like middle school and
elementary all right so the next section
page 17 so this is on reimagining
computational thinking to be more
inclusive so this section i recommend
spending some time diving into some of
the resources that are listed here if
you haven't listened to many episodes
you'll find that there are a ton of
episodes discussing equity and inclusion
and access and all sorts of things that
are important for educators and
especially computer science educators to
consider so you can actually dive into
some of these a little bit deeper by
checking out some of the previous
podcast episodes but there are three
categories that the authors recommend
for classroom educators and these
strategies include designing accessible
instruction the second one is connecting
to students interests homes and
communities and the third one is
acknowledging and combating inequity so
here's a quick summary from page 18 of
each of these quote designing accessible
instruction refers to strategies
teachers should use to engage all
learners in computing connecting to
students as interests home and
communities refers to drawing on the
experiences of students to design
learning opportunities that are
connected with their homes communities
and interests to highlight the relevance
of computing in their lives
acknowledging and combating inequity
refers to a teacher supporting students
to recognize and take a stand against
the oppression of marginalized groups in
society broadly and specifically in
computing end quote now again there are
several podcast episodes for each one of
these particular topics for example
under designing accessible instruction
they mention universal design for
learning which i've unpacked some papers
on also talked to jesse rathgeber and
andreas steffek about accessibility and
whatnot so check out those podcast
episodes when it comes to student
interest homes and communities check out
like the podcast with the interview with
mitch resnick and honestly most of the
podcasts because my own approach in the
classroom and with the curriculum i
design for boot up is all about students
interests guiding their learning but
there are some specific episodes that
i'll link to in the show notes and then
acknowledging and combating inequity
many of the podcasts also discussed this
unpacking different frameworks like
k-port centers culturally responsive and
sustaining pedagogies the discussion
with nikki washington and the discussion
with joyce mccall and so many others so
again i'll include links to these in the
show notes which you can find at
jaredoleary.com so the point of these
three different sections in here in this
particular paper is to say hey
when you're doing computational thinking
you need to do it in a way that
acknowledges and combatant inequalities
that also is designed for accessible
instruction and it is also connecting to
different student interests cultures etc
i strongly agree with all of those ideas
but i don't think it should be limited
to just computational thinking alone i
think good computer science practice and
good education in general includes all
those things and i say that as somebody
who is taught in multiple subject areas
so this is not just unique to
computational thinking or computer
science all right so the next section
what districts should focus on integrate
learning and develop capacity so this is
the bulk of the paper so the first main
need that they focus on is integrating
computational thinking into disciplinary
learning here's a quote from page 21
quote integrating computational thinking
can be beneficial for both the expansion
of computing opportunities and
disciplinary understanding from a
computing perspective computational
thinking integration conceives computing
as a tool for understanding other
disciplines and topics and therefore as
an inherently relevant skill from a
disciplinary content perspective
computational thinking can deepen
disciplinary learning some integrations
will place a greater focus on computing
while others will place the greatest
focus on disciplinary concepts ideally
an integration balances computing and
disciplinary learning to promote both
then ct can become a value add to
disciplinary learning and not an add-on
to an already over scheduled school day
end quote from page 21 so to do this
they have three different strategies the
strategies are leveraging synergies
between disciplinary learning and ct
developing computational thinking skills
in the younger grades and promoting
student agency and purpose so for each
of these three
different strategies they provide an
explanation of why is this important
here's some research that suggests it
and then they provide a couple of
examples for each one of them different
contexts explaining well here's how they
did it here are some things to think
about here's how it relates to
computational thinking and
ex subject area so in the first section
that's on leveraging synergies between
disciplinary learning and ct they
provide a very quick overview of like
