Polemics about Computational Thinking: Digital Competence in

Digital Zeitgeist – Continued Search for Answers

Lúcia Helena Martins-Pacheco

, Christiane Annelise Gresse von Wangenheim

and

Nathalia da Cruz Alves

Department of Informatics and Statistics, Federal University of Santa Catarina, Campus Universitário s/n, Trindade,

Florianópolis, Brazil

Keywords: Digital Zeitgeist, Computational Thinking, ICT Competences, K-12 Education.

Abstract: Human society is immersed in digital zeitgeist and information, and communications technology competences

became fundamental for each citizen around the world in order to participate in the great benefits that this

technological development promotes. In this zeitgeist, several questions appear related to the educational

context because the way to deal with information, knowledge, and communications has changed drastically.

For that reason, several proposals emerged to develop additional competences in youths. Among these

possibilities, computational thinking – CT - arose as an approach to encourage ICT competence. However,

the initial proposal appeared in a simple viewpoint article; that was just an opinion without any reference.

Surprisingly, such an article reverberated around the world, and several proposals appeared trying to define

“what is computational thinking?”. Parallel to this, some critics showed controversial aspects of CT,

especially based on computer science (CS) educational, historical trajectory. But, many solid approaches of

CT based on robust researches became popular, and several educational practices were successful. Thus, we

analyze some criticism and show other points of view, aiming to clarify some questions and to give some

answers. We believe that CT approaches are valuable inside of myriads of possibilities to promote ICT

competences. Polemics and controversies used to make advances in each field, but fruitful initiatives must be

acknowledged. K-12 educational system could not wait until there is a proper and unique consensus between

researchers to start to teach ICT competences to our youths.

1 INTRODUCTION

The last decade of the 20

century was featured by a

great impact of information and communications

technology (ICT), especially the popularization of the

internet, massive dissemination of digital devices,

and globalization. This time and also the beginning of

the 21

century was named as digital convergence

(Iosifidis, 2002), information society (Webster,

2007), knowledge society (Delanty, 2003), and digital

zeitgeist

(Baptista and Bertolli Fo., 2012). This

transformation in global society communications

calls the attention of several international

organizations (Delors, (1996); Gordon et al. (2009);

https://orcid.org/0000-0003-3552-4421

https://orcid.org/0000-0002-6566-1606

https://orcid.org/0000-0002-3523-9199

The general intellectual, the moral, and cultural climate of an era (https://www.merriam-webster.com/dictionary/zeitgeist)

and https://www.psd.gov.sg/challenge/ideas/deep-dive/digital-zeitgeist

P21 (2015), Binkley et al. (2011)) concerned with the

future of education and workforce to attend economic

needs. In this global context, at the end of the 20

century and the beginning of the 21st century, some

studies identified that ICT literacy is an essential skill

for youth development. We believe that this zeitgeist

was very definitive to the massive resonance of

Wing´s Computation Thinking – CT – ideas (Wing,

2006).

According to Jeannette Wing (Wing, 2006),

computational thinking is a fundamental skill for

everyone, not just for computer scientists. To reading,

writing, and arithmetic, we should add computational

thinking to every child's analytical ability (p.33). And

she added: Computational thinking involves solving

Martins-Pacheco, L., von Wangenheim, C. and Alves, N.

Polemics about Computational Thinking: Digital Competence in Digital Zeitgeist – Continued Search for Answers.

DOI: 10.5220/0009797104990506

In Proceedings of the 12th International Conference on Computer Supported Education (CSEDU 2020) - Volume 2, pages 499-506

ISBN: 978-989-758-417-6

499

problems, designing systems, and understanding

human behavior, by drawing on the concepts

fundamental to computer science. Computational

thinking includes a range of mental tools that reflect

the breadth of the field of computer science (p.33).

