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APRIL 2017 | VOL. 60 | NO. 4 | COMMUNICATIONS OF THE ACM 55
ENTHUSIASM HAS GROWN in recent years for computer
science education in many countries, including
Australia, the U.S, and the U.K.14,15 For example, in
2012, the Royal Society in the U.K. said, “Every child
should have the opportunity to learn concepts and
principles from computing, including computer
science and information technology,
from the beginning of primary edu-
cation onward, and by age 14 should
be able to choose to study toward a
recognized qualification in these ar-
eas.”26 And in 2016, the College Board
in the U.S. launched a new computer
science curriculum for high schools
called “Computer Science Principles”6
focusing on exposing students to com-
putational thinking and practices to
help them understand how computing
influences the world. Within the com-
puter science education community,
computational thinking is a familiar
term, but among K–12 teachers, ad-
ministrators, and teacher educators
there is confusion about what it entails.
Computational thinking is often mis-
takenly equated with using computer
technology.11,29 In order to address this
misrepresentation, the scope of this ar-
ticle includes a definition of computa-
Computational
Thinking
for Teacher
Education
DOI:10.1145/2994591
This framework for developing pre-service
teachers’ knowledge does not
necessarily depend on computers
or other educational technology.
BY AMAN YADAV, CHRIS STEPHENSON, AND HAI HONG
key insights
!Few teacher-education programs focus
on training pre-service teachers to
incorporate computational thinking into
K–12 classrooms.
!Redesign of courses on educational
technology and methods is critical
to developing pre-service teacher
competencies in computational thinking.
!Education and computer science faculty
should work collaboratively, using their
complementary expertise in computing
and teacher development.
56 COMMUNICATIONS OF THE ACM | APRIL 2017 | VOL. 60 | NO. 4
contributed articles
IMAGE FROM INTERNATIONAL SOCIETY FOR TECHNOLOGY IN EDUCATION / HTTPS://WWW.ISTE.ORG
with algorithms that guarantee success
if followed correctly.17
Computational thinking has been
suggested as an analytical thinking
skill that draws on concepts from
computer science but is a fundamen-
tal skill used by, and useful for, all
people.28 Some have argued that com-
putational thinking is a practice that
is central to all sciences, not just com-
puter science.13,28 Bundy,4 for example,
noted that computational thinking
concepts have been used in other dis-
ciplines through problem-solving pro-
cesses and the ability to think computa-
tionally is essential to every discipline.
These powerful ideas and processes
have begun to have significant influ-
ence in multiple fields, including biol-
ogy, journalism, finance, and archaeol-
ogy,22 making it important to include
computational thinking as a priority
for K–12 education. Wing28 said, “To
reading, writing, and arithmetic, we
should add computational thinking to
every child’s analytical ability.” In sum-
mary, computational thinking is a set
of problem-solving thought processes
derived from computer science but ap-
plicable in any domain.
Embedding computational thinking
in K–12 teaching and learning requires
teacher educators to prepare teachers
to support students’ understanding
of computational thinking concepts
and their application to the disciplin-
ary knowledge of each subject area.
Specifically, teacher educators need
to provide teachers with the content,
pedagogy, and instructional strategies
needed to incorporate computational
thinking into their curricula and prac-
tice in meaningful ways, enabling their
students to use its core concepts and
dispositions to solve discipline-specific
and interdisciplinary problems. It is
important to acknowledge that the cur-
rent lack of an agreed-upon, exclusive
definition of the elements of computa-
tional thinking makes it a challenge to
develop clear pathways for pre-service
teachers to be educated teachers—
computationally.30 Nevertheless, it is
both important and possible to begin
taking steps in this direction.
