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Abstract

This paper reports on initial findings of a study on developing computational thinking (CT) as a 21st Century skill. Extensive desktop research collecting evidences from the (academic and grey) literature has been complemented with a survey on policy documents and several semi-structured interviews with policy makers, researchers and practitioners involved in the implementation of relevant policy and grassroots initiatives to further understand the uptake of CT approaches in K-12 educational contexts. Preliminary findings from the literature review indicate that the debate on definitional issues remains open. Despite an increasing number of CT implementations in both formal and informal education settings, research still appears necessary on how CT skills develop in K-12 students, what pedagogical approaches can facilitate the effective introduction of CT concepts, and how the acquisition of CT skills should be assessed in practice.
Proceedings EdMedia 2016, Vancouver , June 28-30, 2016
Developing Computational Thinking: Approaches and Orientations
in K-12 Education
Stefania Bocconi
Augusto Chioccariello
Giuliana Dettori
Institute for Educational Technology, National Research Council (CNR) of Italy
Italy
bocconi@itd.cnr.it
augusto@itd.cnr.it
dettori@itd.cnr.it
Anusca Ferrari
Katja Engelhardt
European Schoolnet
Belgium
anusca.ferrari@eun.org
katja.engelhardt@eun.org
Panagiotis Kampylis
Yves Punie
European Commission, DG JRC Institute for Prospective Technological Studies
Spain
panagiotis.kampylis@ec.europa.eu
yves.punie@ec.europa.eu
This paper reports on initial findings of a study on developing computational thinking (CT) as
a 21st Century skill. Extensive desktop research collecting evidences from the (academic and
grey) literature has been complemented with a survey on policy documents and several semi-
structured interviews with policy makers, researchers and practitioners involved in the
implementation of relevant policy and grassroots initiatives to further understand the uptake of
CT approaches in K-12 educational contexts. Preliminary findings from the literature review
indicate that the debate on definitional issues remains open. Despite an increasing number of
CT implementations in both formal and informal education settings, research still appears
necessary on how CT skills develop in K-12 students, what pedagogical approaches can
facilitate the effective introduction of CT concepts, and how the acquisition of CT skills
should be assessed in practice.
Introduction
Digital technology has radically changed the way people think and work. Informatics has contributed
to the scientific and technological development of our society and to the digital revolution. Computational
thinking (CT) is the term in use to refer to the key ideas of the disciplinary areas of informatics and computer
science. This topic has been increasingly gaining attention in the educational field in the past decade, by
researchers, practitioners and policy makers, giving rise to an increasingly large amount of academic and grey
literature, as well as being mentioned, explicitly or implicitly, also in several policy-related documents. An
element that emerges from the debate is the importance of the topic not only for its crucial content, but also for
the positive influence its study can have on the development of general thinking skills.
The complexity of the CT field, however, and the lack of a unique definition and orientation on its
development, highlight the need to carry out some investigation in order to understand more deeply its nature
and how it could be fruitfully introduced into K-12 curricula. Contributing in this respect is the aim of this
study. This article presents the preliminary outcomes of a wide-angle literature analysis. In the next section we
give a short account of the initial definitions and development attempts, then we present the aims and
Proceedings EdMedia 2016, Vancouver , June 28-30, 2016
methodology of our study and sketch the landscape that is emerging from our compound analysis.
Setting the Context
“Computational Thinking” is the title of a ‘viewpoint’ published in the Communications of the ACM
in March 2006 by Jeanette Wing, where it is used as a shorthand for “thinking as a computer scientist”, i.e., the
ability to use computer science concepts to solve problems. Moreover, CT is presented as “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” (Wing, 2006). This article has stimulated a lively international
debate from academia, education, industry, and policy makers that is still active. Consensus on CT definition,
however, has not yet been reached, as one might expect on an issue related to the foundations and epistemology
of computer science as a discipline. The epistemological discussion includes, just to mention a few:
the distinction between computer science and mathematics: “Computer science is … the study of
algorithms” (Knuth, 1974);
computing as natural vs. artificial science: “Computation is present in nature even when scientists are
not observing it ... Computation is more fundamental than computational thinking” (Denning, 2009).
