A Methodology to Conduct Computational Thinking Activities in
Children’s Educational Context
Flavio Nicastro, M. Cec
´
ılia C. Baranauskas and Ricardo da S. Torres
Institute of Computing, University of Campinas, Campinas, Brazil
Keywords:
Computational Thinking, Computational Thinking Methodology, Creative Learning, Educational Methods.
Abstract:
Computational thinking (CT) development has been receiving considerable attention in academic discussions.
In this work, we propose a methodology for conducting computational thinking activities. The results from
a case study involving educators and children from 8 to 11 years old shows that they were pleased when
engaging in the development of activities following a methodology that encourages the reflection about what
they should do and about what results they are achieving. Some challenges were identified, as well as the need
of addressing them to reach acceptance of this kind of methodology by both children and educators. Our next
step will concern the evaluation of the use of this methodology, together with educators, in the planning of
CT-related activities.
1 INTRODUCTION
Education has been undergoing great transformations
in recent years. There is a growing number of papers
that advocate changes in the traditional educational
system. Some of those changes include: finishing
the division by subject, finishing the current model
of classrooms, or finishing the space-constrained ac-
tivities that limit the creativity of students. In this
new scenario, something that is in great evidence
is computational thinking. According to Jeannette
Wing (Wing, 2006), pages 33 and 35:
“Computational thinking is a fundamental
skill for everyone, not just for computer scien-
tists. To reading, writing, and arithmetic, we
should add computational thinking to every
child analytical ability. Computational think-
ing is reformulating a seemingly difficult prob-
lem into one we know how to solve, perhaps
by reduction, embedding, transformation, or
simulation. Computational thinking is a way
humans solve problems; it is not trying to get
humans to think like computers.
From 2006 on, Wing published four more arti-
cles about the subject (Henderson et al., 2007; Wing,
2008; Wing, 2011; Wing and Stanzione, 2016), and
by taking into account a literature review, we found
several works about this research topic published in
various selective conferences and journals (Bau et al.,
2017; Yadav et al., 2017; Baranauskas and Carbajal,
2
1
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166
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500
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3500
1950+a+
1960
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1970
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1980
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2005
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
NUM BER+ OF + PUBLI CA T I O NS
YEAR
RESULTS+OF+ THE+SEARCH+ON+GOOGLE+SCHOLAR+WITH+THE+TERM+"COMPUTATIONAL+THINKING"
Figure 1: Results of the search on google scholar with the
term “Computational Thinking”, as of December 2017.
2017; Grover and Pea, 2013; Denning, 2017; Araujo
et al., 2016; Perkovi
´
c et al., 2010; Barr and Stephen-
son, 2011; Guzdial, 2008; Basawapatna et al., 2011;
Repenning et al., 2010; Lu and Fletcher, 2009). In
Figure 1, we can see the result of a Google Scholar
search with the term “Computational Thinking”, and
we note the increasing number of publications related
to this term in recent years, especially after 2006.
This figure shows that the subject of computa-
tional thinking has been gaining more and more space
in academic discussions. However, there is still no
consensus on its terms and concepts, its boundaries,
and its scope (Baranauskas and Carbajal, 2017; Bren-
nan and Resnick, 2012). Based on Wing’s definitions
Nicastro, F., Baranauskas, M. and Torres, R.
A Methodology to Conduct Computational Thinking Activities in Children’s Educational Context.
In Proceedings of the 10th International Conference on Computer Supported Education (CSEDU 2018) - Volume 2, pages 309-316
ISBN: 978-989-758-291-2
Copyright © 2018 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
309
and on several other papers that aim to characterize
the term, we understand computational thinking as the
practice of the set of skills derived from Computer
Science that make the person able to approach prob-
lems in situations of his daily activities.
In recent years, there has also been a consider-
able increase in the number of systems used to teach
programming with lesson plans and guided activities,
such as Scratch
1
, Code.org
2
, and AppInventor
3
. Sys-
tems like those are being used in several educational
activities that aim at developing skills associated with
computational thinking around the world. However,
when conducting activities with such systems, educa-
tors do not follow or are not aware of well-established
procedures to guide students in their problem-solving
tasks. In the literature review, we have not found a
methodology that was formally described with the ob-
jective of conducting activities that aim at the devel-
opment of skills associated with computational think-
ing.
Given this scenario, this work proposes a method-
ology to help educators on conducting activities that
aim at the development of skills associated with com-
putational thinking. With the objective of analyzing
the performance of children in activities related to the
development of skills associated with computational
thinking, using the proposed methodology, we car-
ried out two workshops in August and September of
2017. These workshops are detailed in Section 4 and
involved educators and children from 8 to 11 years.
