The Creative Process in the Development of Computational Thinking

in Higher Education

Tatyane S. C. da Silva

, Jeane C. B. de Melo

and Patricia Tedesco

Centro de Informática – Universidade Federal de Pernambuco,

Av. Jorn. Aníbal Fernandes, Cidade Universitária, Pernambuco, Brazil

Department of Computing, Universidade Federal Rural de Pernambuco,

Rua Dom Manuel de Medeiros, s/n - Dois Irmãos, Brazil

Keywords: Higher Education, Creative Process, Creativity, Computational Thinking, Programming Education.

Abstract: Today's society, differentiated by knowledge, is characterized by structural changes that require individuals

to act in an innovative, interdisciplinary way and linked to Computational Thinking. This skill stands out for

its relevance, included in the list of skills and competencies required of 21st-century professionals.

Computational thinking encompasses problem-solving using models, abstractions, organization and

decomposition of these elements in an algorithmic way. These elements, in turn, impose on subjects a skill

that is not widely explored in traditional teaching-learning processes: creativity. Given this panorama, this

article presents a study whose objective is to understand the relationship of the Creative Process in the

development of Computational Thinking, to assist the teaching and learning of programming. For this, a

Conceptual Model was created, relating the pillars of the Creative Process to solve problems using

programming and later applied in a class in the Digital Games course, in the Programming discipline. The

results point to the relevance of using the Conceptual Model in the cognitive process, indicating that it

positively influenced the learning of programming by students, which is reflected in the students' solutions

and reports.

1 INTRODUCTION

The Programming discipline is part of the basic

training in Computer Science courses. Its content is

focused on teaching concepts, computational models

and programming language (Bennedsen &

Caspersen, 2004).

However, it is important to emphasize that

programming education is not limited to teaching a

programming language. The process of teaching

programming should also involve problem-solving,

based on concepts such as association, evaluation,

assignment, procedure call and parameter passing

(Bennedsen & Caspersen, 2004).

The teaching of programming-related disciplines,

including their fundamental concepts and

introductory approaches, presents a great challenge

for teachers in the search for appropriate teaching

methodologies (Bennedsen & Caspersen, 2004).

https://orcid.org/0000-0002-9635-4836

https://orcid.org/0000-0002-2357-1178

https://orcid.org/0000-0001-9450-9219

The traditional teaching methodology, commonly

used in programming classes, which are usually

divided into theoretical, theoretical-practical and/or

laboratory classes, has not been satisfactory

(Bennedsen & Caspersen, 2004). These resources are

relevant for presenting the results of a process, but

they do not show the development process in itself.

Another factor to be considered in the

programming teaching-learning process is Creative

Thinking. According to Young (1985), we live in a

knowledge society, characterized by changes that

require innovative individuals. At the same time, the

importance of Computational Thinking (National

Research Council, 2013) stands out, since it is

included in the list of Skills and Competencies

required for professionals in the 21st century.

According to National Research, Computational

Thinking encompasses problem-solving using,

models, abstractions, grouping, and decomposition of

C. da Silva, T., B. de Melo, J. and Tedesco, P.

The Creative Process in the Development of Computational Thinking in Higher Education.

DOI: 10.5220/0009346502150226

In Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) - Volume 1, pages 215-226

ISBN: 978-989-758-417-6

215

these elements in an algorithmic manner. Although

cognitive processes are commonly used by computer

science professionals, formal training in this area of

knowledge is not necessarily needed since in many of

these activities there will be, at least, the use of

information technology related to computational

(algorithmic) reasoning (National Research Council,

2013).

In this perspective, Computational and Creative

Thinking is seen as cognitive tools that expand the

knowledge and skills that can be applied in obtaining

a solution to a given problem. That is computational

tools when used creatively, lead to the development

of new approaches to both old and new problems,

observing different stimuli and perspectives that may

be relevant in their solution (BBC, 2017).

Aiming to propose an approach to the problem of

applying programming concepts to solve real-world

problems using the elements of the Creative Process

and Computational Thinking, this paper presents a

research question: QP1 – Are the Creative Process

and the development of Computational Thinking

factors that influence the learning process of

Programming?

From the QP1 inquiry, it is possible to analyze if

the Creative Process assists students in learning in

programming. To answer the research question the

following hypothesis, H1 was formulated: H1: The

use of the Creative Process in the development of

Computational Thinking helps students solve

problems using programming.

The phases involved in the development of such

research are described in the present work, which is

organized as follows: Section 2 presents the concepts

of Computational Thinking. Section 3 addresses

Programming Teaching and Learning. Section 4

addresses the definition of Creativity and Creative

Process. Section 5 presents Related Works, and

Section 6 presents the Conceptual Model. Finally,

Section 7 regards the final considerations of the

paper, highlighting the contributions of the study.