The Report on “Workshop on the Scope and Nature of Computational Thinking”, which was organised
by the USA National Research Council (NRC) in 2010 and involved key international researchers, among
whom J. Wing, documents the lack of consensus on the basic definitions and a number of open questions.
Throughout the workshop, “participants expressed different views about the scope and nature of computational
thinking; almost every participant held his or her own perspective on computational thinking that placed greater
emphasis on particular aspects or characteristics, such as, for instance, how and to what extent, if any, the
ability to program is an essential aspect of computational thinking, as well as how to define programming in the
context of CT” (NRC, 2010, p. 59). The relationship between programming and computational thinking is still
an open issue. In the NRC report, it is related with the connection of CT to technology, claiming thatthe
computer -and notions of computer programmingcan make the concepts, principles, methods, models, and
tools of CT tangible, in much the same spirit that LOGO was first inspired” (NRC, 2010, p. 61).
As a further contribution to this debate, J. Wing, with input from Al Aho, Jean Cuny and Larry Snyder
(2011), revised the original definition as follows:CT is the thought processes involved in formulating a
problem and expressing its solution(s) in such a way that a computerhuman or machinecan effectively
carry out.” This definition has become a reference point for subsequent discussions on CT in the literature.
Wing (2014) elucidates it suggesting that “informally, computational thinking describes the mental activity in
formulating a problem to admit a computational solution. The solution can be carried out by a human or
machine. Also, computational thinking is not just about problem solving, but also about problem formulation”.
It is important to notice, however, that in several articles on CT, the invention of the term is attributed
to Papert (1980). In his perspective, knowledge emerges as a result of an active engagement with the world
through the creation and manipulation of artifacts that are seen as objects to think with. Hence, the Logo
research programme and related studies might be still relevant to CT at school (Grover & Pea, 2013).
In relation to the introduction of CT skills in K-12 education, a number of prominent European
institutions have intervened in the debate. In 2012, the Royal Society published the report “Shut down or
restart? The way forward for computing in UK”. The Acamie des Sciences (France) intervened on this
subject with the report L’enseignement de l’informatique en France Il est urgent de ne plus attendre.
Moreover, Informatics Europe and the Association of Computing Machinery (ACM) Europe, Working Group
on Informatics Education, urged Europenot to miss the boat on this subject. All those reports call for a
change in the curricula to make room for informatics as a discipline. However, the academic debate alone is not
enough to influence the policy level. For instance, a request to include Computing and CT in the recent US K-
12 STEM curriculum was made by the computer science community, arguing that computing and CT are “an
integral part of science and therefore constitute essential knowledge and practices for students” (NRC, 2012, p.
334). By that time, however, such request was rejected.
A parallel UK request that was supported by industry statements like the Next Generation Report and
Eric Schmidt's speech on UK education managed to convince the government that there was a problem to be
solved. As a result, still in 2012 the UK Department for Education declared the introduction of computer
science teaching into UK schools an official goal (Brown et al., 2013). Attempts to add a new discipline to an
already crowded K-12 curriculum, however, presents some problems. Thus, introducing CT into schools
requires special attention to contents. Subjects like science, technology, engineering and math (STEM) seem to
offer a direct match with CT key ideas (Weintrop et al., 2015). However, other subjects can be seen as linked to
Proceedings EdMedia 2016, Vancouver , June 28-30, 2016
CT as well. For example, interactive storytelling and video games construction (Repenning et al., 2015) are
activities related to media art that can offer interesting connections with CT. In response to a gap between
perceived social needs for skills related to computing, CT and the current offering of the educational settings, a
number of grass-roots initiatives are emerging as relevant actors in the CT debate. Some of those initiatives
have quickly reached an international status like Fab Foundation lunched in 2009 in the USA, CoderDojo
started in Ireland in 2011, or Code.org in the USA in 2013. Some are backed by industry (e.g. Code.org),
whereas others are based on volunteer activity (e.g. CoderDojo). The latter grassroots initiatives have a
relevance that goes beyond their lobbing power. They are generally developed in informal settings, not
necessarily tied to curricular constraints, and foster a participatory technological culture based on community of
practices. This trend might help the inclusion of CT in the school curriculum or enter in conflict with school
education in case of lack of evolution on the school side.