Here, we argue that, given the cross-
disciplinary nature of computational
thinking and the need to address
educational reforms—Next Genera-
tion Science Standards and Common
Core—it is beneficial to prepare teach-
ers to incorporate computational
thinking concepts and practices into
K–12 classrooms. While most current
efforts to embed computational think-
ing focus on in-service professional
development, we posit that pre-service
teacher education is an opportune
time to provide future teachers with
the knowledge and understanding they
require to successfully integrate com-
putational thinking into their curricu-
la and practice. The following sections
discuss the relevance of computation-
al thinking constructs in K–12 educa-
tion. We also discuss how to embed
computational thinking into class-
rooms by using it as a methodology for
teaching programming. In addition,
we provide examples of how teachers
in various disciplines c an use co mput a-
tional thinking to address and enhance
tional thinking and the core constructs
that would make it relevant for key
stakeholders from K–12 education and
teacher-training programs.
Denning suggested13 that the idea
of computational thinking has been
present since the 1950s and 1960s “as
algorithmic thinking,” referring specif-
ically to using an ordered and precise
sequence of steps to solve problems
and (when appropriate) a computer to
automate that process. Today, the term
“computational thinking” is defined by
Wing28 as “solving problems, designing
systems, and understanding human
behavior, by drawing on the concepts
fundamental to computer science.”
Computational thinking also involves
“using abstraction and decomposition
when attacking a large complex task or
designing a large complex system.”28
A report on computational thinking
by the National Council for Research
suggested it is a cognitive skill the av-
erage person is expected to possess.
For example, the cognitive aspects of
computational thinking involve the
use of heuristics, a problem-solving ap-
proach that involves applying a general
rule of thumb or strategy that may lead
to a solution.28 This heuristic process
involves searching for strategies that
generally produce the right solution
but do not always guarantee a solution
to the problem. For example, “asking
for directions in an unfamiliar place”
from a local usually leads one to the
right place, but one could also end up
at a wrong place, depending on one’s
understanding of local geography.17
Heuristic processes can be contrasted
Edtech start-up pavilion at International Society for Technology in Education conference.
APRIL 2017 | VOL. 60 | NO. 4 | COMMUNICATIONS OF THE ACM 57
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Algorithms are central to both
computer science and computational
thinking. Algorithms underlie the
most basic tasks everyone engages in,
from following a simple cooking recipe
to providing complicated driving direc-
tions. Because there is a general mis-
conception that algorithms are used
only to solve mathematical problems
and are not applicable in other disci-
plines,29 it is important to introduce
students to algorithms by first using
examples from their daily lives. For ex-
ample, in early grades, teachers could
highlight the steps involved in brush-
ing teeth, while in later grades, stu-
dents could engage in following steps
during a lab experiment. Understand-
ing algorithms as a set of precise steps
provides the basis for understanding
how to develop an algorithm that can
be implemented in a computing pro-
gram. Students can be exposed to the
computational thinking concept of ab-
straction by creating models of phys-
ics entities (such as a model of the solar
system).3 Abstraction helps students
learn to strip away complexity in order to
reduce an artifact to its essence and still
be able to know what the artifact is. In
another example, Barr and Stephenson3
suggested students can learn about
parallelization by simultaneously
running experiments with different
parameters. A number of leading re-
search, educational, and funding orga-
nizations have argued for the need to
introduce K–12 students to these core
constructs and practices.
Computational Thinking
in K–12 Education
The National Research Council (NRC)22
highlighted the importance of expos-
ing students to computational thinking
notions early in their school years and
helping them to understand when and
how to apply these essential skills.3,22
The NRC report22 on the scope and na-
ture of computational thinking high-
lighted the need for students to learn
the related strategies from knowledge-
able educators who model these strat-
egies and guide their students to use
them independently. Similarly, Barr
and Stephenson3 argued that, given
that students will go into a workforce
heavily influenced by computing, it is
important for them to begin to work
with computational thinking ideas and
existing learning outcomes. Finally, we
discuss ways to implement computa-
tional thinking into pre-service teacher
training, including how teacher educa-
tors and computer science educators
can collaborate to develop pathways to
help pre-service teachers become com-
putationally educated.
What Is Computational Thinking?