The results showed that both were pleased when en-
gaging in activities following a methodology that en-
courages them to reflect on what they should do and
on the results they are achieving. Some challenges
were identified, and it is necessary to address them to
foster the adoption of practices that aim at the devel-
opment of skills associated with computational think-
ing.
The remaining of this text is organized as fol-
lows: Section 2 presents related work in the area of
computational thinking; Section 3 introduces the pro-
posed methodology, while Section 4 describes a case
study concerning the use of the proposed methodol-
ogy in activities conducted with children. Finally,
Section 5 presents our conclusions and directions for
future work.
1
https://scratch.mit.edu (As of Dec. 2017).
2
https://code.org (As of Dec. 2017).
3
http://appinventor.mit.edu/explore/ (As of Dec. 2017).
2 BACKGROUND
Computational Thinking is not something new. In
a search for publications with this term, we found
some papers on mathematics teaching (Bowes, 1955;
Arnold, 1962) published in the 1950s and 1960s.
More specifically, related to the context of computer
use in education, we found the article “Uses of Tech-
nology to Enhance Education” (Papert, 1973). In this
paper, Seymour Papert describes the proposal sent
to the National Science Foundation (in the United
States) asking for support on research about children’s
thoughts and elementary education. In the 1970s,
Seymour Papert pioneered the creation of the LOGO
language and in the studies about the learning pro-
cesses of children mediated by the use of program-
ming languages and artifacts, such as a robot turtle
that helped to understand the concepts of geometry
through programming in the LOGO language (Papert,
1980).
In 2006, the publication of Jeannette Wing, “Com-
putational Thinking” (Wing, 2006), had a significant
impact in the computers & education community,
bringing popularity and interest of academics to the
subject. In this publication, Jeannette Wing presents
computational thinking as a set of problem-solving
mental processes derived from Computer Science ap-
plicable to any domain. It introduces the idea that
computational thinking is a central practice for all sci-
ences which is a fundamental and useful analytical
thinking skill for all people. It is used to break a dif-
ficult problem into more familiar pieces that we can
solve (problem decomposition), using a set of rules to
find solutions (algorithms), and using abstractions to
generalize these solutions to similar problems.
From this pioneering initiative on, several works
have been published on this topic. The article, “Com-
putational Thinking for Teacher Education” (Yadav
et al., 2017), reviews various papers that have been
written on this topic. The author draws attention to
the growing enthusiasm for computer science educa-
tion in many countries, such as Australia, USA, and
England. He points out that in 2012 the Royal Soci-
ety in England published that: “Every child should
have the opportunity to learn concepts and princi-
ples of computing, including computer science and
information technology, from the beginning of pri-
mary education”. It also states that in 2016, the US
College Board launched a new High School Com-
puter Science curriculum called “Principles of Com-
puter Science”, with a focus on exposing students to
computational thinking to help them understand how
computing influences the world. The author stresses
that within the computer science education commu-
CSEDU 2018 - 10th International Conference on Computer Supported Education
310
nity, computational thinking is a familiar term, but
there is confusion among teachers and managers of
what is really meant, mistakenly compared to the use
of technology and computers. In addition to pre-
senting the definition of computational thinking by
Jeannette Wing in 2006, he suggests some ideas that
would make it relevant to the key players involved in
elementary education and teacher training programs.
Complementing the definition of Wing, the authors
state that, according to the Computer Science Teach-
ers Association (CSTA) and the International Society
for Technology in Education (ISTE), computational
thinking relies on nine core concepts and capabili-
ties: data collection, data analysis, data representa-
tion, problem decomposition, abstraction, algorithms
and procedures, automation, parallelization, and sim-
ulation.
Although the concept is still formally undefined,
there is some agreement on its meaning in the direc-
tion that computational thinking involves the mental
processes that occur in solving problems by creating
computer programs to solve them (Baranauskas and
Carbajal, 2017).
3 THE PROPOSED APPROACH
In this work, we propose a methodology to conduct
activities that aim at the development of skills asso-
ciated with computational thinking through a process
model to be followed in the conduction of these activ-
ities. In Figure 2, the methodology steps, which will
be detailed as follows, can be visualized. The symbol
of a full circle is used to indicate the initial state of the
process, while a small circle filled with an empty cir-
cle indicates the end of the process. The rectangles
with the rounded corners represent the main steps.
The first and second steps contemplate the reflection
cycle and the third and fourth, the development cy-
cle. The light blue full arrow represents a precedence
relationship between steps. The full dark blue curve
shows a step in a cycle that must occur while are not
ready for the next one. The final arrow indicates that,
at the end of the process, the work can be restarted by
initiating a new learning cycle.