2 COMPUTATIONAL THINKING

The concept of Computational Thinking (CT) was

proposed in 2006 by Jeannette Wing (National

Research Council, 2013) and is related to problem-

solving and the perception of human behavior, both

guided by definitions of the fundamentals of

Computer Science (National Research Council,

2013). The CT addresses a set of definitions, skills,

and practices of computing that can be applied both

in everyday activities and in other areas of knowledge

(National Research Council, 2013).

According to the BBC - Computational Thinking

(Gomes et. al, 2017), Computational Thinking has

four pillars that help solve complex problems:

Decomposition, Recognition, Abstraction, and

Algorithms.

Decomposition - consists of breaking down a

problem or complex system into smaller, more

manageable parts.

Pattern Recognition - characterized by looking for

similarities between problems and subproblems.

Abstraction - has the purpose of focusing only on

important information searching for the solution,

ignoring irrelevant details.

Algorithms - intended to develop a systematic

solution to the problem, or the rules to follow to solve

it.

The use of the four pillars assists in programming

and solving complex problems – which are those that,

at first sight, one does not know how to solve easily.

Finally, these simple steps or rules are used in

programming to help solve the problem in the best

way (Gomes et. al, 2017). In this research we will use

the four pillars of Computational Thinking (Gomes

et. al, 2017), corroborating with the objectives of the

current proposal.

In this research the four pillars of Computational

Thinking (Gomes et. al, 2017) will be used,

corroborating with the objectives of the current

proposal.

3 PROGRAMMING TEACHING

AND LEARNING

The literature presents a set of difficulties associated

with programming learning and teaching

(Sternberg,2003). Considering the difficulties

presented by the students, these were divided into

three categories: teaching strategies, student attitudes,

study methods, and natural programming difficulties

(Sternberg,2003). Many students are accustomed to

the memorization strategies (read, see solved

exercises), which are not enough to learn to program.

It was necessary to engage in intensive problem-

solving practice, facing the difficulties related to it

and trying to resolve them. This should be based on

generic problem-solving skills previously acquired

that students generally do not have (Sternberg,2003).

Considering this scenario, some creative

strategies can be used in programming teaching,

among which we can cite: diversifying the proposed

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tasks through methods of education, transformation,

simulation, among others; usage of Computational

Thinking to solve problems; creating a space for the

dissemination of student work; sharing personal

experiences related to the studied topic; guiding the

student to seek additional information on topics of

interest to them (BBC, 2017).

4 CREATIVITY AND THE

CREATIVE PROCESS

This section presents the definitions that underlie this

work regarding Creativity and the Creative Process.

4.1 Creativity

There are several definitions of the term creativity,

and there is no consensus as to its exact meaning.

Among the authors, this being an issue addressed

from multiple points of view, we have, for example,

Sternberg's Theory of Creativity (MacKinnon, 1962)

and MacKinnon's Theory (Tschimmel, 2010). This is

related to the fact that creativity, like intelligence, is

a complex construct, with diverse aspects, such as the

characteristics of the individual, the creative process,

items present in the creative product, or aspects of the

environment where people are inserted, which may

influence one’s creative expression (BBC, 2017).

According to Sternberg's Theory of Investment in

Creativity (MacKinnon, 1962), six interrelated

elements will be creative: intellectual skills,

knowledge, thinking styles, personality, motivation,

and appropriate environment. These multiple

perspectives of creativity are related to combinations

of aspects inherent to the individual, depending on

cognitive, emotional and environmental factors.

For MacKinnon (Tschimmel, 2010), three basic

conditions are necessary for creativity: the response

must be new or at least statistically infrequent; the

response must adapt to reality and serve to solve a

problem or achieve a recognizable goal and must

include the evaluation, design, and development of

the original insight.

For this paper, we will use the definition of

MacKinnon (Tschimmel, 2010), since it aligns with

the research objective of using creativity as a tool to

help solve problems.

4.2 Creative Process

The Creative Process is situated at the stage of

generating ideas for a solution and the creation of new

ideas and uses divergent and convergent thinking in

the analysis, synthesis and casual events that are

experienced as relevant (Zavadil, 2019). In this

process, people use their skills and develop new ones

according to the demands and type of activity. These

skills involve cognitive procedures that will allow the

restructuring of elements and the creation of new

combinations for generating an idea or solution in a

specific domain (Osborn, 2008).