How do we define computational
thinking and use the definition as a
framework to embed it in K–12 class-
rooms? Wing’s seminal column28 of-
fered a promising definition of compu-
tational thinking: “… breaking down
a difficult problem into more familiar
ones that we can solve (problem de-
composition), using a set of rules to
find solutions (algorithms), and us-
ing abstractions to generalize those
solutions to similar problems.” Fi-
nally, automation is the ultimate step
in computational thinking that can
be implemented through computing
tools. These concepts cut across disci-
plines and could be embedded across
subjects in elementary and second-
ary schools. Based on this definition,
a steering committee formed by the
Computer Science Teachers Associa-
tion (CSTA https://www.csteachers.
org/) and the International Society for
Technology in Education (ISTE https://
www.iste.org/) presented a computa-
tional thinking framework for K–12
schools in 2011 with nine core com-
putational thinking concepts and ca-
pabilities, including data collection,
data analysis, data representation,
problem decomposition, abstraction,
algorithms and procedures, automa-
tion, parallelization, and simulation.
They were also discussed in 2015 in
the Computing at School (CAS) frame-
work and guide for teachers to enable
teachers in the U.K. to incorporate
computational thinking into their
teaching work.10 CSTA/ISTE and CAS
also provide pedagogical approaches
to embed these capabilities across the
curriculum in elementary and second-
ary classes. For example, CSTA/ISTE
describes how the nine core computa-
tional thinking concepts and capabili-
ties could be practiced in science class-
rooms by collecting and analyzing data
from experiments (data collection and
data analysis) and summarizing that
data (data representation).
Computational
thinking is often
mistakenly
equated with
using computer
technology.
58 COMMUNICATIONS OF THE ACM | APRIL 2017 | VOL. 60 | NO. 4
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practices: connecting computing, creat-
ing computational artifacts, abstracting,
analyzing problems and ar tifa cts , co m-
municating, and collaborating. They
are designed to allow students to de-
velop a deep understanding of compu-
tational content and how computing is
changing our world.6 The course is also
structured around seven big ideas: cre-
ativity, abstraction, data and informa-
tion, algorithms, programming, the
Internet, and global impact. These big
ideas from computer science overlap
with the computational thinking con-
cepts detailed in the CSTA/ISTE frame-
work outlined earlier, but the Com-
puter Science Principles course also
adds programming as a fundamental
concept. Programming is the next step
in the computational thinking frame-
work, allowing students to develop
software and create computational ar-
tifacts like visualizations.6
Programming allows students to
develop and execute algorithms while
providing opportunities for them to
show creative expression, create new
knowledge, and solve problems.6 While
programming is one of big ideas of
Computer Science Principles, the goal
is to go beyond learning one particular
type of programming language to how
computing tools can be used to solve
problems through an iterative proc-
ess.6 The Computer Science Principles
framework is being used by a number
of leading educational organizations
across the U.S. to instantiate differ-
ent versions of the Computer Science
Principles course. For example, Proj-
ect Lead The Way, a nonprofit organi-
zation that provides a transformative
learning experience for K–12 students
and teachers across the U.S. through
pathways in computer science, engi-
neering, and biomedical science has
rolled out its version of the Computer
Science Principles course to more
than 400 schools. Another organiza-
tion, Code.org, is rolling out its own
advanced placement computer science
curriculum to public school districts
across the U.S.
While embedding computational
thinking in STEM subject areas or
through standalone courses is an im-
portant effort, the trans-disciplinary
nature of computational thinking
competencies provides an opportunity
to integrate computational thinking
ideas into all K–12 subject areas. The
goal of computational thinking, said
Hemmendinger,16 is “to teach them
[students] how to think like an econo-
mist, a physicist, an artist, and to un-
derstand how to use computation to
solve their problems, to create, and to
discover new questions that can fruit-
fully be explored.” Research on embed-
ding computational thinking in K–12
is also starting to emerge and has sug-
gested that students exposed to com-
putational thinking show significant
improvement in their problem-solving
and critical-thinking skills.5 A 2015
study by Calao et al.5 reported that in-
tegrating computational thinking in a
sixth-grade mathematics class signifi-
cantly improved students’ understand-
ing of mathematics processes when
compared to a control group that did
not learn computational thinking in
their math class.