The model is comprised of the following steps:
1. Planning: This stage consists in defining the ob-
jectives of the activity and listing the steps that
must be followed to achieve such objectives.
2. Simulation: This step contemplates passing the
planning as if it were running, verifying if the de-
fined steps lead to the objective of the activity. In
case of inconsistency, the planning step should be
performed again.
Figure 2: Proposed model for the process of conducting ac-
tivities.
3. Execution: In this step, the plan will be put into
practice. Considering, for example, an activity in
which a computer program should be developed,
one should code and test whether it is in accor-
dance with the plan.
4. Evaluation: This step consists in evaluating
the execution result. Should remain in the
cycle ExecutionEvaluationExecution while
failures in the execution are identified.
5. Decision: This step consists in verifying whether
the objective has been reached satisfactorily. If
so, the process should be terminated, and a new
learning cycle could be started. If not, one should
review the provided solution, define necessary
changes and return to the planning step.
The proposed methodology has the purpose of as-
sisting those interested in conducting an activity that
aims to develop a skill related to computational think-
ing (CT).
In Section 4, we present a case study realized with
a group of educators and children from 8 to 11 years
old, in which we used this methodology to conduct
some CT-related activities.
A Methodology to Conduct Computational Thinking Activities in Children’s Educational Context
311
4 CASE STUDY
With the objective of analyzing the performance of
children in activities related to the development of
skills associated with computational thinking, using
the proposed methodology, we carried out two work-
shops in August and September of 2017.
The workshops were conducted at PRODECAD
4
with the support of members of the InterHad
group
5
, as part of the project “Oficinas de
Comunicac¸
˜
ao Alternativa, Aumentativa e Criativa,
com crianc¸as, usando interfaces computacionais
vest
´
ıveis e tang
´
ıveis”
6
, and it consisted in carrying
out activities with educators and children using the
proposed methodology.
4.1 Experimental Protocol for the
Development of Activities
The activities consisted of creating a program on
a tablet using ScratchJr
7
following the proposed
methodology. The activities were carried out with six
educators and 14 children from 8 to 11 years. At the
beginning of each session, they were guided on the
purpose of the task, and the methodology and its cor-
respondent model was explained.
The solution development was expected to be per-
formed in two parts: first, composed of the plan-
ning and simulation steps, the participants received
a printed sheet with a scenario (Figures 3 and 6)
and a paper with instructions, where they should de-
scribe what needed to be done to achieve the goal. Af-
ter these steps, they received a tablet with ScratchJr
and started the second part. In this part, they were
expected to create a program in ScratchJr, test, ver-
ify the result, and make a decision (if they should
redo/improve some aspect or if the result is satisfac-
tory). It was requested that all the reasoning be regis-
4
Programa de Desenvolvimento e Integrac¸
˜
ao
da Crianc¸a e do Adolescente: offers complemen-
tary education for children between 6 and 17 years
old, registered in the scholl Escola S
´
ergio Porto
(http://www.dgrh.unicamp.br/dedic/prodecad As of
September 2017).
5
http://interhad.nied.unicamp.br (As of September
2017).
6
The project is duly registered in the ethics
committee of Unicamp under the CAAE Number:
55678316.4.0000.5404)
7
ScratchJr is an introductory programming language
specifically for tablets, inspired by Scratch (scratch.mit.edu
– As of Dec. 2017) and developed in collaboration between
the DevTech Research Group of Tufts University, the Life-
long Kindergarten Group at MIT Media Lab and Playful In-
vention Company (https://scratchjr.org – As of Dec. 2017).
tered and that if they redesigned something, previous
solutions (planning) should not be discarded (erased
from the sheet). This procedure aims to allow the
analysis of the development of reasoning throughout
the session.
The steps to follow were:
1. Plan what to do;
2. Simulate the activity with the help of the scenario
on paper;
3. Develop the program in ScratchJr;
4. Test and Evaluate the Result;
5. Analyze and Decide. Was the goal achieved?
No: What was wrong? Analyze what could have
been done differently and return to Step 1.
Yes: Are you satisfied with the result?
No: What can be done to improve it? Review
and return to step 1.
Yes: Propose a new challenge and start a new
activity.
