computational thinkingcomputational thinking
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Definitionen
Computational thinking is loosely
defined as the habits of mind developed
from designing programs, software
packages, and computations performed
by machines.Computational Thinking (CT) is a thought process (or a human thinking skill) that uses
analytic and algorithmic approaches to formulate, analyse and solve problems. I
Von Stefania Bocconi, Augusto Chioccariello, Giuliana Dettori, Anusca Ferrari, Katja Engelhardt im Buch Developing Computational Thinking in Compulsory Education (2016) This term has been defined in many ways and encompasses a broad and somewhat debated range of analytic and problem-solving skills, dispositions,
habits, and approaches used in computer science
Von Marina Umaschi Bers, Louise P. Flannery, lizabeth R. Kazakoff im Text Computational thinking and tinkering (2014) 
Dies meint die Fähigkeit, Probleme und Prozesse so
zu formulieren, dass sie sich mithilfe von Computertechnologien lösen bzw. Bearbeiten lassen. Dies umfasst einerseits die Auswahl und Nutzung und
andererseits auch die Programmierung geeigneter Software.
Computational thinking is thinking in terms of
prevention, protection, and recovery from worst-case
scenarios through redundancy, damage containment,
and error correction. It is calling gridlock deadlock
and contracts interfaces. It is learning to avoid race
conditions when synchronizing meetings with one
another.we have created the following working definition of CT: The conceptual
foundation required to solve problems effectively and efficiently (i.e., algorithmically, with
or without the assistance of computers) with solutions that are reusable in different
contexts. This definition highlights that CT is primarily a way of thinking and acting, which
can be exhibited through the use particular skills, which then can become the basis for
performance-based assessments of CT skills.
Von Valerie J. Shute, Chen Sun, Jodi Asbell-Clarke im Text Demystifying computational thinking (2017) Computational thinking is thinking recursively. It
is parallel processing. It is interpreting code as data
and data as code. It is type checking as the generalization
of dimensional analysis. It is recognizing
both the virtues and the dangers of aliasing, or giving
someone or something more than one name. It
is recognizing both the cost and power of indirect
addressing and procedure call. It is judging a program
not just for correctness and efficiency but for
aesthetics, and a system’s design for simplicity and
elegance.Very briefly, the key points of Computational Thinking are that
Von James J. Lu, George H. L. Fletcher im Text Thinking about computational thinking (2009) - it is a way of solving problems and designing systems that draws on concepts fundamental to computer science
- it means creating and making use of different levels of abstraction, to understand and solve problems more effectively;
- it means thinking algorithmically and with the ability to apply mathematical concepts to develop more efficient, fair, and secure solutions; and
- it means understanding the consequences of scale, not only for reasons of efficiency but also for economic and social reasons.
Computational thinking is using abstraction and
decomposition when attacking a large complex task
or designing a large complex system. It is separation
of concerns. It is choosing an appropriate representation
for a problem or modeling the relevant aspects
of a problem to make it tractable. It is using invariants
to describe a system’s behavior succinctly and
declaratively. It is having the confidence we can
safely use, modify, and influence a large complex
system without understanding its every detail. It is
modularizing something in anticipation of multiple
users or prefetching and caching in anticipation of
future use.Papert and Harel (1991) were the first who coined the term “computational thinking”
in their 1991 paper on constructionism. They proposed that computational
thinking was a shift on students’ thinking by contributing to their mental growth and
become producers of knowledge using computing. Computational thinking received
broader recognition from Wing (2006) who suggested that computational thinking
was a critical twenty-first-century skill comparable to reading or math. Wing
described computational thinking as “the thought processes involved in formulating
a problem and expressing its solution in a way that a computer—human or
machine—can effectively carry out” (p. 33).
Von Olgun Sadik, Anne-Ottenbreit Leftwich, Hamid Nadiruzzaman im Buch Emerging Research, Practice, and Policy on Computational Thinking (2017) im Text Computational Thinking Conceptions and Misconceptions auf Seite 222
Ever since Jeannette Wing (2006) coined the term “computational thinking,” there has been a debate over
providing a single definition. Despite the lack of a consistent definition, within the Computer Science
community, a common understanding of the term emerged related to abstraction as a means for solving
problems. According to P.J. Denning (2009), computational thinking is just a new term for a core
concept, algorithmic thinking. Computer Science is not just about programming, but an entire way of
thinking. The Computer Science community believes that learning to think in this way, to think
computationally, could promote new perspectives and solutions to problems in many other disciplines
(Wenger, 1998).Computational Thinking (vgl. GAS 2014)
betont den Stellenwert des Nachdenkens und Analysierens von Problemen
und Problemlösungsstrategien, die der anschließenden Umsetzung mit ei
nem Computer vorausgehen. Hierzu gehören die Anwendung verschiedener
In der Informatik zentraler Konzepte wie Logik (analysieren und Voraussagen
treffen), Abstraktion (Unwichtiges weglassen), Dekomposition (Komplexität
in Teilprobleme zergliedern) und Algorithmisieren (Prozesse automatisieren
und nachvollziehen) sowie Arbeitsweisen, die in der Informatik und bei der
Nutzung und Gestaltung digitaler Medien gefördert werden. Hierzu zählen
Kreativität (Gestalten und Umsetzen von Ideen), Debuggen (Fehler finden
und korrigieren). Durchhalten (Probleme meistern lernen) und Kollaboration
(zusammenarbeiten).