In this context, the terms Creativity and Creative

Process, although sometimes used as synonyms, are

used in this study with different meanings. Creativity

is the systemic capacity manifested in new and value-

added solutions (be them ideas, products, concepts,

questions, etc.), influenced by various contextual

factors of the social and cultural environment

(Zavadil, 2019) (Osborn, 2008). This is done through

means of the Creative Process, which consists of

methods, techniques, instruments and procedural

knowledge that can facilitate the development of new

conceptions, dealing with the various factors

influencing Creativity and facilitating

communication and interaction between the

individuals (Osborn, 2008).

4.3 Creative Problem Solving (CPS)

Creative Problem Solving (CPS) was created by

Osborn. It is a methodological paradigm composed of

methods and techniques to analyze, identify and solve

problems.

Research, Discovery of Ideas and Discovery of

Solutions. This model’s strategy is to obtain a clear

and precise definition of the problem and generate

several solutions.

The problem is delimited at the Investigation

stage. According to Osborn, the definition of the

problem is fundamental to propose new questions and

possibilities.

The generation and development of ideas happen

in the Discovery of Ideas stage. The most promising

ideas are then selected and developed in the project

activity.

The Solution Discovery phase encompasses the

evaluation of the provisional ideas, the choice of the

final solution and its subsequent implementation. The

evaluation of ideas highlights critical intelligence,

analytical thinking, and convergent thinking.

5 RELATED WORK

The literature presents some approaches that use

creativity as an element to promote Computational

The Creative Process in the Development of Computational Thinking in Higher Education

217

Thinking and programming learning, however, it is

still incipient, especially if the study’s objective is

teacher training (Miller et al, 2013; et al, 2017).

The study by Shell et. al (2017) addressed the

integration of Computational Thinking and Creative

Thinking into Computer Science courses to improve

the learning and performance of higher education

students using Computational Creativity Exercises

(CCEs). This research uses Epstein's theory of

generationality (2017) to support the definition of

Creative Thinking, which divides it into four

competencies: capture, challenge, amplify, and

engage. Capturing competence refers to the ability to

recognize and note unique ideas as they occur. The

ability to challenge established thinking and behavior

patterns are related to the ability to generate new

approaches to problems. The competence to extend,

or amplify, one's knowledge beyond one's discipline

allows the innovative integration of ideas. And, lastly,

the stimulus, that can be social or environmental, can

lead to new experiences and ideas. The principles of

Computational Creativity Exercises (CCEs) are (1)

attribute balancing between Computational and

Creative Thinking and (2) mapping between

computational and creative concepts and skills, as

manifested in different disciplines. For each exercise,

the study has a set of creative objectives,

computational objectives, and collaborative problem-

solving objectives. For the set of computational

objectives, two aspects are used: PC concepts, such

as classification and logical condition, as well as

Computational Thinking skills. The Computational

Thinking skills that were used in the study were:

problem decomposition, pattern recognition,

abstraction, generalization, algorithmic design, and

evaluation. The study concluded that the integration

of computational creativity exercises based on the

creative competencies of Epstein (2017) improved

the learning of Computational Thinking in Computer

Science courses.

The study by Shell et. al (2017) points out the

need to relate the teaching of Computational and

Creative Thinking in the Computation course, to help

students learn and develop their ability to apply, in a

creative way, the knowledge of Computational

Thinking in solving problems. However, this study

does not clearly show how problem-solving is related

to the pillars of Computational Thinking.

6 CONCEPTUAL FRAMEWORK

The study was divided into a few phases and the

activities were based on the Conceptual Model. The

research is qualitative, carrying out a content analysis

of the semi-structured interviews with the students.

The Conceptual Framework was based on the pillars

of Computational Thinking and Creative Problem

Solving (CPS), to aid programming learning and

problem-solving. The model can be viewed in Figure

The Conceptual Framework is divided into three

parts: Computational Thinking, CPS and Creativity

Techniques. The first two have the purpose of

assisting in problem-solving to facilitate the learning

of programming and the Creativity Techniques have

the objective of developing Creative Thinking.

The Decomposition phase of the Computational

Thinking pillars is related to the six hats technique

(Bono, 2017), because this technique helps in

dividing the problem and observing it from different

perspectives, and can be used in the definition phase

of the CPS problem.

The Pattern Recognition stage of the

Computational Thinking pillars is correlated with the

Domite to Destroy (D2D) technique. This technique

aims to recognize the patterns to create something

new or innovative and concerns the generation phase

of the CPS, which is the selected stage for this

function.