Although computational thinking is
deeply connected to the activity of pro-
gramming, it is not essential to teach
programming as part of a pre-service
computational thinking course. Such
courses should focus on computa-
tional thinking within the context of
the teachers’ content areas. Those in-
terested in programming should have
access to standalone courses that focus
more specifically on programming and
computer science. Despite the current
lack of clarity as to the definition of
computational thinking, Wing’s ideas
provide a good starting point for con-
ceptualizing it for teacher educators.
Similarly, the computational thinking
concepts and practices outlined in the
CSTA/ISTE framework exemplify how
these concepts can be used across the
curriculum and to prepare pre-service
teachers. The rest of this article focuses
on how to develop pre-service teacher
computational thinking competencies
not related to programming to allow
them to teach computational thinking
ideas in their classrooms.
To achieve these goals, we need to
prepare new teachers who are able to
incorporate computational thinking
skills into their discipline and teach-
ing practice so they can guide their stu-
dents to use computational thinking
strategies.22 The following section dis-
cusses how the education community
can prepare teachers to embed compu-
tational thinking in their curricula and
tools in grades K–12. Specifically, they
discussed3 the need to highlight “algo-
rithmic problem solving practices and
applications of computing across dis-
ciplines, and help integrate the appli-
cation of computational methods and
tools across diverse areas of learning.”
Recent educational reform move-
ments (such as the Next Generation
Science Standards and the Common
Core) have also focused on computa-
tional thinking as a key skill for K–12
students. For example, the Next Gen-
eration Science Standards (NGSS) have
identified computational thinking as
key scientific and engineering prac-
tices that must be understood and ap-
plied in learning about the sciences.20
Computational theories, information
technologies, and algorithms played
a key role in science and engineering
in the 20th century; hence, NGSS sug-
gested allowing students to explore
datasets using computational and
mathematical tools. One example of
embedding computational thinking
in science classrooms is Project GUTS
(Growing Up Thinking Scientifically),
which highlights what computational
thinking looks like for students using
three domains: modeling and simu-
lation, robotics, and game design.18
Using the NetLogo computational en-
vironment, Project GUTS focuses on
abstraction, automation, and analysis
through a use-modify-create learning
progression to allow students to use
the tools, as well as modify and create
them, thus deepening their acquisition
of computational thinking concepts in
the context of science learning. Simi-
larly, the Scalable Game Design proj-
ect engages students in computational
thinking concepts through game and
simulation design in science classes.23
While such efforts involve embed-
ded computational thinking in ele-
mentary and secondary subject areas,
the College Board, with support from
the National Science Foundation, has
led the effort to introduce students
to computational thinking constructs
through a standalone advanced-place-
ment course called Computer Science
Principles designed to go beyond pro-
gramming and focus on computational
thinking practices to “help students co-
ordinate and make sense of knowledge
to accomplish a goal or task.”6 The course
includes six computational thinking
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contributed articles
IMAGE FROM SAN JOSE STATE UNIVERSITY, SAN JOSE, CA / HTTPS://WWW.SJSU.EDU
trol group) did not experience the com-
putational thinking module, while the
second (the experimental group) spe-
cifically learned about computational
thinking ideas by working through the
module. The authors found the major-
ity of pre-service teachers in the control
group viewed computational think-
ing as integration of technology in the
classroom, whereas the majority of
participants in the experimental group
developed their understanding of
computational thinking as a problem-
solving approach by using algorithms/
heuristics. Results also suggested pre-
service teachers in the experimental
group were better able to articulate
how to integrate computational think-
ing in K–12 classrooms as compared to
the control group. The results from the
study indicate the potential to integrate
computational thinking for pre-service
teachers within existing teacher-edu-
cation courses. The authors used ex-
amples from daily life, as well as dis-
cipline-specific examples, to highlight
computational thinking to pre-service
teachers. For example, they used an ex-
ample of giving directions from point
A to point B to highlight what an algo-
rithm is (a step-by-step route), the ef-
ficiency of algorithms (how to provide
the best way to get from A to B), abstrac-
tion (how to effectively give any direc-
tion), and automation (how to design
a system like Google Maps). In another
example, Yadav et al.29 showcased the
idea of parallel processing by discuss-
practice and offers recommendations
to prepare the next generation of com-
putationally literate teachers.