The Study
The CompuThink study (https://ec.europa.eu/jrc/en/computational-thinking) is a forward looking
exploration aiming to contribute to the current debate on CT, coding and transversal skills at European and
international level. Its ultimate goal is to further understand the core concepts and attributes of CT as a key skill
in K-12 education, in particular on the following aspects: What characterizes CT differently from other thinking
skills? What is the relationship to programming and to Computer Science? Should CT be addressed within a
specific subject (e.g., CS), integrated in STEM, or as a cross-curriculum topic? What pedagogical approaches
could facilitate CT introduction in K-12 education? How should CT be assessed? What is needed to further the
CT agenda in K-12 education? The overall methodology of the study is based on a qualitative approach. An
extensive review of the literature using a wide range of academic and grey literature has been complemented
with a survey of policy documents with Ministries of Education in Europe in order to identify countries that are
including CT in their curricula, as well as to spot relevant documents (e.g. curricula, guidelines) for further
analysis. A review matrix outlining main research studies, findings and implications is used to structure the in-
depth and comparative analysis of the sources and to identify key issues. Informed insights on crucial factors for
a successful development of CT skills in K-12 is being collected via semi-structured interviews with policy
makers, researchers and practitioners so as to validate and complement the literature review.
Initial Findings: General Trends on Computational Thinking in K-12 Education
Two main trends emerged on the rationale for including CT in K-12 education: (1) fostering CT to
boost economic growth, fill vacancies in ICT, and prepare for future jobs; (2) develop CT skills in children and
young people to enable them to think in a different way, to express themselves through a variety of media, to
solve problems and analyze everyday issues with a different perspective. Many articles mention both trends
when explaining rationales for teaching CT: the general benefits of CT as a thinking skill and the need to
develop new skills for the employment market. The emphasis on one or the other depends on the stakeholder’s
point of view: some criticize a too narrow focus on employability aspects (e.g. CoderDojo, Computing at
School), others put a strong emphasis on the job opportunities that coding can provide (e.g. the recent initiative
of President Obama “Computer Science for all”).
CT Definitions and Characterizations
Regarding the definition of CT and its main characterizations, the majority of the literature refers to
J. Wing’s definitions (2006, 2011). One voice against this widely adopted definition comes from Jones (2011)
who argues that it remains abstract and fails to differentiate CT from other forms of thinking. In his blog article,
Guzdial (April 2012) suggests to include risks and cyber-security in CT definition. Aaron Sloman (London
Knowledge Lab, 2012) even defines CT as "one of the required approaches to understanding the universe,
which was not available to the deepest thinkers in most of the history of science, mathematics, engineering and
philosophy". Some papers also refer to the creative aspects of CT: "computational thinking is, indeed, a key to
developing the capacity to discover, create and innovate" (Allan et al., 2010). Many authors refer to CT in
relation to problem solving, or to modeling and solving real world problems (e.g. Lee, 2016). Regarding what
differentiates CT from other thinking skills, some authors argue that a deeper analysis is needed on the typology
of thoughts that are key to CT. Grover & Pea (2013) extract from the literature several CT characterizations:
Proceedings EdMedia 2016, Vancouver , June 28-30, 2016
Abstractions and pattern generalizations (including models and simulations)
Systematic processing of information
Symbol systems and representations
Algorithmic notions of flow of control
Structured problem decomposition (modularizing)
Iterative, recursive, and parallel thinking
Conditional logic
Efficiency and performance constraints
Debugging and systematic error detection.