These ideas have profoundly reverberated in K-12

educational communities around the world. But, if we

look at her article, trying to comprehend what her

intention was at that time, several issues call our

attention. A question is: why an article in a section

Viewpoint – ACM, march, 2006, with only four pages

and no references got 5892 citations (Scholar Google

in 02.24.2020)? Why does just a viewpoint of a

researcher achieve such an impact in K-12 related

groups and researchers? This simple article

significantly elicits several studies trying to define,

specify, and to implement CT ideas in educational

environments. In Parallel, another movement, not so

strong, criticizing her ideas came alongside. Critics

used to question her idea foundations, especially

around computer science (CS) educational history. In

this context, in this present article, we show our

viewpoint about this scenario, trying to clarify that

nowadays, several solid research and experiments

deepened the initial simple ideas by Wing,

constituting a substantial corpus of knowledge. We

believe that when we presently talk about CT, the

question is: what approach are you talking about?

Along with this present article, we bring back some

discussion to explain our vision of this situation.

2 MAIN POLEMICS ABOUT CT

Polemics, divergences, criticisms, and emphatic

argumentations are common in scientific fields, and

such "social activism" is crucial for the development

of science in every field. Thomas Kuhn (1962), a

great American philosopher of science, considered

that such processes make scientific advances and the

appearance of new paradigms possible. And in CS, it

is not different, for example, structured programming

versus object-oriented programming, which high-

level language should be introduced to a beginner:

Java? C++? Phyton?; which computer architecture

must be taught – RISC or CISC?; free software or

commercial software in educational practices?; and

so on. These discussions are beneficial and

sometimes do not reach a consensus. Each choice that

someone makes, consequently has implicit

compromises in terms of limitatios and possibilities.

So, we should ponder the benefits and difficulties of

each decision considering the situations and material

resources that are available. To listen to different

opinion and viewpoints allow us to see a broader

vision of the involved scenarios. And it is no different

when we talk about CT.

To analyze the author's criticisms, we consider an

exploratory approach through a qualitative method.

Among qualitative methods, Lenberg et al. (2017)

suggest three qualitative methods: interpretative

phenomenological analysis, narrative analysis, and

discourse analysis. To understand the criticism about

CT ideas, we chose discourse analysis because it

clarifies the essence of the problem and the

underlying assumptions that enable its existence

(Lenberg et al., 2017). Sometimes it reveals implicit

and unacknowledges aspects, and it can be used to

any type of text. Qualitative methods are interesting

to clarify complex issues that involve behaviors,

emotions, values, hidden social factors as bias,

prejudice, and social norms. So that, based on

documents produces by critics about CT approaches,

we try to analyze their arguments through reflexivity.

Reflexivity involves thinking about how our thinking

came to be and how pre-existing understanding is

constantly revised in the light of new insights (p.14)

(Lenberg et al., 2017).

To identify papers with arguments against CT

approaches, we define the followed strategy: in the

beginning, we took Peter Denning's paper titles

(Denning (2009) and Denning (2017)) as a search

string in Scholar Google. Denning is an

acknowledged critic of CT. After the search was

performed, we opened the citations of the two

articles. At first, we analyze their title and exclude the

ones that do not express any kind of criticisms or

doubts about CT. Next, we read the abstract (if it

exists) and exclude those who do not have strong

arguments against CT. From the selected ones, we

unfolded the references to find others. We do not

intend to exhaust this subject, but just to gather some

more usual opinions against CT. Our initial

hypothesis is that critics did not consider several

successful initiatives that use the CT approach in

education, as such we found before (Martins-Pacheco

et al., 2019).

Table 1 shows a summary of the main critiques.

We selected 11 references with strong arguments

against the CT approach. Then, in the following

paragraphs, we expose some of the main criticisms.

We are considering the critiques of Denning (2009),

(2010), (2017), (2017a); Tedre and Denning (2016),

Hemmendiger (2010), Armoni (2016), Corradini et

al. (2017), Yaşar (2018), Guzdial et al. (2019), and

Nardelli (2019).

CSEDU 2020 - 12th International Conference on Computer Supported Education

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Table 1: Main references with arguments against CT approaches.