At the end of each workshop all participants (chil-
dren and teachers) filled a Self-Assessment Manikin
(SAM) instrument (Bradley and Lang, 1994). SAM
is a nonverbal instrument of self-assessment of emo-
tions, specifically the level of pleasure, arousal, and
dominance, associated with the affective reaction of a
person to a stimulus, in this case, the activities with
tablets. It consists of a pictographic representation in
which each one could register their pleasure, arousal
and dominance in relation to the system that was be-
ing used. For each of the three dimensions of SAM,
the scale of responses ranges from one to nine, where
one represents the lowest level (of pleasure, arousal or
dominance) and nine represents the highest level. In
addition, the children answered a short questionnaire
about their perception of the workshop.
4.1.1 Workshop 1: Algorithmic Solution for a
Structured Problem
In the first workshop, held on August,22 2017, the
program to be developed consisted in indicating the
“steps” of a character along a path until arriving
at a specific place. More specifically, the program
should contain the “steps” needed to get a rabbit to a
house (to meet Alice) by traversing the predetermined
squares on a board (Figure 3).
In this workshop, we held a preliminary session
with the teachers, using the same steps that would
be worked on with the children. The teachers have
had previous contact with ScratchJr’s programming-
like environment through TaPrEC (Carbajal and
CSEDU 2018 - 10th International Conference on Computer Supported Education
312
Início
Figure 3: Scenario created for the activity on Workshop 1.
Objetivo:
Fazer
o
coelho
percorrer
a
trilha
azul
ate
chegar
a
casa
da
Alice
para
tomar
um
cha
1-
-
Planejamento
:
Descrever
passo
a
passo
o
que
deve
ser
feito
para
atingir
o
objetivo
5+
A
5
4+1
A-
1
34
8
1
Figure 4: Procedure (in Portuguese) recorded by a group of
teachers in Workshop 1.
Baranauskas, 2015). The TaPrEC allows program-
ming based on the use of wooden blocks that are
docked to define the movements of the character. The
program developed in TaPrEC leads to an algorithm
that is more symbolic than descriptive. With this, the
two groups of teachers who participated in the work-
shop simply put a sequence with the number of steps
to walk and the direction of the vertical movement (
or ) or horizontal ( or ) - for example, 8 , 4,
etc., as we can see in Figure 4.
After the session with the teachers, we performed
similar procedures with the participation of the chil-
dren. They were split into pairs and the forms were
handed over to them. After the planning phase,
the children received a tablet with ScratchJr, pre-
configured with the board and programmed so that,
when the rabbit meets Alice, a bell would be played
and an invitation (to have a tea with Alice) would ap-
pear on the screen.
All pairs of children used literal descriptions of
what should be done. Some children opted for more
detailed descriptions such as “He has to walk eight
squares forward, turn right and .... Other pairs were
based on the drawings that were in the path: “First go
through the clock and then go through the plate and
turn right .... Examples of these solutions are shown
in Figure 5.
Figure 5: Procedures (in Portuguese) registered by two pairs
of students in Workshop 1.
(a) Scenario (b) Meet with Lambi Zambi
(c) Meet with the fairy (d) Find the wizard
Figure 6: Example of screens related to the scenario and the
meeting of characters in Workshop 2.
4.1.2 Workshop 2: Algorithmic Solution for an
Unstructured Problem
The second workshop was held on September, 12
2017. In this workshop, a strategy was adopted in
which the participants would have more freedom to
create their solutions. They could determine their own
path to be taken, without any paths predefined on the
scenario. As in workshop 1, the goal was to take the
rabbit character to meet Alice. We also included some
other characters in the scenario, whose names should
be discovered. They were also told about the exis-
tence of a hidden character and that they should find
out who it was. The tablet was customized with the
scenario as shown in Figure 6 (a). Also, when the rab-
bit meets another character in his way to Alice, a mes-
sage appears on the screen with the character’s name.
When the horse in the scenario is met, a sound is emit-
ted and a wizard (the hidden character) appears on the
middle of the screen saying his name as shown in
Figure 6 (b), (c), and (d).
In this workshop, children were already aware of
A Methodology to Conduct Computational Thinking Activities in Children’s Educational Context
313
Figure 7: Visibly redone procedure (in Portuguese) by a pair
of students in Workshop 2.
ScratchJr and how to develop their solutions on the
tablet because all of them took part in workshop 1.
This caused an anxiety in most of them in the plan-
ning phase, because they wanted the tablets to pro-
gram as soon as possible. In fact, most of them fin-
ished the planning step very quickly, which led to the
creation of very simplistic descriptions of the solu-
tions. On the other hand, two pairs took much longer
than the others at this stage, even comparing with
mean time observed in the first workshop. These
pairs actually engaged in the planning and simulation
phase, including drawing paths in the scenario. When
they started programming, they were much faster and
made a much more succinct program.