The Abstraction phase of Computational

Thinking pillars is related to the Zoom Out creativity

technique, since this technique, as well as abstraction,

has the intent to train in an individual the ability to

observe the concepts only in a generic form while

searching for the most relevant information. Besides,

it is localized in the ideas generation phase, a moment

of convergence.

Finally, on the Algorithm pillar, this is related to

code, UML or any algorithmically representation of

the solution and is located in the Action phase of the

CPS model, since it is the stage of developing the

solution. In the following subsections, the application

of this model will be detailed in the game

programming class.

6.1 The Participants

The research includes the participation of students

from two classes: class 1, with nine students, and

class 2, with six students, from the last period of the

course of the digital games in higher education who

were taking the multiplatform programming

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discipline. Both classes have already taken the

Introduction to Programming course. The average age

of students in class 1 was 20 years old and all were

male. The average age of students in class 2 was 23

and all were male. The students were chosen because

they are in the same period and all have already seen

the same number of subjects. The object-oriented

programming classes, in C #, were given by the same

teacher, before conducting the study using the

Conceptual Model. The full transcript of the class 1

interview is on the link.

6.2 The Study

For the application of the Conceptual Framework, an

activity was carried out with a duration of 2 weeks,

with two classes per week, lasting a total of 3 hours

and 30 minutes, in Class 1. This activity intended to

study the impact of the Creative Process on the

development of Computational Thinking to assist

programming learning in the development of a game.

The game was created with Engine Unity and it

was necessary to use object-oriented programming

with the C # language. This activity involved the

whole class. At first, the students made, with the

professor’s aid, a Timberman style game – a casual

game in which a woodcutter needs to cut a tree and

not let the branches hit him. Then the students should

create a functionality different from the basic game.

Students used Creativity Techniques in

conjunction with the Computational Thinking pillars.

Before solving the proposed issue, the students

divided the problem into smaller pieces

(Decomposition), utilizing the six hats technique

(Leavy, 2014), to find the solution. They recognized

the Pattern of the basic solution through D2D and

used abstraction, noting which the most important

part of the code should be modified, as well as using

Zoom Out to create a creative solution.

The students decided that the new Timberman

game would be in line with the theme Jack and the

Beanstalk, which is about a fairy tale where the

character Jack climbs on a large magic bean tree.

Students used the concept of climbing the branches

instead of having them descend, just like in the

original game. Therefore, they changed the gameplay

and altered the game code.

Students who used the Conceptual Framework

and those who did not participate in the activity were

interviewed after its conclusion, using the Conceptual

Framework. The questions can be seen below, in

Table 1.

Table 1: Interview questions.

INTERVIEW QUESTIONS

HOW DO YOU DEFINE CREATIVITY?

DO YOU BELIEVE THAT CREATIVITY HELPS IN PROBLEM-

SOLVING? YES, NO, AND WHY?

IN YOUR OPINION, CAN CREATIVITY BE USED TO AID IN

PROGRAMMING?

DID YOU HAVE ANY DIFFICULTY IN PROGRAMMING? IF YES,

WHICH?

Figure 1: Conceptual Framework.

To analyze the students' responses to the semi-

structured interview, we used Content Analysis

(Leavy, 2014). Leavy (2014) presents Content

Analysis as a qualitative analysis technique, starting

from three processes, or phases, understood as

necessary to perform a content analysis: 1) pre-

analysis, 2) material exploration, and 3) treatment of

the results, inference, and interpretation.

The pre-analysis begins the creation of the corpus

of the research, through the organization of the

The Creative Process in the Development of Computational Thinking in Higher Education

219

material that is to be analyzed, making it operational

(Leavy, 2014).

In the material exploration, which characterizes

the second phase, corpus coding techniques are

administered, including a careful examination of the

material for the definition and set of categories. The

third step appertains to the results’ treatment, as well

as its inference and interpretation (Leavy, 2014).

Students in Classes 1 and 2 also answered

questions from the Inventory of Teaching Practices

for Creativity in Higher Education, validated by

Alencar (2004), after the conclusion of the activity

utilizing the Conceptual Model. The instrument

consists of 37 items that aim to evaluate the teaching

practices that favor the development and expression

of creative abilities in university students,

constituting a first step towards the development of

Creative Thinking in the students. The Inventory of

Teaching Practices for Creativity in Higher Education

can be viewed in Table 2.

Table 2: The Inventory of Teaching Practices for Creativity

in Higher Education.

STRONGL

DISAGREE

DISAGRE

DOUBT

AGREE

FULLY

AGREE

1. CULTIVATE

IN STUDENTS

THE TASTE FOR

DISCOVERY

AND THE

SEARCH FOR

NEW

KNOWLEDGE.