REFERENCE AND ARGUMENTS

(

some ori

inal citations

)

DENNING (2009)

–

Viewpoints (ACM)

–

3 pages

–

9 refs.

. If we are not careful, our fascination with “computational thinking” may lead us back into the trap we are

trying to escape. (p.28)

. I am concerned that the computational thinking movement reinforces a narrow view of the field and will not

sell well with the other sciences or with the people we want to attract. (p.28)

. CT movement ignores the venerable history of computational thinking in computer science and in all the

sciences. (p.29)

. Alone, computational thinking seems like an inadequate characterization of computer science. (p.30)

. CT seen as a repackaging—a change of appearance but not of substance. Do we really want to replace that

older notion with “CS = computational thinking”? (p. 30)

DENNING

(

2010

)

–

enin

Statement Conference

(

ACM

)

–

32 refs.

. The term “computational thinking” has recently become popular (Wing, 2006), after hibernating many years in

the jargon of our field. We are discovering that neither we in the field nor our friends outside agree on what this

term means. Future education and research

olicies de

end on the answer. We need a better answe

)

DENNING

(

2017

)

–

View

oints

(

ACM

)

–

37 refs.

. Definitions of CT made fuzzy and overreaching claims. (p.34)

. Unsubstantiated claims undermine the effort by overselling computer science, raising expectations that cannot

be met, and leaving teachers in the awkward position of not knowing exactly what they are supposed to teach or

how to assess whether they are successful. (p.34)

. The boldest claim of all is that CT enhances general cognitive skills that will transfer to other domains where

they will manifest as superior problem-solving skills. (p.38)

. CT primarily benefits people who design computations and that the claims of benefit to non-designers are not

ubstantiated.

.38

)

DENNING

(

2017A

)

–

American Scientist

–

12 refs.

. They launched a political movement to secure funding for computational science. (p.14)

. It quickly opens the door to the false belief that step-by-step procedures followed by human beings are

necessarily algorithms. (p.15)

. Fuzzy definitions have made it difficult for educators to know what they are supposed to teach and how to

assess whether students have learned it.

. The word “thinking” is not what we are really interested in—we want the ability to design computations. (…)

computational design is a more accurate term. (p.15)

TEDRE AND DENNING, (2016)

–

Conference

–

10 pages

–

80 refs.

. Seven threats: lack of ambition, dogmatism, knowing versus doing, exaggerated claims, narrow views of

computing, overemphasis on formulation, and lost sight of computational models. (p.120)

. Risk exaggerated claims of applicability of CT. (p.126)

. Ignoring the history and the work of the field's pioneers diminishes the computational thinking movement rather

than stren

thenin

it.

.127

)

HEMMENDINGER

(

2010

)

–

Critical Pers

ective

(

ACM Inroads

)

–

11 refs.

. The original components of CT (Wing, 2006) are not exclusive of it.

. All knowledge domains use problem-solving as strategies, for example, heuristics, decomposition, recursively,

and modeling, are common practices to reformulating complex problems.

. It is not reasonable to decree to think like a computer scientist for people of other disciplines because each one

has a

er wa

of thinkin

. Thinkin

well is not the

rovince of an

one disci

line.

)

ARMONI (2016)

–

Opinion (ACM Inroads)

–

4 pages

–

11 refs.

. CS in K-12 education has undergone two different processes: rationalized extraction, stemming from a

meaningful view of CS. (p.24)

. It depicts more of a reduced version of CS, just a pale image of it, deemphasizing the challenges and the

thinking patterns. (p.24)

. The hi-tech industry, bypasses college and university CS education, and goes directly into K–12 education.

(p.27)

. Block-based educational environments use the term ‘coding’ instead of ‘programming’ or ‘solving;’ and

promise quick learning. (p.27)

. CT will mostly be in the hands of elementary school teachers, who are not knowledgeable in this field, we will

promote a false public image of CS, far from the problem-solving discipline that it actually it is. (…) we will

delete 30 years from the maturity of CS and its image, back to its early days, and ten from the age of CT,

eliminating it altogether (p.27).