Computational Thinking
and Teacher Education
As discussed previously, research-
ers have argued that computational
thinking needs to be on par with
reading, writing, and arithmetic.3,28
Recent efforts to train teachers to
embed computational thinking have
focused on in-service teacher profes-
sional development,18 but there is lim-
ited understanding of how to engage
pre-service teachers from other content
areas in computer science and compu-
tational thinking.29 This complication is
compounded by the fact that few teach-
er-preparation institutions offer pro-
grams specifically for computer science
teachers. Furthermore, certification
and licensure of computer science
teachers is deeply flawed, as detailed in
the “Bugs in the System” report by the
Computer Science Teacher Associa-
tion.8 It is vital that teacher education
programs address the lack of teacher
training around computer science
ideas, given the burgeoning grassroots
movement and impetus from govern-
ments to expand computer science
learning opportunities in elementary
and secondary classrooms, including
the Computer Science For All initiative
launched January 2016 in the U.S.
So how do teacher educators develop
mechanisms to expose pre-service
teachers to computational think-
ing constructs and understanding
within the context of their subject
areas? How do we develop pre-ser-
vice teachers’ knowledgebase so they
can provide relevant, engaging, and
meaningful computational think-
ing experiences for their students?
Darling-Hammond and Bransford12
proposed a framework that could be
adapted to prepare teachers to incor-
porate computational thinking, ar-
ticulating knowledge, skills, and dis-
positions that teachers should acquire
and suggesting that teachers need
knowledge of learners, as well as of
subject matter and curriculum goals.
Teacher educ ators need to first dev el-
op pre-service teachers’ knowledge and
skills on how to think computationally
and then how to teach their students to
think computationally. It is thus impera-
tive for pre-service teachers to under-
stand computational thinking in the
context of the subject area they will be
teaching. This requires them to have
deep understanding of their own disci-
pline and knowledge of how computa-
tional thinking concepts relate to what
students are learning in the classroom.22
Moreover, the NRC report on the peda-
gogical aspects of computational think-
ing argued that teaching this content
could put teachers in new and unfamil-
iar roles in classrooms where students
collaborate to solve complex problems.
It is thus important that teacher educa-
tors “build on what teachers know and
feel comfortable doing.”21
Developing pre-service teachers’
competencies to embed computation-
al thinking in their future classrooms
requires that they are taught to think
computationally, as well as how to
teach their students to think compu-
tationally, especially in the context of
specific subject areas. Teacher-train-
ing programs are a natural place to
introduce teachers to computational
thinking and how to incorporate it in
their content. A 2014 study by Yadav et
al.29 examined the influence of a one-
week computational thinking module
on pre-service teachers’ understand-
ing and attitudes toward embedding
computational thinking in their fu-
ture classrooms. Pre-service teachers
enrolled in a required introductory
educational psychology course were
divided into two groups. One (the con-
Project Lead the Way session at San José State University, San Jose, CA.
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courses are typically disconnected
from the teaching theories and methods
pre-service teachers learn in other
education courses, focusing instead
on technology (such as Web 2.0 tools
to teach).19 Rather than focus on using
educational technology tools, educa-
tional-technology courses should be
revised to provide pre-service teachers
with opportunities to think computa-
tionally and experience computational
thinking as a generic set of skills and
competencies that do not necessarily
depend on computers or other educa-
tional technology.