CT Relation to Programming and Computer Science
CT is recognized not to necessarily need programming of computers, but rather to be an approach to
problem solving that uses strategies such as algorithms, abstraction and debugging (Dede et al., 2013).
However, programming is creative and engaging; it illustrates in concrete terms otherwise-abstract concepts
(Peyton-Jones, 2015). There is, therefore, a mutual influence between CT and coding/programming:
To some extent, the acquisition of computational thinking skills has been a side effect of learning to
program: while learning programming languages, computer science students also to pick up higher
level skills which are applicable outside of computer science (Howland et al., 2009).
Design-based learning activities in particular, programming interactive media support the
development of CT in young people (Brennan & Resnick, 2012).
Due to this mutual influence, the borders between CT and coding/programming are seen as not really
clear-cut: the concepts of CT and the practice of programming are difficult to separate in the literature because
many CT studies use programming as their reference context. This can be confusing and often leads to the
impression that CT is the same as programming or, at the very least, that CT requires the use of programming to
be developed (Voogt et al., 2015).
CT Assessment in K-12 Education
A number of methodologies and tools for assessing the acquisition of CT skills in compulsory
education emerged from the literature. Along more traditional multiple choice tests and open ended questions, a
project-based approach emerges as essential element of assessments systems. Two approaches to project-based
CT assessment are present in the literature: (automated) analysis of projects portfolio and artifact-based
interviews. Brennan & Resnick (2012), e.g., describe three approaches to assessing the development of CT:
analyzing the portfolio of projects uploaded by a particular community member and generating a visual
representation of the blocks used (or not used) in every project;
artifact-based interviews, based on two projects selected by the interviewee;
design scenarios; given three sets of projects with increasing complexity the interviewee is asked to
select one and “(1) explain what the selected project does, (2) describe how it could be extended, (3)
fix a bug, and (4) remix the project by adding a feature”.
Skill transfer to other contexts is another form of assessment being investigated, as for example the
capability of transferring computational understanding built in a visual programming environment to a textual
one (Grover, Pea & Cooper, 2015).
Implementation of CT Initiatives
Most of the papers analyzed on CT implementation represent serious and effective attempts to develop
practical learning activities apt to foster some of the skills and competences that characterize CT. Some authors
(e.g., Taub et al.,2014) give emphasis to the development of CT characterizing skills, such as abstraction, yet
referrring to CS instead of to CT. As concerns the kind of activity proposed to develop CT, most author refer to
programming tasks, yet often carried out with learning environments/tools (e.g., Scratch) that do not require
coding in a formal language. The objective of the proposed programming activities is mostly the development
of games, that are considered excellent situations in which abstraction (of moves and actions) can be understood
and meaningfully used. There are some notable exceptions, however. For instance:
Weintrop et al. (2015) propose the development of CT within STEM course;
Yevseyeva and Towhidnejad (2012) aim to disclose the advantages of CT to non-computing students,
by organizing collaborative activities on world issues, thanks to the fact that CT helps decompose
Proceedings EdMedia 2016, Vancouver , June 28-30, 2016
problems into manageable steps, employ abstraction to deal with complexity, recognize patterns and
create scalable algorithms to solve real problems;
Taub et al. (2014) see abstraction as a common element between CT and Physic, and plan a physics
problem solving activity apt to highlight different levels of abstraction in physics.
Some attention is also given to introduce CT to girls (e.g., Weintrop et al., 2015), by proposing
activities closer to girls' tastes and hence more motivating to them. As concerns the school levels considered,
most implementations concern high school, but also middle school (e.g., Cher 2015) and primary school (e.g.,
Quinlan, 2015) are considered.