. CS is broader than

rammin

, and

rammin

is broader than codin

Polemics about Computational Thinking: Digital Competence in Digital Zeitgeist – Continued Search for Answers

501

Table 1: Main references with arguments against CT approaches (cont.).

CORRADINI ET AL.

(

2017

)

–

Conference

–

efs.

. CT term has a lack of a widely accepted definition - has become a “buzzword.” We are convinced this approach

is wrong and misleading: in the long run it will do more harm than benefit to informatics. (p.136)

. In schools they do not teach “linguistic thinking” or “mathematical thinking,” with specific “body of knowledge”

or “assessment methods.” (p.136)

. to think like a computer scientist is required since informatics is the science underlying the digital technology

pervading all aspects of contemporary society (p.136).

. In order to teach CT or informatics subjects, the teachers’ conception concerning this issue is essential. They

found that the vast majority of Italian primary school teachers has not a sound and complete conception about CT.

.143

)

YASAR

(

2018

)

–

View

oints

(

ACM

)

–

34 refs.

. Some of the remaining trouble spots include definition, methods of measurement, cognitive aspects, and universal

value of CT. (p.33)

. He proposes an interdisciplinary perspective to address both cognitive and curricular aspects of CT by merging

CS education research with concepts from epistemology, cognitive and neurosciences. (p.34)

. CT educational approaches should put more emphasis on modeling and simulation (M&S).

GUZDIAL ET AL. (2019)

–

Viewpoints (ACM)

–

ages

–

5 refs.

. CT movement puts the onus on the student and on the education system the onus should be put back on the

computer scientists and other computationalists. (p.28)

If we want better thinking and problem-solving. to improve the computing and use that to change our teaching.

(p.28)

NARDELLI (2019)

–

Viewpoints (ACM)

–

4 pages

–

21 refs.

. We probably need the expression as an instrument, as a shorthand reference to a well-structured concept, but it

might be dangerous to insist too much on it and to try to characterize it (…) precisely. (p.32)

. what is important is stressing the educational value of informatics for all students. (p.32)

. Considering CT as something new and different is misleading: in the long run it will do more harm than benefit

to informatics. (p.33)

. We should discuss what to teach and how to evaluate competences regarding informatics in

primary/middle/secondary schools, and forget about teaching and evaluating competences in CT. (p.33)

. CT is not a kind of thinking better than others, just that it offers a complementary and useful conceptual paradigm

to describe realit

(pp

.33-4

)

We found seven papers that are the point of view

or opinions of just one author. In the gathered papers,

the amount of references varies between five to 80.

Denning (2009), (2010), (2017), (2017a); Tedre and

Denning (2016), Hemmendiger (2010), and Armoni

(2016) show worries about CS educational legacy

and also CS reputation in the K-12 context. They

consider that CT diminishes CS to programming or

coding. Many of them consider that CT claims are

exaggerated, raising expectations that cannot be met

(Denning, 2017) and decreasing other knowledge

domains. Besides, some of them affirm that no

evidence of developing CT skills allows them to

transfer them to other knowledge domain skills.

Most of the authors argue that CT conception

based on Wings (2006) is vague and a repackage of

older ideas that belonged to CS educational context.

Corradini et al. (2017) and Nardelli (2019) consider

that informatics is a more adequate term to use

instead of CT.

It is important to highlight that some of these

critics, despite some disagreements about CT as

proposed by Wing (2006), show their definition of

CT. For example, Nardelli (2019) affirms: forget

about teaching and evaluating competences in CT.

But, he shows his definition: "Computational

thinking is the thought processes involved in

modeling a situation and specifying the ways an

information-processing agent can effectively operate

within it to reach an externally specified (set of)

goal(s)." (p. 34).