Redesigning introduction-to-edu-
cational-technology courses around
learning core computational thinking
concepts and capabilities is also an op-
portunity for computer science and edu-
cation faculty to work together. Taylor25
wrote that many early courses focus
on simple programming intended to
help students “learn something both
about how computers work and how
his or her own thinking works.” About
a decade ago, however, educational-
technology courses moved away from
this view and began to focus instead
on use of predesigned software tools
in the classroom. The recent burgeon-
ing movement around computational
thinking is an opportunity to reset
and redesign educational technology
courses, making them both more rel-
evant and more rigorous.
Given the importance of exposing
pre-service teachers to computational
thinking in the context of their disci-
pline, educational technology courses
could be customized for groups of pre-
service teachers based on their subject
areas and tied to their day-to-day class-
room activities. The Technological
Pedagogical Content Knowledge (TPACK)
framework19 is a useful model for inte-
grating computational thinking where
the related ideas are closely knit within
the subject matter and pedagogical
approaches pre-service teachers will
teach in their future classrooms.
TPACK extends Shulman’s idea24 of
pedagogical content knowledge by
including knowledge teachers need
to teach effectively with technology.19
TPACK suggested teachers learn about
effective technology integration within
the context of subject matter and
pedagogy; similarly, teachers need
to develop computational thinking
knowledge within the context of
their content knowledge and peda-
gogical knowledge.
Methods courses in teacher-edu-
cation programs also provide an op-
portunity to help pre-service teachers
incorporate computational thinking in
the context of their future subject areas.
Methods courses enable them to acquire
new ways to think about teaching and
learning in one particular subject area
and provide opportunities for “develop-
ing pedagogical ways of doing, acting,
and being as a teacher.”1 A methods
course weaves “together knowledge
about subject matter with knowledge
about children and how they learn,
about the teacher’s role, and about
classroom life and its role in student
learning.”1 Within this context, a
methods course could also be a place
where pre-service teachers explore
computational thinking ideas within
the context of their specific subject-
ing the quickest way for two friends to
buy movie tickets when three lines are
available; see the Computational Think-
ing Modules at http://cs4edu.cs.purdue.
edu/comp_think for other examples of
how computational thinking constructs
were highlighted for pre-service teach-
ers. However, the study by Yadav et al.29
was conducted in a general teacher-
education course for pre-service teach-
ers from all content areas, next steps
should involve embedding computa-
tional thinking concepts into courses
for teachers of specific subject areas.
Given the strict sequence of courses
for teacher education students, teach-
er educators need to expose pre-service
teachers to computational thinking
ideas and competencies through ex-
isting coursework. One opportunity
that offers a natural fit is to introduce
computational thinking within exist-
ing educational-technology courses
in teacher-education programs. These
Recommendations for computational thinking in teacher preparation.
Curriculum. Develop a pre-service teacher education curriculum to prepare teachers to embed
computational thinking in their classrooms.
Core ideas. Introduce pre-service teachers to core ideas of computational thinking by redesigning
educational technology courses.
Methods courses. Use elementary and secondary methods courses to develop pre-service teachers’
understanding of computational thinking in the context of the discipline.
Collaboration. Computer science educators and teacher educators collaborate on developing
computational thinking curricula that goes beyond programming.
Teacher education. Use existing resources and curriculum standards to assimilate computational
thinking into pre-service teacher education.
Developing pre-service teacher computational thinking.
Educational
technology courses
to develop
computational
thinking knowledge
Partnerships
between computer
science educators
and teacher
educators
Knowledge needed
to teach
computational
thinking
Methods courses to
apply computational
thinking concepts to
various subject areas
APRIL 2017 | VOL. 60 | NO. 4 | COMMUNICATIONS OF THE ACM 61
contributed articles
the scope of computational thinking
concepts and capabilities, as well as
engage with computational tools that
nurture development of computa-
tional thinking competencies. These
courses would ideally be developed by
education faculty and computer sci-
ence faculty collaborating to identify
appropriate learning outcomes and
available resources.