Von Ralf Romeike im Buch Software takes command im Text Wie informatische Bildung hilft, die digitale Gesellschaft zu verstehen und mitzugestalten (2017) Wing’s original paper did not offer a succinct definition for
computational thinking, but offered many examples of how
computer scientists tackle common problems: “When your
daughter goes to school in the morning, she puts in her
backpack the things she needs for the day; that’s prefetching
and caching. When your son loses his mittens, you suggest
he retrace his steps; that’s back-tracking. [...] Which line
do you stand in at the supermarket?; that’s performance
modeling for multi-server systems.” [12]. Extrapolating from
these examples, the overall message is that computer scientists
have a toolbox of methods for matching problem situations
to standard types of solution, drawn from various parts of the
computer science curriculum, and, perhaps just as importantly,
a standard terminology to describe these abstract problemsolution
patterns.
Von Steve Easterbrook im Text From Computational Thinking to Systems Thinking (2014) 
Bemerkungen
Endlich wird in vielen Fächern durch das Lösen von Problemen
("problem solving approach") das informatische Denken
gefördert.CT is not about getting humans to think like computers, but rather about developing the full set of mental tools necessary to effectively use computing to solve complex human problems [8].
Von James J. Lu, George H. L. Fletcher im Text Thinking about computational thinking (2009) Ubiquitous computing is to today as computational
thinking is to tomorrow. Ubiquitous computing was
yesterday’s dream that became today’s reality; computational
thinking is tomorrow’s reality.Just as the printing press facilitated the spread of the
three Rs, what is appropriately incestuous about this
vision is that computing and computers facilitate the
spread of computational thinking.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.Computational Thinking ist ein Ansatz, der bewusst auf
Konzepte und Problemlösungsstrategien allgemeiner
Relevanz fokussiert. Es geht unter anderem darum, den
Zusammenhang zwischen sequenziellen und parallelen
Prozessen zu verstehen.Computational thinking involves solving 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.Computational thinking
confronts the riddle of machine intelligence:
What can humans do better than computers? and
What can computers do better than humans? Most
fundamentally it addresses the question: What is
computable? Today, we know only parts of the
answers to such questions.Computational thinking will have become
ingrained in everyone’s lives when words like algorithm
and precondition are part of everyone’s vocabulary vocabulary;
when nondeterminism and garbage collection
take on the meanings used by computer scientists;
and when trees are drawn upside down.Dieses Computerdenken kann man lernen, ohne den konkreten Programmcode zu kennen, sagt auch Ulrich Kortenkamp, der an der Universität Potsdam Didaktik der Informatik lehrt. Er ergänzt aber, dass es viel einfacher und schöner sei, wenn man auch programmieren darf. "Das ist die naheliegende praktische Umsetzung, die man sich nicht nehmen lassen sollte."
Von Christoph Drösser im Text Kids & Codes (2017) 
Computational Thinking ist ein Denken mit und in numerischen Modellen. Im Altertum wurden Theorien
aufgestellt – Astronomie mit Kugeln auf Kreisen –, in der frühen Neuzeit wurde gemessen und experimentiert – Kugeln auf Ellipsen, Bahnen mit
Abweichungen –, und heute wird zusätzlich numerisch modelliert. Ohne Computer wäre schon der Mondflug unmöglich gewesen.True, an algorithm is a series of
steps—but the steps are not arbitrary,
they must control some computational
model. A step that requires human judgment
has never been considered to be
an algorithmic step. Let us correct our
computational thinking guidelines to
accurately reflect the definition of an algorithm.
Otherwise, we will mis-educate
our children on this most basic idea.Computational thinking provides an ontology of computational
concepts, and a set of terms for talking about them. For
example, procedural and data abstractions provide the building
blocks of computational solutions, and sequential and parallel
composition provide a way of putting them together. Hierarchical
decomposition is used to reduce complex problems, and
encapsulation is used to create re-usable solutions.