Besides the before-mentioned authors, the study

accomplished by Cansu and Cansu (2019) aimed to

define the concept of CT. They performed an

analysis of some criticisms and contemporary related

studies concerning CT in K-12. According to them,

Denning (2009) and Hemmendinger (2011) showed

their thesis that original definition (Wing, 2006) of

computational thinking could give the impression

that computational thinking is only relevant to the

field of computer science and is largely inapplicable

to everyday situations in would-be computational

thinking learners (Cansu and Cansu (2019), p. 6).

Cansu and Cansu (2019) examined such criticism

and deducted that in ascribing undeserved

importance to certain fields – whether they are

CSEDU 2020 - 12th International Conference on Computer Supported Education

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deemed coding, computer science, or computational

thinking – would be inappropriate (p.9). For them,

many types of research hold CT as a potential

method of transforming education, as long as they

also hold the criticisms applied to the field in equal

regard (p.9). According to Cansu and Cansu (2019),

it is essential to ponder that an important sub-field of

CS is programming, and while primarily conducted

to educate learners in the best practices of computer

programming, one of its goals is being conducive to

the creation of high-quality computer programs.

(p.6).

3 ISSUES ABOUT CT CRITIQUES

IN DIGITAL ZEITGEIST

When we see these critiques and observe what

happened from 2006 until now (2020), several

contradictions and advances emerge in researches

that are unconsidered in the discussion by the critics.

Then we return to our initial questions: why does an

article in a section Viewpoint – ACM, march, 2006,

with only four pages, and no references get 5892

citations? Why just a viewpoint of a researcher

achieves such an impact in K-12 related groups and

researchers? Why have people been looking forward

to an answer to "what is computational thinking?"

Why even hard critics also try to define it?

Our understanding of such phenomenon is as

follows. We dare to hypothesize some possible

answers. Hu (2011) said: Often, fruitful discussions

can be more valuable than finding definitive answers

(p. 223). In philosophy, many times, to have a good

question is more useful than giving precise answers.

When we have open questions or an ill-defined

problem about a crucial issue, which is very common

in social sciences, we open several possibilities to

create cognitive dynamism to find good responses for

such a conundrum. It is what is called in the Gestalt

the "closure principle" (Todorovic, 2008).

Considering the digital zeitgeist, there is a strong

appeal of several international organizations since the

end of the 20

century, which had acknowledged that

digital and ICT competence would be as essential to

citizens in the 21

century (Pischetola, 2019) as

reading and writing. The idea of the “information

society” and “knowledge society” become a reality

due to the internet, popularization of digital devices,

and, lately, especially due to the "omnipresence" of

https://www.realclearscience.com/articles/2019/07/02/

your_mobile_phone_vs_apollo_11s_guidance_computer

_111026.html - accessed in 02.24.2020

the smartphones. Digital inclusion has to be achieved.

This idea is aligned with public governmental

policies, democratic practices, and also with

commercial interests. Educational systems have been

concerned about how to teach and how to learn in a

digital age (Bates, 2016).

Armoni (2016), concerned with a false image of

CS, as mentioned before, said: teaching CT will

mostly be in the hands of elementary school teachers,

who are not knowledgeable in this field (p.27). In this

sense, Wing´s article probably called the attention of

the K-12 public because the language that she used

was sufficiently accessible for reaching people

beyond the CS expert community. Wing expressed,

maybe, some aspects in an exaggerated way, but in

fact, it motivated people to believe that computational

thinking is important for everyone. It was a strong

generalization, as we are used to doing when we are

just talking, but it deeply resounds in the educational

system. For everyone, we could interpret that it does

not means that it has to be compulsory but a

possibility available to promote digital inclusion.

The long history of computer science comes

alongside digital technology advances in the

availability of electronic devices and connectivity.