Because integrating computational
thinking into any curriculum involves
exposing teachers and students to con-
cepts and practices used by computer
scientists, it is important for teacher
educators to work closely with computer
science faculty. Similarly, education fac-
ulty have a nuanced understanding of
K–12 curriculum and educational poli-
cies that are key to ensuring current com-
putational thinking efforts are success-
ful. A 2016 report by the Computing
Research Association9 highlighted the
need for computer science faculty to
establish interdisciplinary connections
with colleagues from other disciplines
(such as teacher education, educational
psychology, and learning sciences).
These collaborations included co-
developing and co-teaching courses that
prepare teachers to teach computa-
tional thinking; see Yadav and Korb31
for what such a course might look
like. Furthermore, faculty could have
joint appointments in education and
computer science that would enable
them to jointly develop programs
and collaborate on research around
teaching computational thinking.8
This would enable computer scientists
and teacher educators to collaborate
on developing both plugged and un-
plugged activities to expose pre-service
teachers to computational thinking and
its implementation. The accompany-
ing figure showcases the intercon-
nectedness of our recommendation
for developing pre-service teacher
competencies as computer science and
teacher educators collaborate to develop
computational thinking understand-
ing through educationa-technology
courses. Pre-service teachers then
learn how to use that knowledge to
teach children to think computation-
ally in the context of a particular subject
area through methods courses.
Additionally, many available re-
sources could be incorporated into an
educational-technology or subject-spe-
area specializations. For example, in
a Methods of Teaching English course,
prospective teachers could learn to
embed algorithms into a writing
activity by asking students to write a
detailed recipe—a step-by-step series
of instructions—for a favorite food.
Similarly, pre-service teachers in a social
studies methods course could learn to
incorporate data analysis and pattern
recognition by having students
collect and analyze population statis-
tics and use it to identify and represent
trends.3 Data-analysis tools could be
as simple as Piktochart, which allows
students to represent data and infor-
mation through infographics, to more
advanced tools like Google Charts,
which allow students to dynamically
represent data using customizable and
interactive charts. Pre-service teachers
in a science-methods course could
be exposed to computational think-
ing through computational models
for demonstrating scientific ideas and
phenomena to their future students.27
The computational models could also
be used to test hypotheses, as well as
solutions to problems.23 As discussed
earlier in this article, students could
use tools like NetLogo and Scalable
Game Design to develop computa-
tional models as they engage in simu-
lation and game design.
The general concepts of computa-
tional thinking acquired in the educa-
tional-technology course and the disci-
pline-specific computational thinking
practices acquired in the methods
courses would help pre-service teach-
ers connect computational thinking
to content they will cover in their fu-
ture classrooms. In this way, the con-
structs of pedagogical content knowl-
edge24 and technological pedagogical
content knowledge19 provide support
for developing pre-service teachers’
computational thinking knowledge.
Specifically, educational-technology
courses would serve as a foundation
for developing content knowledge for
computational thinking. This knowl-
edge would allow teachers to explore
core computational thinking ideas,
why those ideas are central, and how
computational thinking constructs
are similar to or differ from other par-
allel concepts (such as mathematical
thinking).24 As pre-service teachers
take teaching-methods courses, they
would learn to integrate computa-
tional thinking into the context of par-
ticular subject areas. This would allow
them to learn how to represent and for-
mulate computational thinking in the
subject and make it comprehensible
to students.24 By engaging pre-service
teachers in computational thinking
ideas in the context of teaching their
content area, teacher educators could
better ensure it becomes part of their
own and their students’ vocabulary
and problem-solving tool set.
The Computational Thinking Pro-
gression Chart3 provides a starting
framework around which teacher edu-
cators could begin to shape pre-service
teacher experiences in elementary
and secondary teacher-education pro-
grams. Within elementary education,
incorporating computational thinking
exercises into literacy learning offers a
straightforward transition for teacher
candidates. For example, pre-service
teachers would be able to explore how
to include abstraction into the analysis
of themes within prose or poems us-
ing textual details or in summarizing
text.7 They could also build a lesson
plan that incorporates data analysis
and data representation by having stu-
dents identify words that depict feel-
ings and comparing how they are rep-
resented across different versions of
the same story. Similarly, pre-service
teachers could embed computational
thinking into lesson plans for language
arts at the secondary level by allowing
students to collect and integrate data/
information from multiple sources to
visually represent common themes. El-
ementary- and secondary-level pre-ser-
vice science teachers could include data
collection, analysis, and representation
into any activity in which students gath-
er data and identify and represent pat-
terns in that data. Finally, social studies
pre-service teachers could explore how
to use large datasets (such as census
data) to enable students to explore and
identify patterns and discuss the im-
plications of the increasing access to
large amounts of personal data.