some pre-k 3-12 and 6-12 standards in
arts ela math science and social studies
they have between like one and three
examples of well here's how you might be
able to use this in the arts here's how
you might be able to use this in math
and then following this they have two
different examples so one is on
integrating computational modeling into
middle school science for bilingual
students so check that out if that
sounds interesting and then the next one
is on exploring health disparities using
data science in high school biology and
those are pages 24-28
so in the second section on developing
computational thinking skills in the
younger grades they say it's important
for younger kids to engage in
computational thinking because i can
help them develop an interest in some
foundational understandings of computing
so the examples in here are on
integrating life relevant computational
thinking into preschool and then
integrating computational thinking into
elementary ela and so those are from
pages 29 to 32 and then the further
third strategy on promoting student
agency and purpose is all about quote
providing student-centered learning
experiences so that students are driving
decisions about what tool to use how to
use it and for what purpose provides
them with opportunities to gain
experience autonomy and confidence in
computing they can take outside of the
classroom in quote now one of the things
that i really
really appreciated that they mention is
there's a continuum of how you can
actually implement or integrate
computational thinking i've mentioned in
other episodes about integration of
computer science as a whole how there
are many ways you can do it that could
be subservient or multidisciplinary or
interdisciplinary or transdisciplinary
etc so include links to those episodes
in the podcast as well as some episodes
that kind of dives deeper into what do
we mean by curriculum but for here they
talk about how computational thinking
could be a simple enhancement through a
full-on transformation of how you
actually engage with a subject area or
domain this reminded me very much of
sammer which sammer is an acronym for
substitution augmentation modification
and redefinition so the enhancement
would be the substitution or
augmentation we are going to use
computational thinking to substitute or
augment a subject and then the
transformation side of things is
modification or redefinitions we're
going to have a completely new way of
experiencing this subject area or this
particular concept in a domain because
of computational thinking i would argue
from my own perspectives having read a
lot of scholarship on computational
thinking and seeing a lot of lesson
plans that talk about and integrate
computational thinking the vast majority
of computational thinking is done
through substitution or augmentation and
does not actually get into modification
or redefinition i.e it does not really
transform the learning experience unless
it uses an approach that was actually
outlined in computational literacies
which i did an unpacking scholarship on
a particular paper by kfi and proctor so
i highly recommend checking that one out
if you're interested in computational
thinking computational literacies in my
opinion is like the next best thing for
a variety of reasons that i kind of talk
about within that episode one of the
interesting things that i do notice when
people talk about how computational
thinking can be transformative is it's
usually done using a computing device to
design create or analyze so like being
able to analyze large sets of data or
create some kind of a computational
model to simulate something or
demonstrate something but thinking out
loud whenever i see stuff like that it
makes me go well then is it the thinking
that's important or is it actually using
a device that's more important but
because it makes me think of that it
just again brings me back to samura and
makes me go okay well sammer is a
framework for thinking through
integrating technology in meaningful
ways so you're not just like swapping
out a whiteboard for a tablet and going
look we're using technology but instead
using the tablet and going hey instead
of taking notes on here we can create
mind maps that are hyperlinked to
projects that students create all on the
same device that is a modification or a
redefinition of what you can actually do
because of the device so again going
with this line of thought if we're going
to get into transformational
computational thinking i'd like to see
some more examples of just the thinking
that is transformational and not just
the use of a device that actually makes
it a transformational experience but
those are my own biases in this
particular section on promoting student
agency and purpose they do have some
examples so one of them is on students
identifying social justice community
needs so that i can inform an app design
and then the other one is on promoting
student agency in data practices so if
those sound interesting make sure to
check out pages 34 all the way up to 38.