Von Steve Easterbrook im Text From Computational Thinking to Systems Thinking (2014) If computational
thinking is the central tool of computer scientists, then we
ought to consider whether computational thinking becomes
just another instance of Maslow’s Hammer [16]: “If all you
have is a hammer, then everything looks like a nail”. In
other words, computer professionals may attempt to solve all
problems through algorithmic means, while failing to perceive
those that cannot be expressed using the abstractions of CT.
Von Steve Easterbrook im Text From Computational Thinking to Systems Thinking (2014) Because computation has invaded
so many fields, and because people who
do computational design in those fields
have made many new discoveries, some
have hypothesized that CT is the most
fundamental kind of thinking, trumping
all the others such as systems thinking,
design thinking, logical thinking,
scientific thinking, etc. This is computational
chauvinism. There is no basis
to claim that CT is more fundamental
than other kinds of thinking.
Von Peter J. Denning, Matti Tedre, Pat Yongpradit im Text Misconceptions About Computer Science (2017) Computational thinking is using heuristic reasoning
to discover a solution. It is planning, learning,
and scheduling in the presence of uncertainty. It is
search, search, and more search, resulting in a list of
Web pages, a strategy for winning a game, or a counterexample. Computational thinking is using massive
amounts of data to speed up computation. It is making
trade-offs between time and space and between
processing power and storage capacity.Finally, it is worth noting that educators
have long promoted a large number
of different kinds of thinking: engineering
thinking, science thinking,
economics thinking, systems thinking,
logical thinking, rational thinking,
network thinking, ethical thinking,
design thinking, critical thinking,
and more. Each academic field claims
its own way of thinking. What makes
computational thinking better than
the multitude of other kinds of thinking?
I do not have an answer.Programming should not, however, be essential in the
teaching of computational thinking, nor should knowledge
of programming be necessary to proclaim literacy in basic
computer science. Just as math students come to proofs after
12 or more years of experience with basic math, and
English students come to literary analysis after an even
longer period of reading and writing, programming should
begin for all students only after they have had substantial
practice thinking computationally.
Von James J. Lu, George H. L. Fletcher im Text Thinking about computational thinking (2009) Encouraged by funding programs from the NSF, the US
computer science community has readily adopted the term
computational thinking, using it as a slogan to re-design existing
computer science curricula to make them more attractive
to students, and to develop new courses aimed at audiences
who would not otherwise be exposed to computer science. For
example, the Computer Science Teachers Association (CSTA)
set up a task force to “explore and disseminate teaching and
learning resources related to computational thinking”.
Von Steve Easterbrook im Text From Computational Thinking to Systems Thinking (2014) Computational thinking (CT) stems back to the constructionist work of Seymour Papert (Papert, 1980, 1991) and was first
coined as a term in a seminal article by Wing (2006). She explained that CT entails “solving problems, designing systems, and
understanding human behavior, by drawing on the concepts fundamental to computer science” (Wing, 2006, p. 33). As such,
it represents an ability to analyze and then solve various problems. Her arguments provided a fresh perspective on the relationship(
s) between humans and computers, and gave rise to a wave of research on CT.
Von Valerie J. Shute, Chen Sun, Jodi Asbell-Clarke im Text Demystifying computational thinking (2017) The computational thinker looks for problems that can be
tackled with computers. Immediately, this provides a selective
lens through which to view the world. Problems that are unlikely
to have computational solutions (e.g. ethical dilemmas,
value judgements, societal change, etc) are ignored. Others are
reduced to a simpler, computational proxy. It is no coincidence
that computer science students tend to be less morally mature
than students from other disciplines [17]. Ethical dilemmas
have no computational solutions, and so are overlooked when
peering through a CT lens.
Von Steve Easterbrook im Text From Computational Thinking to Systems Thinking (2014) Computational thinking (CT) is an old idea in CS, first
discussed by pioneers such as Alan
Perlis in the late 1950s.8 Perlis thought
“algorithmizing” would become part
of every field as computing moved in
to automate processes. Dijkstra recognized
he had learned new mental skills
while programming (1974). In his 1980
book Mindstorms, Papert was the first
to mention the term CT explicitly when
discussing the mental skills children
developed while programming in Logo.
Jeannette Wing catalyzed a discussion
about how people outside CS could
benefit from learning computing.
Von Peter J. Denning, Matti Tedre, Pat Yongpradit im Text Misconceptions About Computer Science (2017) At heart, CT is inherently reductionist. Computational problems
are tackled by reducing them to a set of discrete variables
that can be mapped onto abstract data types, and a set of
algorithmic steps for manipulating these data types. In the
process, multiple perspectives on the nature of the problem are
lost, as is any local, contingent knowledge about the problem
situation [18]. Computational thinking thus ignores the fact
that any particular expression of the “the problem to be solved”
is the result of an ongoing negotiation between the competing
needs of a variety of stakeholders [19], [20].