For example, a smartphone, today present in the hand

of millions of people around the world in everyday

life, has about one million times more memory

capacity than NASA's Apollo 11 guidance computer

in 1972

Thus, since the beginning of CS, a lot of things in

the digital age change drastically in terms of

availability for every people. There are two questions

that critics of CT should be concerned about to certify

the reputation of CS: What must be kept? What must

be changed? They frequently return to Wing´s

primordial article, but, in the interim, many other

proposals to define, implement, assess CT in schools

have been done, and they ignore them. For example,

Kalelioglu et al. (2016), Martins-Pacheco et al.

(2019), Zhang and Nouri (2019) and Moreno-León et

al. (2019) did literature reviews, and they found

several advances in terms of educational practices

based on one of the several approaches for CT and

also a myriad of different solid definitions. Recently,

Moreno-León et al. (2019) found in their network of

textual analysis that neither programming nor coding

emerges among the most influential words of the main

CT definitions (p.32). In this sense, the concerns of

the critics are that CT approaches lead to reducing CS

to programming or coding, which does not seem real.

Polemics about Computational Thinking: Digital Competence in Digital Zeitgeist – Continued Search for Answers

503

Serious researchers that use the CT term

frequently cite Wing (2006) just as a historical view,

but they choose an approach better defined as ISTE

and CSTA (2011) (2016), Brennan, and Resnick

(2012), or other. When someone is talking about CT,

the question is, "what CT approach are you

considering?". Wing´s article is just an initial idea. A

lot of other researches constructed frameworks,

defining and specifying details of how to make CT in

educational practices feasible in K-12. Some critics

try to frame CT into CS, and they limit the

possibilities and exclude the reality of the digital age

that encompass many non-major people much beyond

the CS community experts. Some authors (e.g.,

Mühling et al., 2015) have a proposal for CS

education in K-12 and do not use CT approaches

since it is just another possibility. Some critics claim

to change the term CT to computational design,

modeling, and simulation, informatics, or modeling

of a dynamic system. Probably these terms are better

adjusted to the CS or engineering community, but will

non-specialized people understand them?

Other aspects that critics comment on are about

vagueness and ambiguous definitions or that some

concepts or aspects do not belong exclusively to CT.

But, these characteristics used to appear in CS and

other areas of knowledge. For example, problem-

solving is a very general concept that belongs to each

field of knowledge and also belongs to the every day

individual/group life. Decomposition is part of the

cartesian method

proposed in the 17th century. This

old method is important in a lot of scientific fields.

Another concept is the 'algorithm' that seems

exclusive of CS. Nonetheless, according to the

Merriam-Webster dictionary

: It was formed from

algorism "the system of Arabic numerals," a word

that goes back to Middle English and ultimately stems

from the name of a 9th-century Persian

mathematician, abu-Jaʽfar Mohammed ibn-Mūsa al-

Khuwārizmi, who did important work in the fields of

algebra and numeric systems.

So, the term 'algorithm' has hundreds of years of

age, and it was taken to CS from mathematics. Even

the word computation

had first known use in the 15th

century, meaning the act or action of calculation. That

sometimes is pointed out the historical use of the term

CT. Some authors (for example, Moreno-Leon et al.

(2019) and Denning (2017) state that Papert (1980),

is the first one to use the term computational thinking.

After that, it seems that only Wing (2006) took the

use of this term. But, we had searched in Scholar

Google (02.23.2020). In the period between 1990 and

https://plato.stanford.edu/entries/descartes-epistemology/

https://www.merriam-webster.com/dictionary/algorithm

2005 articles that use CT in the title, we found eight

occurrences. Therefore the term CT was used in other

scientific and technical fields without associated with

CS formal concept or definition.

Concerning concepts, definitions, semantics, and

meaning of words or terms, they are human cognitive

and historical constructs, as CT is. The meaning of

words is dynamic and changes, or it gets broader

along with human history. The comprehension of

Otte and Barros (2016) about concepts and definitions

is: definitions are formulated to draw conclusions and

to solve technical problems. (…) Concepts, in

contrast, are like continua relations and visions of

possibilities. For them, conceptual meanings are

much more ambiguous and infinitely more versatile

than tools (p.159). Concepts and definitions are

developed through interactions among individuals

and changes in the environment, along with the

history.