Another point we noticed is that children resist the
idea of not erasing what they planned when they redo
it. Note, for example, in the procedure described by
a pair in Figure 7, in which even the names of the
characters are already present; something that could
only be discovered after running the program on the
tablet.
4.2 Results and Analysis
During the planning and simulation phase, all pairs
were quite entertained and developed their own plan-
ning to solve the task. We note that everyone was en-
gaged in the paper planning and simulation and after
receiving the tablet, developed their programs in ac-
cordance with what was planned. But when the exe-
cution did not reach the goal, they did not go back and
analyzed the planning to understand what was wrong,
to devise and implement possible new solutions. In
general, they opted for a trial-and-error-based solu-
tion strategy, instead of analyzing possible mistakes
in a planned solution to redesign a novel solution for
the problem. In the end, all the pairs succeeded in
reaching the goal with regard to proposing a correct
solution to the problem.
From the comments on the questionnaire (which
contained questions about what one liked and disliked
the most, and about suggestions from both the work-
shop and the system), we can observe that both edu-
cators and children generally liked the workshops and
did not point any negative aspect.
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Figure 9: Results of SAM with children – 1st Workshop.
Among the teachers, one suggested the inclusion
of commands to make the execution faster (e.g., com-
mands to skip squares), another suggested the diversi-
fication of commands in the system, and two teachers
complained about the size (possibly referring to the
size of the scenario on the tablet screen).
Figures 8, 9, 10, 11, 12 show the results about the
SAM and the perception of the workshops.
With regard to the teachers (Figure 8), in relation
to the dimensions of Pleasure and Arousal, all of them
experienced a positive affective response. In relation
to the Dominance, 50% presented a positive affective
response, and 50%, neutral.
With the children (Figures 9 and 10), we obtained
100% positive responses to the Pleasure dimension,
both in the first and second workshops. In the dimen-
sion of Arousal, 78% positive affective response in the
first one increasing to 93% in the second workshops.
In the Dominance dimension, we noticed the negative
affective response by 28.5% of the children in the first
workshop, reducing to 14% in the second workshop.
Regarding how they evaluate the activities and
how they evaluate the system (Figures 11 and 12),
100% evaluated as Very Good or Good.
Based on the conducted workshops, we came up
with some guidelines that may improve the imple-
CSEDU 2018 - 10th International Conference on Computer Supported Education
314
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Figure 10: Results of SAM with children – 2nd Workshop.
12
2
0
0
0
12
2
0
0
0
VERY GOOD GOOD REGU LAR BAD VERY BAD
NUMBER OF PARTICIPANTS
HOW DO THEY EVALUATE THE WORKSHOP
Works hop 1 Workshop 2
Figure 11: Workshop evaluation by children.
12
2
0
0
0
13
1
0
0
0
VERY GOOD GOOD REGU LAR BAD VERY BAD
NUMBER OF PARTICIPANTS
HOW DO THEY EVALUATE THE SYSTEM
Works hop 1 Workshop 2
Figure 12: System evaluation by children.
mentation and evaluation of this kind of activities us-
ing the propose methodology:
Record the time spent in each activity and corre-
late the observed times with the quality of the pro-
gram developed.
Observe the comments of children during their
interaction, both in the planning and simulation
phase, as well as in the programming and testing
phase.
Develop strategies to keep track of the develop-
ment of the reasoning strategies of children.
5 CONCLUSIONS
Although the subject of computational thinking has
attracted attention of researchers in the computers and
education field, especially in the last years, literature
still lacks a formal methodology to address the devel-
opment of skills associated with computational think-
ing. In this paper, we analyzed existing literature on
computational thinking and proposed a methodology
to conduct activities that may foster its development
in an educational context.
We experimented the proposed methodology with
children from 8 to 11 years old and their teachers. The
activities aimed at the development of computational
thinking skills by means of solving proposed prob-
lems using ScratchJr in a tablet. The analysis of re-
sults from these workshop shows that both educators
and children were pleased when engaging in the de-
velopment of activities following a methodology that
encourages them to reflect about what they should do
to solve a problem and about the results achieved.
For future work, we intend to evaluate the use of
this methodology in other educational scenarios, and
conduct some workshops with educators using this
methodology for planning activities. Additionally, we
also plan to develop a platform for supporting the use
of the methodology in the development of computa-
tional thinking, with the possibility of sharing activ-
ities, experiences, validations, and evaluations of the
proposed methodology.
ACKNOWLEDGEMENTS
Authors are grateful to CAPES, CNPq (grants
#308618/2014 9 and #307560/2016 3), and
FAPESP (grant #2015/16528 0) funding agency for
their support.
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