now on page 39 there is the second need
which is on developing capacity for
computational thinking and so we have
strategy one which is promoting shared
leadership among districts schools and
teachers strategy two is on developing
sustained individualized professional
learning opportunities and then strategy
three is on integrating computational
thinking into pre-service teacher
education so for the first strategy on
promoting shared leadership among
district schools and teachers what they
recommend for cs is to have consistency
to make it so that cs is cumulative and
that is competency based but in order to
do this the authors argue that many
leaders can't do this on their own so
it's really helpful to have support and
i'll include a link in the show notes to
the cs equity guide which is really
helpful for administrators because as
written by administrators who are
interested in implementing computer
science in equitable ways so i highly
recommend checking out one that podcast
episode that unpacks it and then two the
actual equity guide which is now being
rolled out into more states than just
california so check it out now in this
section they talk about how many
different districts implement ct in
different ways some of them use it as a
tool some of them use it as a theme and
some of them use it as competencies just
like how there's no unified definition
of what computational thinking is
there's also no unified way of actually
integrating it or implementing it in
other subject areas so it's really
important when you're sitting down with
your schools to figure out one are we
trying to integrate computer science or
computational thinking or both and then
two
what do those actually look like and
make sure that we have a shared
definition before you actually start
going in and start implementing it
because you might say
hey we're going to integrate
computational thinking into our
classroom and that's going to mean
something very different to a different
person if they have a different
definition of computational thinking and
what it looks like so for example here's
a quote from page 39 quote with tools
districts provide technology and
programs to teachers such as scratch
code.org and project lead the way with
themes they embed these tools into
integration approaches such as maker
learning or stem with competencies
districts focused on student knowledge
and abilities such as algorithms data
and computational modeling
competency-based pathways are an
effective strategy to define
computational thinking while providing
educators flexibility to select
appropriate tools and methods of
instruction for their students end quote
now in this particular section or
strategy they provide two different
examples so one of them is on designing
k-12 computational thinking pathways in
rural alabama and then another one is on
developing school capacity using
computational thinking integration
framework and so these are discussed
from pages 40 all the way up to page 44
and on page 45 is the next strategy on
developing sustained individualized
professional learning opportunities so
in this particular section they
mentioned that quote teachers have
indicated that challenges to integrating
computational thinking into the
practices include limited planning and
instructional time and identifying
connections between computing concepts
and core content end quote from page 45
one reason why they might not be able to
make those connections between computing
concepts and core content is because
they don't have a very solid
understanding of computing content or
like computer science in particular or
computational thinking in particular
another reason why is maybe there aren't
great connections between that subject
area and computational thinking or
computer science as i mentioned before
in other podcast episodes many people
have talked about how computational
thinking can be used to analyze music
and i've looked at that as a
professional musician and music educator
and said i don't know anyone who's done
that from the standpoint of a composer
producer a musician or a music educator
it just doesn't make sense yes you can
find patterns but that's not what we do
when we are creating music there's so
many more nuances and complications than
just figuring out where there are
repeats so i say that to say maybe
computational thinking is not actually a
good fit outside of limited application
in a subject area so just because we can
come up with a couple of simple examples
of these potential connections to
different domains doesn't actually mean
it's robust enough to use everywhere and
at any time but in this section on
teacher support they suggest that we
provide opportunities for ongoing
professional learning we clarify grade
appropriate terminology provide access
to exemplar lesson plans create some
strategies to assess student work and
help develop the recognition of
computational competencies then the
authors provide some examples on
differentiated readiness aligned
professional learning for elementary
educators which is from pages 49 through
last strategy which is on integrating
computational thinking into pre-service
teacher education which is i know a huge
step towards helping preparing future
educators and they include a variety of
different sections of what teacher
educators might be able to do including
like building partnerships between cs
educators and teacher educators
introducing computational thinking
within the educational technology
courses applying it across different
methods courseworks or practicums
creating some resources and tools that
actually define computational thinking
which good luck with that providing
opportunities for pre-service educators
to apply computational thinking in
different disciplinary environments to
problem solve and provide coaching for
how to apply ct practices in the
classroom and then engaging various
stakeholders across higher education and
local school districts so if any of
those sound interesting make sure to
check out pages 51-52 as well as the
examples such as computational thinking
and universal design for learning and
introductory education coursework and
integrating computational thinking into
methods courses and student teaching
experiences and those are starting on
page 53 all the way up to 56 and then on
page 57 is the conclusion and after that
it's just all of the references and
whatnot all right so at the end of these
unpacking scholarship episodes i like to
provide some lingering questions and
thoughts this is not critiquing the
authors or anyone who's interested in
computational thinking i do have some
general questions about computational
thinking and in particular the way that
is discussed so i just share them on
here because i think we should talk
about it more as a field before we
actually continue to promote
computational thinking for example it
would be really helpful if we actually
had a definition of computational