1 2 3 4 5

2. ASK

CHALLENGING

QUESTIONS

THAT

MOTIVATE

STUDENTS TO

THINK AND

REASON.

1 2 3 4 5

3. ENCOURAGE

STUDENTS TO

ANALYZE

DIFFERENT

ASPECTS OF A

PROBLEM

1 2 3 4 5

4. STIMULATES

STUDENT

INITIATIVE

1 2 3 4 5

5. ENCOURAGE

THE STUDENT

TO HAVE NEW

IDEAS RELATED

TO THE

CONTENT OF

THE

DISCIPLINE.

1 2 3 4 5

6. PROMOTES

STUDENTS'

SELF-

CONFIDENCE.

1 2 3 4 5

7. IT

STIMULATES

STUDENTS'

CURIOSITY

THROUGH THE

PROPOSED

ACTIVITIES.

1 2 3 4 5

8. ENCOURAGES

STUDENT

INDEPENDENCE

1 2 3 4 5

9. DEVELOPS

CRITICAL

ANALYSIS

SKILLS IN

STUDENTS.

1 2 3 4 5

10. IT LEADS

THE STUDENT

TO PERCEIVE

AND KNOW

DIVERGENT

POINTS OF

VIEW

ABOUT THE

SAME PROBLEM

OR SUBJECT OF

STUDY.

1 2 3 4 5

11. IT VALUES

THE STUDENTS'

ORIGINAL

IDEAS.

1 2 3 4 5

12.

ENCOURAGES

STUDENTS TO

ASK QUESTIONS

ABOUT

STUDIED.

1 2 3 4 5

13. IT IS ONLY

CONCERNED

WITH

INFORMATION

CONTENT.

1 2 3 4 5

14. CREATES AN

ENVIRONMENT

OF RESPECT

AND

ACCEPTANCE

FOR STUDENTS'

IDEAS.

1 2 3 4 5

15. ALLOW TIME

FOR STUDENTS

TO THINK AND

TO DEVELOP

NEW IDEAS.

1 2 3 4 5

16. IT GIVES

THE

STUDENTS A

CHANCE TO

DISAGREE

WITH THEIR

POINT OF

VIEW.

1 2 3 4 5

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Table 2: The Inventory of Teaching Practices for Creativity

in Higher Education (cont.).

STRONGL

DISAGREE

DISAGRE

DOUBT

AGREE

FULLY

AGREE

17. USES

EVALUATION

FORMS THAT

REQUIRE THE

STUDENT TO

ONLY

REPRODUCE

THE CONTENT

GIVEN IN

CLASS OR

CONTAINED IN

THE BOOKS /

TEXTS.

1 2 3 4 5

18. IT

PRESENTS

SEVERAL

ASPECTS OF

AN ISSUE

BEING

STUDIED.

1 2 3 4 5

19. ALWAYS

USE THE SAME

TEACHING

METHODOLOG

1 2 3 4 5

20. PROMOTE

THE DEBATE

WITH THE

ENCOURAGEM

ENT OF THE

PARTICIPATIO

N OF ALL

STUDENTS.

1 2 3 4 5

21. ASKS

QUESTIONS,

SEEKING

CONNECTIONS

WITH ISSUES

ADDRESSED.

1 2 3 4 5

22. USE

EXAMPLES TO

ILLUSTRATE

WHAT IS

BEING

ADDRESSED IN

CLASS.

1 2 3 4 5

23. IS WILLING

TO ELUCIDATE

STUDENTS'

DOUBTS.

1 2 3 4 5

24. PROVIDES

EXTENSIVE

BIBLIOGRAPH

Y ON THE

TOPICS

COVERED.

1 2 3 4 5

25. AWAKENS

STUDENTS'

INTEREST IN

THE CONTENT

TAUGHT

1 2 3 4 5

26. IS WILLING

TO SERVE

STUDENTS

OUTSIDE THE

CLASSROOM.

1 2 3 4 5

27. IT USES A

VARIETY OF

FORMS OF

EVALUATION.

1 2 3 4 5

28. IT

PRESENTS

PROBLEM

SITUATIONS

TO BE SOLVED

BY THE

STUDENTS.

1 2 3 4 5

29. IT EXPOSES

THE CONTENT

IN A DIDACTIC

WAY.

1 2 3 4 5

30. IT OFFERS

STUDENTS

LITTLE

CHOICE IN

THE WORK TO

BE DONE.

1 2 3 4 5

31. GIVE

CONSTRUCTIV

E FEEDBACK

TO STUDENTS.

1 2 3 4 5

32. PROVIDES

IMPORTANT

AND

INTERESTING

INFORMATION

REGARDING

THE CONTENT

OF THE

COURSE.