Bringing these ideas back to our reflections, the

initial concept of CT proposed by Wing (2006) is

ambiguous, versatile, and also very ambitious.

However, as it was mentioned before, in subsequent

years, several serious researchers formulated and

reformulated CT definitions, even the critics. It was

done to solve technical (or educational) problems

aiming to operationalize scholar practices along with

all stages of K-12. This process has created a

substantial corpus of knowledge, and it also allowed

different approaches. Nevertheless, it is under

development, and there are several challenges to

overcome related to pedagogy and childhood

development issues, teacher formation, material

resources for schools, etc. As a result, there is an

important contribution of CT approaches to provide

ICT competence in the digital zeitgeist.

Concerning knowledge transfer from a different

domain, recently, Scherer et al. (2019) found that

learning how to program a computer improves

cognitive skills even beyond programming (p.764).

So, it put in check some critiques and promote new

possibilities to teach and learning CT.

It is out of the scope of this present work to make

an in-depth review of CT definition evolvement. But,

in a recent study, Zhang and Nouri (2019) have done

a systematic review related to Scratch, and also

Moreno-León et al. (2019) made an in-depth general

review of CT concepts. Moreno-León et al. (2019)

performed extensive textual analysis and collected

new CT definitions, that is: The ability to formulate

and represent problems to solve them by making use

of tools, concepts, and practices from the computer

https://www.merriam-webster.com/dictionary/computati

on #h1

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science discipline, such as abstraction,

decomposition, or the use of simulations. (Moreno-

León et al., (2019), p. 33)

When we look back, it is possible to realize that

the CT concept meaningfully evolved in comparison

to the initial vision of Wing (2006). So, CT

approaches are becoming more mature and certainly

can make part of the multitude of possibilities to teach

and to learn ICT skills.

4 FINAL CONSIDERATIONS

We presented the main controversies concerning CT,

and we attempted to present other perspectives

around these issues. In the present digital zeitgeist, it

is necessary to cross the frontiers between CS and CT

and include them inside the "computers and society"

field. This study could be deepened in the future to

understand critics' believes and attitudes, the kind of

references that they take into account aiming to

delimited their epistemological foundations.

CT can be considered as a social practice. Rather

than seeking conceptual unity in computational

thinking, we highlighted the different ontological

commitments that cognitive, situated and critical

framings bring to computational thinking and

illustrated how these contextualize research with

programming tools, design of applications, and

classroom implementations (p.51) (Kafai et al.,

2020). For them, multiple framings and

interdisciplinary perspectives for CT are desirable.

We agree with them because, especially when we

have K-12 as a scenario concerning pedagogy,

educational/ developmental/ cognitive psychology,

public policies, material resources, and so on, the

diversity of possibilities must be taken into account.

There is a great variety of approaches and methods,

and, in general, governments define some common

rules, and schools and teachers choose what is more

adequate to the context where they are inserted.

Our exploratory analysis allowed us to confirm

the initial hypothesis that several successful

initiatives that use the CT approach in education were

not taken into account by critics. Consequently, their

opinions seem partial and attached to the context of

experts in CS education or traditional practices.

To promote digital competences in K-12 is a

broader space than just the CS field. Probably, the

rules and more rigid definitions are essential for CS

experts, but in K-12, the way to cope with teaching

and learning has to be more flexible. We do not

https://dl.acm.org/newsletter/sigcas

believe that CT is a panacea, but certainly, it is a

valuable one. Polemics and controversies used to

make advances in each field, but successful initiatives

have to be acknowledged. K-12 educational system

can not wait until there is a proper and unique

consensus between researchers to start to teach ICT

competencies to our youths.

ACKNOWLEDGMENTS

The authors would like to thank Renata Martins

Pacheco for her help with formatting and reviewing

the English version of the final text.

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