Von Steve Easterbrook im Text From Computational Thinking to Systems Thinking (2014) Wing (2006) argued that CT does not mean to think like a computer; but rather to engage in five cognitive processes with
the goal of solving problems efficiently and creatively. These include:
Von Valerie J. Shute, Chen Sun, Jodi Asbell-Clarke im Text Demystifying computational thinking (2017) - Problem reformulation - Reframe a problem into a solvable and familiar one.
- Recursion - Construct a system incrementally based on preceding information.
- Problem decomposition - Break the problem down into manageable units.
- Abstraction - Model the core aspects of complex problems or systems.
- Systematic testing - Take purposeful actions to derive solutions.
Although there are different efforts to define the term and there is no consensus on different definitions, there is a general
acceptance that CT skills cover the concepts of “abstraction, algorithmic thinking, problem-solving, decomposition, generalization,
and debugging” (Sarıtepeci & Durak, 2017). In support of this, Kalelioglu, Gülbahar and Kukul (2016) have formed a
word cloud in relation to the explanations about computational thinking in their work and have found that the data words
that are most used in terms of defining the process of computation thinking in the literature are “abstraction, problem,
solving, algorithmic and thinking.
Von Hatice Yildiz Durak, Mustafa Saritepeci im Text Analysis of the relation between computational thinking skills and various variables with the structural equation model (2017) 
Verwandte Objeke
Verwandte Begriffe (Cozitation) | AgentCubes, Programmierenprogramming, AgentSheets, Scratch, Informatikcomputer science |
CoautorInnenlandkarte
Relevante Personen
Häufig erwähnende Personen
AlexanderRepenning
Kenny A.Hunt
David D.Riley
Ashok R.Basawapatna
Yasmin B.Kafai
QuinnBurke
MarkGuzdial
Häufig co-zitierte Personen
Jeannette M.Wing
AlexanderRepenning
Kyu HanKoh
AndriIoannidou
Ashok R.Basawapatna
Yasmin B.Kafai
HilarieNickerson
George H. L.Fletcher
James J.Lu
Vicki E.Bennett
SeymourPapert
BrianSilverman
AmonMillner
EvelynEastmond
JaySilver
DavidWebb
AndrésMonroy-Hernández
KarenBrennan
EricRosenbaum
CatharineBrand
JamesAmbach
MitchelResnick
NatalieRusk
JohnMaloney
Statistisches Begriffsnetz
Blahfasel-Generator (Beta)
Computational thinking - eine Auslegeordnung angeregt von Alexander Repenning
Nicht erst seit gestern erregt das Thema "computational thinking" die Gemüter. Es wird aus diesen Überlegungen der Versuch unternommen, einige allgemeine Erläuterungen im Laufe der Zeit zu formulieren.
Im Jahr 1978 wurde der Begriff erstmals erwähnt. Wer erinnert sich noch genau an diese Zeiten? Allgemein gilt Alexander Repenning als häufig zitierter Experte für dieses Thema. Ashok R. Basawapatna wird aber ebenfalls oft genannt.
Ein Blick auf die Begriffsgenese ist unumgänglich. Die am meisten zitierte Erklärung des Begriffs lautet: "Computational thinking is thinking in terms of prevention, protection, and recovery from worst-case scenarios through redundancy, damage containment, and error correction. It is calling gridlock deadlock and contracts interfaces. It is learning to avoid race conditions when synchronizing meetings with one another." (Jeannette M. Wing, 2006). Vergleichbar formuliert die Definition von Jeannette M. Wing (2006) : "Computational thinking is using abstraction and decomposition when attacking a large complex task or designing a large complex system. It is separation of concerns. It is choosing an appropriate representation for a problem or modeling the relevant aspects of a problem to make it tractable. It is using invariants to describe a system’s behavior succinctly and declaratively. It is having the confidence we can safely use, modify, and influence a large complex system without understanding its every detail. It is modularizing something in anticipation of multiple users or prefetching and caching in anticipation of future use.". Hier zeigen sich nun sowohl Unterschiede und Gemeinsamkeiten. ...
Nicht erst seit gestern erregt das Thema "computational thinking" die Gemüter. Es wird aus diesen Überlegungen der Versuch unternommen, einige allgemeine Erläuterungen im Laufe der Zeit zu formulieren.
Im Jahr 1978 wurde der Begriff erstmals erwähnt. Wer erinnert sich noch genau an diese Zeiten? Allgemein gilt Alexander Repenning als häufig zitierter Experte für dieses Thema. Ashok R. Basawapatna wird aber ebenfalls oft genannt.