1 2 3 4 5

33. HAS

ENTHUSIASM

FOR THE

DISCIPLINE HE

TEACHES.

1 2 3 4 5

34. LISTEN

CAREFULLY

TO STUDENTS'

INTERVENTIO

NS.

1 2 3 4 5

35. IS NOT

AWARE OF

STUDENTS'

INTERESTS.

1 2 3 4 5

36. HAS

POSITIVE

EXPECTATION

S REGARDING

STUDENT

PERFORMANC

1 2 3 4 5

37. HAS A

SENSE OF

HUMOR IN

THE

CLASSROOM

1 2 3 4 5

The Creative Process in the Development of Computational Thinking in Higher Education

221

This study, which resulted in the validation of the

instrument after a factorial analysis, suggests the

following organization: Factor 1 - Incentive to New

Ideas, in which it contemplates the items I1-I10, I12,

I15, I18, I20, I21; Factor 2 - Climate for Expression

of Ideas, that includes items I11, I14, I16, I34, I35,

I37; Factor 3 - Teaching Assessment and

Methodology, which includes I13, I17, I19, I27 and

I30; and Factor 4 - Interest in Student Learning, that

addresses items I22 - I29, I31, I32, I33 and I36.

Each of the items is answered on a Likert scale

(1932) of five points, ranging from strongly disagree

to strongly agree. The instrument is complemented

with an initial page with instructions on how to

answer it properly, including biographical data of the

respondents, information on the courses to which they

are related, age and gender, allowing the description

of the students’ profile.

The Likert scale (1932) is a type of psychometric

response often used in questionnaires in the areas of

Psychology, Education and Marketing. In responding

to a questionnaire based on this scale, respondents

detail their level of agreement with a statement

(LIKERT, 1932). Based on the questionnaire’s

answers, the average value of the students' answers

was calculated based on the Weighted Arithmetic

Mean, as done in Oliveira (2005), using the following

formula:

6.3 Results

The responses of the Inventory of Teaching Practices

for Creativity in Higher Education were analyzed

from a quantitative approach. The study was based on

Descriptive Statistics, which is intended to describe

and summarize a set of data, that is, to transform the

collected data into information.

For this research, Frequency Distribution was

used, specifically the Absolute Frequency, to present

the data and its respective frequencies. For each

assertion, the frequency of the answers given by the

participants is shown, according to the Likert scale

(1932). As the survey was carried out with 8 students

from Class 1 and 9 students from Class 2, then the

total of observations for each assertive is 8 and 9,

respectively.

The closer to 5, the maximum number on the

Likert scale (1932), the higher the level of agreement

of the students about the assertions of the Inventory

of Teaching Practices for Creativity in Higher

Education.

Tables 3, 4, 5 and 6 present the average result of

factors 1, 2, 3 and 4, respectively obtained through the

students' answers on the Inventory of Teaching

Practices for Creativity in Higher Education.

Table 3: Factor 1 - Incentive to New Ideas.

ASSERTIVE CLASSES RESULTS BY ASSERTIVE

1 4,25

2 4,22

1 4,38

2 4,11

1 3,75

2 4.67

1 4,13

2 4,11

1 4,00

2 4,11

1 3,75

2 4,22

1 4,13

2 4,44

1 4,13

2 4,33

1 3,13

2 3,89

I10

1 3,50

2 3,89

I12

1 4,25

2 4,44

I15

1 4,25

2 4,22

I18

1 4,38

2 4,00

I20

1 4,25

2 3,78

assertive

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In Table 3, the average result of the answers

indicates that Factor 1, called Incentive to New Ideas,

related to the stimulation of cognitive abilities and

affective characteristics was evaluated positively by

the students of the two groups.

Table 4: Factor 2 - Climate for Idea Expression.

ASSERTIVE CLASSES RESULTS BY ASSERTIVE

I11

1 4,88

2 4,33

I14

1 4,25

2 4,33

I16

1 3,88

2 4,22

I34

1 4,38

2 4,56

I35

1 1,75

2 2,00

I37

1 4,63

2 4,56

In Table 4 the average result of the answers

indicates that Factor 2, called Climate for Expression

of Ideas, which refers to the posture and acceptance

by the teacher regarding the ideas presented by the

students, obtained agreement indexes. The I35

inquiry is emphasized, is that even with a score of less

than 5 it is positive, for the question wants to

understand if the teacher "is not attentive to the

interests of the students", and the students responded

by disagreeing with this statement.