thinking that people agreed upon the
other episodes that i've done that talk
about inclusive pedagogies and equity
center pedagogies have very clear needs
totally agree with that i do however
disagree that there is a clear need for
computational thinking a question that
i've asked previously on this podcast is
when is computational thinking in the
discourse around it a form of
epistemological colonization so
colonizing our ways of learning
or knowing so for example in this
particular paper and again this is not a
critique for the authors there was
phrasing that computational thinking
needed to be prioritized by district
leaders on page 21. on page 28 they
mentioned that it's really important for
young children to learn computational
thinking because this sets up pathways
to get into other areas of computing and
like page 18 and 19 is talking about how
computational thinking gives some skills
that allows people to understand
technology and competing processes and
so i agree that yeah maybe computational
thinking would be useful for
understanding computing but why is it
that that makes it necessary to learn in
literally every subject area which is
what was proposed in this particular
paper and has been proposed in many
other papers that i've looked at if
computational thinking has skills and
practices that are specific to solving
problems what if those problems don't
need computing devices to solve them so
why is it that we view everything from a
technocentric framing yeah it's
pervasive
in society but it's not pervasive in
every single academic domain and even if
it is it's for different reasons than
just to solve problems to dive a little
bit deeper into the questioning the way
that people discuss computational
thinking is that it often comes across
as refining a collection of tools but a
collection of tools is not a heuristic
or process to think through so because
computational thinking isn't really a
process to go through it's often framed
within discrete tasks or activities but
rarely is it actually discussed in
relation to broader learning goals or
purposes of studying a particular
subject area so if we use language from
like wiggins and mktai who talk about
understanding by design and big ideas
these are the questions that are core to
a subject area that not only can
students explore but professionals in
the field are also exploring it and a
lot of the big ideas that i have seen in
different subject areas in my opinion
aren't going to be answered through
computational thinking but
little problems that arise in relation
to those big ideas
might benefit from some forms of
computational thinking but a lot of
these domains honestly have their own
frameworks for thinking through so for
example design thinking is very useful
for engineering and design and it is a
process or at least it is framed as a
process of empathizing defining ideating
prototyping and testing it can be a
linear process but it also has the
opportunity to cycle back through the
process at any given point this is very
different than a collection of skills
and practices that people can't actually
agree what skills and practices count as
computational thinking what skills and
practices do not count as computational
thinking so for me what i'm wondering
out loud is why is computational
thinking more important than a heuristic
like design thinking and why is it so
important that it's being encouraged to
be pushed into every single subject area
why can't it just be a tool or a set of
tools that is used when it is needed
rather than promote it as something
everyone needs to do in every subject so
to combine this questioning of this
collection of tools with a previous
point about epistemological colonization
again this is me reflecting on the
points of this paper this is not a
critique of the authors by any means but
the way that people generally talk about
computational thinking is it's as if
scientists who were really passionate
about the scientific method said that
every subject area should learn and use
the scientific method but the way that
they talk about it is as if they only
spoke about instances where it sort of
applies to a subject area but isn't
actually getting at some of the bigger
ideas or core ideas within that subject
but instead are just finding almost like
a affirmation or confirmation bias
examples
of where it might sort of fit but the
biggest difference that i see between
this hypothetical scenario of scientists
engaging in
epistemological colonization through the
scientific method is actually a process
to think through with some steps that
people agree upon and not just like a
relatively vague set of skills that can
be interpreted many different ways so
one thing that i think might be helpful
for the field is to define when is it
not computational thinking so for
example it's framed as a problem-solving
approach but not all learning is
problem-based nor are there any set of
skills or practices that are universal
to solving any given problem so when
does it make sense to engage in
computational thinking and when does it
not make sense to engage in
computational thinking so while we tend
to highlight instances where
computational thinking fits within a
discrete activity we also need to talk
about when it does not make sense to use
computational thinking i think this
would help educators immensely however i
also think it would be very helpful for
the field to really take a look at kfi
and proctor's discussion of
computational literacies which i think
helps clarify some of the issues that i
see with computational thinking and in
my opinion provides a more useful
heuristic to think through and you might
disagree and that's okay you can come on
the podcast and tell me i'd honestly
love to chat with somebody who
completely disagrees with me on this so
i can learn from you and if you want to
do that you can find the contact me
button on my website by clicking the
link in the app they're listening to
this on or by going to jaredaler.com or
you could honestly even join me on
twitch someday and jump in the chat and
ask me questions about computational
thinking or provide your perspectives i
think it'd be funny to do that playing
elden ring or fortnite while chatting
about computational thinking let's do it
anyways i'm getting too goofy right now
so that is my cue to wrap up this
podcast i do highly recommend reading
this paper i enjoyed going through it
there are a ton of resources and
examples that are very relevant to a
variety of educators so i hope you
consider taking the time to checking out
the actual paper itself and maybe
sharing this podcast or the paper with a
friend or colleague stay tuned next week
for another episode and until then i
hope you're all staying safe and are
having a wonderful week
Article
Mills, K., Coenraad, M., Ruiz, P., Burke, Q., & Weisgrau, J. (2021, December). Computational Thinking for an Inclusive World: A Resource for Educators to Learn and Lead. Digital Promise.