Ein Blick auf die Begriffsgenese ist unumgänglich. Die am meisten zitierte Erklärung des Begriffs lautet: "Computational thinking is thinking in terms of prevention, protection, and recovery from worst-case scenarios through redundancy, damage containment, and error correction. It is calling gridlock deadlock and contracts interfaces. It is learning to avoid race conditions when synchronizing meetings with one another." (Jeannette M. Wing, 2006). Vergleichbar formuliert die Definition von Jeannette M. Wing (2006) : "Computational thinking is using abstraction and decomposition when attacking a large complex task or designing a large complex system. It is separation of concerns. It is choosing an appropriate representation for a problem or modeling the relevant aspects of a problem to make it tractable. It is using invariants to describe a system’s behavior succinctly and declaratively. It is having the confidence we can safely use, modify, and influence a large complex system without understanding its every detail. It is modularizing something in anticipation of multiple users or prefetching and caching in anticipation of future use.". Hier zeigen sich nun sowohl Unterschiede und Gemeinsamkeiten. ...
Vorträge von Beat mit Bezug
- Informatik konkret machen
Ideen zum Informatikunterricht in der Volksschule
Fachbereich Medienbildung, PH Zürich, 03.10.2013
2 Einträge in Beats Blog
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- Informatik erschließen - Ein curricularer Ansatz für Mädchen (Anne Weibert, Thomas von Rekowski, Volker Wulf) (2013)
- Informatik erschließen - Ein curricularer Ansatz für Mädchen (Anne Weibert, Thomas von Rekowski, Volker Wulf) (2013)
- Programmieren oder programmiert werden - Die Grundlagen der Informatik sollten an den Schulen in einem eigenständigen, obligatorischen Fach unterrichtet werden (Stefan Betschon) (2013)
- «Die Informatik verändert, was unter Allgemeinbildung zu verstehen ist» (Carl August Zehnder, Stefan Betschon) (2013)
- Informatik im Lehrplan 21 - Ein grundsätzlicher Positionsbezug zum Wohl und Nutzen des Denk- und Werkplatzes Schweiz (Hasler Stiftung) (2013)
- Digitale Schule Österreich (Peter Micheuz, Anton Reiter, Gerhard Brandhofer, Martin Ebner, Barbara Sabitzer) (2013)
- Informatik und Bildung - eine philosophische Annäherung (Ludwig Hasler) (2013)
- ICER 2013 - International Computing Education Research Conference, ICER '13, La Jolla, CA, USA, August 12-14, 2013 (Beth Simon, Alison Clear, Quintin I. Cutts) (2013)
- The zones of proximal flow - guiding students through a space of computational thinking skills and challenges (Ashok R. Basawapatna, Alexander Repenning, Kyu Han Koh, Hilarie Nickerson) (2013)
- Efficient egg drop contests - how middle school girls think about algorithmic efficiency (Michèlle Friend, Robert Cutler) (2013)
- Alternate realities for computational thinking (Karen Doore) (2013)
- The zones of proximal flow - guiding students through a space of computational thinking skills and challenges (Ashok R. Basawapatna, Alexander Repenning, Kyu Han Koh, Hilarie Nickerson) (2013)
- The 44th ACM Technical Symposium on Computer Science Education, SIGCSE '13, Denver, CO, USA, March 6-9, 2013 (Tracy Camp, Paul T. Tymann, J. D. Dougherty, Kris Nagel) (2013)
- The simulation creation toolkit - an initial exploration into making programming accessible while preserving computational thinking (Ashok R. Basawapatna, Alexander Repenning, Clayton H. Lewis) (2013)
- Computing creativity - divergence in computational thinking (Vicki E. Bennett, Kyu Han Koh, Alexander Repenning) (2013)
- Robobuilder - a computational thinking game (abstract only) (David Weintrop, Uri Wilensky) (2013)
- Using scaffolded examples to teach computational thinking concepts (Heidi C. Webb, Mary Beth Rosson) (2013)
- The simulation creation toolkit - an initial exploration into making programming accessible while preserving computational thinking (Ashok R. Basawapatna, Alexander Repenning, Clayton H. Lewis) (2013)
- Schweizer Informatik Gesellschaft (SI) zum Lehrplan 21 (Schweizer Informatik Gesellschaft (SI), Jürg Gutknecht, Juraj Hromkovic, Marc Brandis, Mehdi Jazayeri, Dominik Gruntz, Beat Trachsler, Armin Barth, Stefan Niggli) (2013)
- Computational thinking and tinkering - Exploration of an early childhood robotics curriculum (Marina Umaschi Bers, Louise P. Flannery, Elizabeth R. Kazakoff) (2014)
- A Practical Guide to Teaching Computing and ICT in the Secondary School - 2. Edition (Andrew Connell, Anthony Edwards, Alison Hramiak) (2014)
- Beim Programmieren der Fantasie freien Lauf lassen (Alexander Repenning) (2014)
- Should Everybody Learn to Code? (Esther Shein) (2014)
- Computational Thinking for the Modern Problem Solver (David D. Riley, Kenny A. Hunt) (2014)
- 1. What is Computational Thinking?