Table 5 shows the average result of Factor 3

responses, called Teaching Assessment and

Methodology, regarding teaching practices favorable

to the development of creative expression, showing

that even though the indexes are low in Class 1, that

used the Conceptual Model in the activities, they are

positive because they are related to the disagreement

that the teaching is only informative and that there is

only the reproduction without reflection on the

content.

Table 5: Factor 3 - Teaching Assessment and Methodology.

ASSERTIVE CLASSES RESULTS BY ASSERTIVE

I13

1 2,13

2 3,33

I17

1 2,25

2 3,33

I19

1 1,38

2 3,78

I27

1 4,00

2 3,78

I30

1 1,75

2 3,44

Table 6: Factor 4 - Interest in Student Learning.

ASSERTIVE CLASSES RESULTS BY ASSERTIVE

I22

1 4,25

2 4,44

I23

1 4,63

2 4,86

I24

1 4,00

2 3,89

I25

1 4,63

2 3,78

I26

1 3,88

2 4,00

I28

1 3,75

2 4,56

I29

1 4,00

2 4,44

I31

1 4,38

2 4,44

I32

1 4,38

2 4,67

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223

Table 6: Factor 4 - Interest in Student Learning (cont.).

ASSERTIVE CLASSES RESULTS BY ASSERTIVE

I33

1 4,38

2 4,78

I36

1 4,38

2 4,22

In Table 6 the average result of the answers is

related to the Factor 4, denominated Interest in

Student Learning, related to strategies and

educational resources that motivate the student to

learn creatively, presented indicators that prove that

the students agree with the affirmations in the

questionnaire.

Additionally, the Content Analysis was carried

out based on the transcripts of the semi-structured

interviews. Table 7 presents an overview of the

categories created from the students' responses, as can

be seen, below. The categories were created using the

MAXQDA software. The initial categories went

through a synthesis where the authors arrived in the

final categories. This modification is part of the third

stage of content analysis, as in this phase, the results

are treated and the coded data is synthesized, seeking

information for analysis, which will result in

inferential interpretations. The full transcription of

the interviews is in the appendix.

Table 7: Categories.

INITIAL CATEGORY FINAL CATEGORY

CREATION

GENERATE NEW IDEAS

RELATING EXISTING

KNOWLEDGE

INNOVATION

DIVERGENT THINKING

SYNTAX

THEORETICAL

PROGRAMMING CONCEPTS

SEMANTICS

RELATING THEORETICAL

CONCEPTS WITH

PRACTICE

RELATING THEORETICAL

CONCEPTS WITH PRACTICE

PROGRAMMING LOGIC

CREATIVE PROCESS

CREATIVE PRODUCT

CREATIVITY DOESN’T

APPLY TO PROGRAMMING

CREATIVITY DOESN’T APPLY

TO PROGRAMMING

One issue to remark is the Creative Process

category, created in Content Analysis, which

emerged from the question "In your opinion, can

creativity be used to aid in programming." This

category arose only from Class 1, which was applied

to the Conceptual Framework.

Besides, the category "Creativity doesn’t apply to

programming" was identified only in Class 2, to

which the Conceptual Framework was not applied in

a classroom activity

6.4 Discussion

In this session, we presented the Conceptual Model

and its use in a class undertaking the course of Digital

Games in a Multiplatform Programming discipline,

as well as the results achieved with the study that

evaluated the model in an activity taken place in a

learning scenario.

The study was taken forth by a research question

that sought to verify that the Creative Process is,

indeed, a factor that influences the development of

Computational Thinking and Programming teaching

and learning processes.

Regarding the performed activity using the

Conceptual Model, there was greater involvement of

the students in the solution of the problem, as well as

the resolution itself was completed using elements of

the Unity IEnumerator, which was used in the

solution and has the function of stopping a process

and then resume it. This functionality was not used in

the standard solution presented by the teacher.

Regarding the students' responses in the semi-

structured interview, the students in class 1 - those in

which the Framework was used - when answered

about the relationship between programming and

creativity, had the perception that the creative process

can be inserted in the resolution of problems in use of

programming and that not only creative products are

the result of the relationship between programming

and creativity. As can be seen in the students' speech:

Student 5:

Yes, mainly because of the programming logic.

Why would she, a person like me, for example,

that I don't know how to program properly, but I

have a good programming logic, this is more

creativity and creativity helps you develop a

programming logic, so if a person who knows how

to program and do not have a good creativity and

he is training his creativity naturally he creates a

better programming logic that already helps in

both cases. (Student 5).

This may be an indication that students, by using

the Conceptual Framework in an activity to solve a

problem, have realized that the Creative Process can

influence and assist in the solution of a given

problem.