Conclusion and Future Work
This brief paper has presented initial findings emerging from literature analysis in the context of the
CompuThink study. Although the debate on definitional issues remains open and ongoing, much of the recent
work in the field increasingly focuses on CT specific characterizations and related skills. We would argue that
this point is a cornerstone for the successful and meaningful implementation of CT in education, especially in
curricula: clear definitions and conceptualizations lead to well-structured and effective curricula and learning
objectives. As more and more CT implementations emerge (both in formal and informal education settings),
major attention is given to the disciplinary contexts in which CT should be addressed in K-12 (i.e., within a
specific subject such as Computer Science, integrated in STEM, or as a cross-curriculum topic). Large gaps,
however, still exist that call out for extensive research on (among other issues) how CT skills develop in K-12
students and what pedagogical approaches can facilitate the effective introduction of CT concepts throughout K-
12 education. CT assessments practices are also underinvestigated, and, in particular, what kind of assessment
can elicit students’ problem solving and CT skills in authentic contexts. Grassroots initiatives that are emerging
are currently not focusing their action on assessing CT, possibly as a consequence of their inception status in
several cases and for their extra curricular application in others. To help fill these gaps, in the context of
CompuThink, curricula and policy documents, together with grassroots initiatives will be analyzed more in
depth, so as to highlight the red thread that goes from conceptual constructions (i.e. research and studies, as
exemplified in the review of the academic and grey literature) to practices (i.e. grassroots initiatives), passing
through policy-making (as emerging from the analysis of curricula and policy-documents surveyed with EU
Ministries of Education). Informed insights collected from stakeholders and practitioners involved in CT
initiatives will also contribute to building an overall picture of this field, shedding lights on the crucial factors for
a successful development of CT skills in K-12 students.
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Acknowledgements
CompuThink is funded and designed by the Joint Research Centre (JRC), Institute for Prospective Technological Studies of
the European Commission (EC) (Contract No. 199551-2015A08IT). The JRC is an EC-run service which involves scientists
to provide independent scientific advice and support to EU policy. The study, which runs from December 2015 to
September 2016, is carried out by the Institute for Educational Technology of the Italian National Research Council and
European Schoolnet, which represents a network of Ministries of Education in Europe. The data presented, the statements
made and the views expressed are purely those of the authors and should not be regarded as the official position of the
European Commission.
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... Wing (2006Wing ( , 2010 proposed a set of characteristics to define CT, and in the years to come, several additional models and definitions have been presented, for example by Brennan and Resnick (2012) and Weintrop et al. (2016). No formally established definition of the concept exists, even though several representations share central ideas (Bocconi, et al., 2016a(Bocconi, et al., , 2016bRich & Langton, 2016;Shute et al., 2017;Tedre & Denning, 2016). Programming is generally seen as a distinct tool with which broader CT skills can be developed (Resnick et al., 2009), but the academic debate of how programming relates to CT, what the broader skills associated with CT are and how these can be integrated in K-12 education and assessed is ongoing (Saqr et al., 2021). ...
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The purpose of this study is to examine the role of Minecraft-based coding activities on computational thinking (CT) of middle school students. In the study, CT was conceptualized so that it encapsulates not only the knowledge of computational concepts (e.g., loops and conditionals) but also the use of CT practices (e.g., testing and debugging). Data were collected using a combination of knowledge of computational concepts tests, the Minecraft-based coding artifacts, and one-on-one student interviews focusing on the processes of developing computational artifacts. The participants were 20 fifth-grade middle school students from a low-income public school with very limited (if none) formal computer programming experiences before the study. The Minecraft-based coding activities were designed and implemented as an instructional program to last 6 weeks. The results of the study showed a statistically significant increase in students’ knowledge of computational concepts. Based on the analysis of the students’ final coding artifacts, we identified that students mostly used the concepts of sequences, events, loops, and parallelism correctly, whereas variables, operators, and conditionals appeared to be the least successfully used concepts. The qualitative analysis of the artifact-based interviews showed that students employed the CT practices of testing and debugging most of the time while developing an artifact through coding. In contrast, the least resorted CT practice appeared to be reusing and remixing.
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