- 4. Solving Problems
- 12. Information Security
- Beyond Minecraft - Facilitating Computational Thinking through Modeling and Programming in 3D (Alexander Repenning, David C. Webb, Catharine Brand, Fred Gluck, Ryan Grover, Susan Miller, Hilarie Nickerson, Muyang Song) (2014)
- Medienbildung im digitalen Zeitalter (Thomas Merz, Mareike Düssel) (2014)
- Connected Code - Why Children Need to Learn Programming (Yasmin B. Kafai, Quinn Burke) (2014)
- KEYCIT 2014 - Key Competencies in Informatics and ICT (Torsten Brinda, Nicholas Reynolds, Ralf Romeike) (2014)
- «Schüler sind keine Memory Sticks» (Alexander Repenning, Raffael Schuppisser) (2014)
- Lessons in Teaching Computing in Primary Schools (James Bird) (2014)
- From Computational Thinking to Systems Thinking - A conceptual toolkit for sustainability computing (Steve Easterbrook) (2014)
- ISSEP 2014 - Informatics in Schools - Teaching and Learning Perspectives (Yasemin Gülbahar, Erinç Karataş) (2014)
- 1. Informatics and General Education (Walter Gander) (2014)
- 1. Informatics and General Education (Walter Gander) (2014)
- ICER 2014 - International Computing Education Research Conference, ICER 2014, Glasgow, United Kingdom, August 11-13, 2014 (Quintin I. Cutts, Beth Simon, Brian Dorn) (2014)
- Computational thinking curriculum development for upper elementary school classes (Charlotte Hill) (2014)
- Computational thinking curriculum development for upper elementary school classes (Charlotte Hill) (2014)
- The 45th ACM Technical Symposium on Computer Science Education, SIGCSE '14, Atlanta, GA, USA - March 05 - 08, 2014 (J. D. Dougherty, Kris Nagel, Adrienne Decker, Kurt Eiselt) (2014)
- China's perspective from the viewpoint of computational thinking on CS1 for non-majors (abstract only) (Ming Zhang 0004, Bo Li, Ginnie Lo) (2014)
- Studio K - a game development environment designed for gains in computational thinking (abstract only) (Gabriella Anton, Matthew Berland) (2014)
- Kodu alice and computer science unplugged - a model of effective introducing middle school students to computer science and computational thinking (abstract only) (Daniela Marghitu, Lavaris Thomas, Yasmeen Rawajfih, Jillian Hall, Andrew Marshall) (2014)
- Creative Computing (Karen Brennan, Christan Balch, Michelle Chung) (2014)
- WiPSCE 2014 - Proceedings of the 9th Workshop in Primary and Secondary Computing Education, Berlin, Germany, November 5-7, 2014 (Carsten Schulte, Michael E. Caspersen, Judith Gal-Ezer) (2014)
- Introducing teachers to computational thinking using unplugged storytelling (Paul Curzon, Peter W. McOwan, Nicola Plant, Laura R. Meagher) (2014)
- Informatics concepts for primary education - preparing children for computational thinking (Barbara Sabitzer, Peter K. Antonitsch, Stefan Pasterk) (2014)
- Computational thinking skills in dutch secondary education - exploring teacher's perspective (Natasa Grgurina, Erik Barendsen, Bert Zwaneveld, Klaas van Veen, Idzard Stoker) (2014)
- Regelstandards informatische Bildung in der Volksschule des Kantons Solothurn - Wegleitung und Empfehlungen (imedias) (2014)
- Teaching Computing - Developing as a Reflective Secondary Teacher (Carl Simmons, Claire Hawkins) (2015)
- Computational Thinking in der Lehrerbildung (Alexander Repenning) (2015)
- Proceedings of the 46th ACM Technical Symposium on Computer Science Education - Kansas City, MO, USA, March 4-7, 2015 (Adrienne Decker, Kurt Eiselt, Carl Alphonce, Jodi Tims) (2015)
- Evaluating Scratch Programs to Assess Computational Thinking in a Science Lesson - (Abstract Only) (Jennifer Albert, Barry W. Peddycord III, Tiffany Barnes) (2015)
- Situating Computational Thinking with Big Data - Pedagogy and Technology (Abstract Only) (Austin Cory Bart) (2015)
- Developing Computational Thinking Through Image Making and Constructionist Learning - (Abstract Only) (Eileen Fordham, Halley Freger, Amanda Hinchman-Dominguez, Alexander Mitchell, Daniel Rebelsky, Victoria Tsou, Earnest Wheeler, Zoe Wolter, Samuel A. Rebelsky) (2015)