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The responses of students in Class 1 show that

creativity helps in the development of Computational

Thinking since students report on their answers that

creativity does indeed aid in programming logic and

problem-solving, and we can infer from the context

of the answers that this definition is related to

Computational Thinking.

The students in Class 2 had different answers,

stating that creativity is related to programming only

to a certain extent. Following are the statements of

Student 5:

In programming, creativity will have to be filtered

well in fact, because depending on what the

person, like, ends up thinking it often becomes

very difficult for the level of the person doing it or

if they are in a moment that they are not you can

adapt the programming, so it has to be well

filtered even in this part of creativity. (Student 5).

Regarding the results of the responses of the

Inventory of Teaching Practices for Creativity in

Higher Education, the factor that had a considerable

difference between Class 1 and Class 2 was Factor 3

entitled Teaching Assessment and Methodology,

regarding favorable teaching practices to the

development of creative expression.

This may be an indicator of the activities that were

performed using the Conceptual Model, for in Class

1 the interventions were not only theoretical and the

practices in the laboratory made use of the creative

techniques that are present in the creative process.

Regarding the problems faced by students in the

process of programming learning, the students stated,

for the most part, that they have difficulty using

knowledge in solving problems. These answers

converge with the research question.

7 CONCLUSION

Nowadays, society has increased the degree of

requirement regarding the creativity used to solve

increasingly complex problems. This fact generates

demand for studies on how to stimulate creativity in

education, especially in teachers’ education (BBC,

2017). The skills and knowledge required today are

extensive and include Computational Thinking as one

of its key pieces in this context. Computational

Thinking enables students to define, analyze and

solve complex problems by the use of models and

concepts derived from Computer Science, using the

technological resources, increasingly more present

and accessible, to obtain more efficient solutions

(National Research Council, 2013).

The current research is aligned with the context

presented, proposing an approach in which the

Creative Process is used for the development of

Computational Thinking through the resolution of

programming problems.

The Conceptual Framework was applied in a

higher education class and was later evaluated using

Content Analysis to investigate students' perceptions

about the relationship between Creativity as a tool to

solve problems in programming and through the

resolution of the proposed activity. The study

presented evidence that there were contributions with

the expansion of creativity, since the results of the

Content Analysis point in this direction. In this

perspective, the educational environment is relevant

to the development of creativity, especially in the

teacher's actions, seeking to introduce such an

element in its practices and leading them to use

innovative methods to engage students in becoming

more interested in the projects’ contents. This

approach promotes the active participation of the

students in the development of creative and efficient

solutions, while also promoting the development of

Computational Thinking, confirming the hypothesis

of this study.

Finally, we realize that the students of the class to

which the Conceptual Framework was applied

recognized that the teacher adopts creative practices

in the classroom. As discussed in this paper, the

expansion of creativity presents itself as part of the

skills and competencies expected for individuals in

our society. The methodology here presented

corroborates with the systematization of this process,

presenting techniques to promote the development of

Creative Thought through the Creative Process, and,

consequently, to favor Computational Thinking,

essential elements in programming education.

7.1 Paper Contribution

Considering the perspective of the use of the Creative

Process in the development of Computational

Thinking to aid programming teaching and learning,

the research contributed to problem-solving through

programming. The following are the contributions: i)

Creation and Evaluation of a Conceptual Model for

the development of Computational Thinking using

Creative Process to aid in the teaching and learning of

programming; ii) Process-based and Creative

Thinking helped to solve problems using

programming.

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225

7.2 Limitations and Future Works

This research’s limitations of will be presented as

follows: i) the choice of the students who participated

in the research was not randomized; ii) the Creative

Process was not introduced at the beginning of the

discipline, limiting itself to only one activity; iii) the

interview and the questionnaire were performed only

once. Therefore, it is important to create other forms

of analysis that are used throughout the teaching and

learning process. Despite such limitations, the

research has shown promise. As a future work, we

intend to use the Framework in programming

disciplines that are not related to game development.

Analyze the profile of students before and after using

the Framework. Do activities based on the

Framework with more classes and assess student

learning throughout the intervention, using

Framework.

ACKNOWLEDGEMENTS

The authors would like to thank the National Council

for Scientific and Technological Development

(CNPq) for funding this research.

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APPENDIX

The full transcript of the class 1 interview is on the

link. https://drive.google.com/file/d/1wva4--

GK31rPTY8-tjNjM615T6nngh2e/view?usp=sharing

The full transcript of the class 2 interview is on the

link. https://drive.google.com/drive/folders/1oSdc-

xR6J3fFZ23yPLSXc8ceH-duIim_?usp=sharing .

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