While existing teacher-education
courses provide opportunities to intro-
duce pre-service teachers to computa-
tional thinking, some programs might
consider developing standalone courses
and/or certificate programs that al-
low pre-service teachers to discover
62 COMMUNICATIONS OF THE ACM | APRIL 2017 | VOL. 60 | NO. 4
contributed articles
ering them to teach students these
higher-order-thinking skills. Teach-
er-education programs are the oppor-
tune time to engage teachers early in
their preparation to formulate ways
to integrate computational thinking
into their practice. Educational-tech-
nology and methods courses in ele-
mentary and secondary teacher prep-
aration programs are ideal places for
teacher educators to discuss compu-
tational thinking. The accompanying
table summarizes our recommenda-
tions for teacher educators to embed
computational thinking into teacher-
education programs.
In summary, we have emphasized
the importance of embedding compu-
tational thinking curricula in teacher
education and provided recommenda-
tions for how teacher educators might
be able to do it. For this effort to suc-
ceed, however, computer science and
education faculty must work collab-
oratively, as both groups bring comple-
mentary expertise in computing and
teacher development.
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Aman Yadav (ayadav@msu.edu) is an associate professor
in the College of Education and director of the Masters of
Arts in Educational Technology program at Michigan State
University, East Lansing, MI.
Chris Stephenson (stephensonc@google.com) is the
head of Computer Science Education Strategy at Google,
Mountain View, CA.
Hai Hong (haihong@google.com) leads the K–12 Education
U.S. Outreach team at Google, Mountain View, CA.
Copyright held by the authors.
cific methods course that could help
pre-service teachers connect computa-
tional thinking to their daily lives and
to classroom contexts. For example,
pre-service teachers could carry out
“CS Unplugged” activities (http://csun-
plugged.org/), many of which teach
computational thinking skills with-
out needing a computer and are easily
adapted to other subjects. Pre-service
teachers could also use Scratch—a pro-
gramming environment that allows
students to create programs by drag-
ging and dropping blocks representing
core constructs—to create simple pro-
grams and animations.
Recognizing the need for teachers
to address computational thinking in
their curricula and practice, several
organizations, including the CSTA,
ISTE, and the National Science Teach-
ers Association, are also developing
and sharing tools and resources for
current and future teachers. Google’s
Exploring Computational Thinking
website (http://g.co/exploringCT) pro-
vides more than 130 lesson plans and
sample programs aligned with inter-
national education standards; a col-
lection of videos demonstrating how
computational thinking concepts are
used in real-world problem solving;
and a “Computational Thinking for
Educators” online course (http://g.co/
computationalthinking). Since 2014,
the Computer Science Education Re-
search Group at the University of Ad-
elaide in Australia has been partnering
with Google to create introductory cours-
es for implementing Australia’s Digital
Technologies Curriculum and teaching
computer science and computational
thinking at primary and secondary lev-
els, explicitly tied to the Australian cur-
riculum (https://csdigitaltech.appspot.
com). These resources provide a start-
ing point for teacher educators to in-
corporate computational thinking
ideas and relate them to specific sub-
ject area pre-service teachers will go on
to teach in their future classrooms.
Conclusion
The 21st century is heavily influenced
by computing, making it imperative
that teacher educators incorporate
computational thinking into elemen-
tary and secondary education. This
means they must prepare teachers
for computational thinking,2 empow-
Watch the authors discuss
their work in this exclusive
Communications video.
http://cacm.acm.org/videos/
computational-thinking-for-
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