- KELP CS and LaPlaya - A Computational Thinking Curriculum and Development Environment for 4th - 6th Grade (Abstract Only) (Diana Franklin, Hilary A. Dwyer) (2015)
- Assessments for Computational Thinking in K-12 - (Abstract Only) (Shuchi Grover, Marie A. Bienkowski, Eric Snow) (2015)
- STEM Careers Inforgaphic Project (SCIP) - Teaching Media-Based Computational Thinking Practices (Abstract Only) (Brittany Ann Kos, Elizabeth Sims) (2015)
- Computing in the Classroom - A Workshop for Teachers to Infuse Computational Thinking into K-12 Classrooms (Abstract Only) (Yesem Kurt-Peker, Lydia Ray, Rania A. HodHod, Shamim Khan) (2015)
- What Does It Take to Do Computer Programming? - Surveying the K-12 Students' Conceptions (Antti-Jussi Lakanen, Ville Isomöttönen) (2015)
- ENGAGE - A Game-based Learning Environment for Middle School Computational Thinking (Kristy Elizabeth Boyer, Philip Sheridan Buffum, Kirby Culbertson, Megan Hardy Frankosky, James C. Lester, Allison G. Martínez-Arocho, Wookhee Min, Bradford W. Mott, Fernando J. Rodríguez, Eric N. Wiebe) (2015)
- Teaching with Tablets (Helen Caldwell, James Bird) (2015)
- 8. Computing (Yasemin Allsop)
- Programmieren als dritte Fremdsprache (Marc Bodmer) (2015)
- To Block or not to Block, That is the Question - Students’ Perceptions of Blocks-based Programming (David Weintrop, Uri Wilensky) (2015)
- A New Culture of Learning: Computing and Next Generations - IFIP Working Conference (1-3 July 2015) (2015)
- Proceedings of the Workshop in Primary and Secondary Computing Education, WiPSCE 2015, London, United Kingdom, November 9-11, 2015 (Judith Gal-Ezer, Sue Sentance, Jan Vahrenhold) (2015)
- Using Interface Design to Develop Computational Thinking Skills (Ana C. Calderon, Tom Crick) (2015)
- A Pilot Computer Science and Programming Course for Primary School Students (Caitlin Duncan, Tim Bell) (2015)
- Exploring Students' Computational Thinking Skills in Modeling and Simulation Projects - a Pilot Study (Natasa Grgurina, Erik Barendsen, Klaas van Veen, Cor J. M. Suhre, Bert Zwaneveld) (2015)
- A Work in Progress Paper - Evaluating a Microworlds-based Learning Approach for Developing Literacy and Computational Thinking in Cross-curricular Contexts (Craig Jenkins) (2015)
- Dr. Scratch - a Web Tool to Automatically Evaluate Scratch Projects (Jesús Moreno-León, Gregorio Robles) (2015)
- Relationships - computational thinking, pedagogy of programming, and Bloom's Taxonomy (Cynthia Collins Selby) (2015)
- Using Interface Design to Develop Computational Thinking Skills (Ana C. Calderon, Tom Crick) (2015)
- ISSEP 2015 - Informatics in Schools. Curricula, Competences, and Competitions (Andrej Brodnik, Jan Vahrenhold) (2015)
- 11. Computing at School in Sweden - Experiences from Introducing Computer Science within Existing Subjects (Fredrik Heintz, Linda Mannila, Karin NygÃ¥rds, Peter Parnes, Björn Regnell)
- 13. Introducing a New Computer Science Curriculum for All School Levels in Poland (Maciej M. Sysło, Anna Beata Kwiatkowska)
- 11. Computing at School in Sweden - Experiences from Introducing Computer Science within Existing Subjects (Fredrik Heintz, Linda Mannila, Karin NygÃ¥rds, Peter Parnes, Björn Regnell)
- Primary Computing in Action (Yasemin Allsop, Ben Sedman) (2015)
- 13. Planning and assessment of computing and computational thinking (Mark Dorling, John Woollard)
- ICER 2015 - Proceedings of the eleventh annual International Conference on International Computing Education Research, ICER 2015, Omaha, NE, USA, August 09 - 13, (Brian Dorn, Judy Sheard, Quintin I. Cutts) (2015)
- On Pre-requisite Skills for Universal Computational Thinking Education (Elizabeth C. Cole) (2015)
- Grounding Computational Thinking Skill Acquisition Through Contextualized Instruction (Hilarie Nickerson, Catharine Brand, Alexander Repenning) (2015)
- Understanding Collaborative Computational Thinking (Bushra Chowdhury) (2015)
- On Pre-requisite Skills for Universal Computational Thinking Education (Elizabeth C. Cole) (2015)