Abstract
“Technology is becoming more integral across professional fields and within our daily lives, especially since the onset of the pandemic. As such, opportunities to learn computational thinking are important to all students—not only the ones who will eventually study computer science or enter the information technology industry. However, large inequalities continue to exist in access to equipment and learning opportunities needed to build computational thinking skills for students that experience marginalization. We call all educators to integrate computational thinking into disciplinary learning across PreK-12 education, while centering inclusivity, to equip students with the skills they need to participate in our increasingly technological world and promote justice for students and society at large. This report issues two calls to action for educators to design inclusive computing learning opportunities for students: (1) integrate computational thinking into disciplinary learning, and (2) build capacity for computational thinking with shared leadership and professional learning. Inspired by the frameworks, strategies, and examples of inclusive computational thinking integration, readers can take away practical implications to reach learners in their contexts.”
My One Sentence Summary
This white paper provides strategies for integrating computational thinking into disciplinary learning and for developing capacity for computational thinking.
Some Of My Lingering Questions/Thoughts
When is computational thinking and the discourse around it a form of epistemological colonization?
Why is there a tendency to center technology over everything else?
Discourse around CT sometimes comes across as reifying a collection of tools, but it’s not a heuristic or process to think through.
I think it would be useful as a field to define when something is not computational thinking
Resources/Links Relevant to This Episode
Other podcast episodes that were mentioned or are relevant to this episode
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Curriculum integration podcasts I mentioned
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In this episode I unpack an excerpt from Schubert’s (1986) book titled “Curriculum: Perspective, paradigm, and possibility,” which describes different examples, intents, and criticisms of “images” or “characterizations” of curriculum.
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In this episode I unpack my (2020) publication titled “Intersections of popular musicianship and computer science practices,” which discusses potential implications of hardware and software practices that blur the boundaries between music making and computer science.
In this episode I unpack Bresler’s (1995) publication titled “The subservient, co-equal, affective, and social integration styles and their implications for the arts,” which “examines the different manifestations of arts integration in the operational, day-to-day curriculum in ordinary schools, focusing on the how, the what, and the toward what” (p. 33).
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In this interview with Jesse Rathgeber, we discuss what educators should know about (dis)ability culture and research, person-first language vs identity-first language, suggestions for combating ableism through anti-ableist practices, how the arts and CS can come together and learn from each other (great for sharing with arts educators who might be interested in CS), and much more.
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In this interview with Mitch Resnick, we discuss misconceptions people have around the four P’s (Projects, Passion, Peers, and Play) in Mitch’s book, encouraging depth of understanding while playing, what has surprised Mitch during his career, encouraging online communication and collaboration without creating artificial engagement, what Mitch wishes we’d see more of and discuss in CS education, our pet peeves with unplugged activities and computational thinking, accounting for survivorship bias with Scratch, expanding our focus on equity and inclusion to include both the “who” and the “how,” the importance of experimenting and learning through play, and much more.
Nicki Washington is Unapologetically Dope
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