- Hello Ruby - Adventures in Coding (Linda Liukas) (2015)
- Computational thinking - A guide for teachers (Andrew Csizmadia, Paul Curzon, Mark Dorling, Simon Humphreys, Thomas Ng, Cynthia Selby, John Woollard) (2015)
- Pflichtfach Informatik - Bildungsexperten fordern verpflichtenden Unterricht an allgemeinbildenden Schulen (Beate Barrein, Dorothee Wiegand) (2015)
- Learner-Centered Design of Computing Education - Research on Computing for Everyone (Mark Guzdial) (2015)
- Makerspace in der Primarschule (Marcel Jent) (2015)
- 300 Keywords Informationsethik - Grundwissen aus Computer- Netz- und Neue-Medien-Ethik sowie Maschinenethik (Oliver Bendel) (2016)
- From computing to computational thinking (Paul S. Wang) (2016)
- Developing Computational Thinking in Compulsory Education - Implications for policy and practice (Stefania Bocconi, Augusto Chioccariello, Giuliana Dettori, Anusca Ferrari, Katja Engelhardt) (2016)
- Computational Participation - Understanding Coding as an Extension of Literacy Instruction (Quinn Burke, W. Ian O’Byrne, Yasmin B. Kafai) (2016)
- Proceedings of the 47th ACM Technical Symposium on Computing Science Education - Memphis, TN, USA, March 02 - 05, 2016 (Carl Alphonce, Jodi Tims, Michael E. Caspersen, Stephen H. Edwards) (2016)
- Computational Thinking as a Liberal Study (Dave Mason, Irfan Khan, Vadim Farafontov) (2016)
- Computational Thinking as a Liberal Study (Dave Mason, Irfan Khan, Vadim Farafontov) (2016)
- Computational Thinking: I do not think it means what you think it means (Lorena A Barba) (2016)
- Mehr als 0 und 1 - Schule in einer digitalisierten Welt (Beat Döbeli Honegger) (2016)
- 6. Wozu Informatik? (2016)
- 6. Wozu Informatik? (2016)
- Das ist kein Spiel (Jochen Bettzieche) (2016)
- Die Informatik aus der Spielkiste (Andreas Lorenz-Meyer) (2016)
- ICER 2016 - Proceedings of the 2016 ACM Conference on International Computing Education Research, ICER 2016, Melbourne, VIC, Australia, September 8-12, 2016 (Judy Sheard, Josh Tenenberg, Donald Chinn, Brian Dorn) (2016)
- Mixed Methods for the Assessment and Incorporation of Computational Thinking in K-12 and Higher Education (Joshua Levi Weese) (2016)
- Computational Thinking as a Computer Science Education Framework and the Related Effects on Gender Equity (Jon Good) (2016)
- Mixed Methods for the Assessment and Incorporation of Computational Thinking in K-12 and Higher Education (Joshua Levi Weese) (2016)
- Proceedings of the 11th Workshop in Primary and Secondary Computing Education (WiPSCE 2016) - Münster, Germany, October 13-15, 2016 (Jan Vahrenhold, Erik Barendsen) (2016)
- Teacher Feedback on Delivering Computational Thinking in Primary School (Tim Bell, Caitlin Duncan, James Atlas) (2016)
- CTWINS - improving Computational Thinking confidence in educators through paired activities (Richard Millwood, Glenn Strong, Nina Bresnihan, Pamela Cowan) (2016)
- Teacher Feedback on Delivering Computational Thinking in Primary School (Tim Bell, Caitlin Duncan, James Atlas) (2016)
- Informatics in Schools: Improvement of Informatics Knowledge and Perception - 9th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2016, Münster, Germany, October 13-15, 2016 (Andrej Brodnik, Françoise Tort) (2016)
- 3. It´s Computational Thinking! - Bebras Tasks in the Curriculum (Valentina Dagienė, Sue Sentance)
- 4. How to Attract the Girls - Gender-Specific Performance and Motivation in the Bebras Challenge (Peter Hubwieser, Elena Hubwieser, Dorothee Graswald)
- 13. Combining the Power of Python with the Simplicity of Logo for a Sustainable Computer Science Education (Juraj Hromkovic, Tobias Kohn, Dennis Komm, Giovanni Serafini)
- 3. It´s Computational Thinking! - Bebras Tasks in the Curriculum (Valentina Dagienė, Sue Sentance)
- Scalable Game Design - Ein Erfolgsmodell - Kurzfassung des Schlussberichts (2016)
- Teaching Computing Unplugged in Primary Schools - Exploring primary computing through practical activities away from the computer (Helen Caldwell, Neil Smith) (2016)
- Bildung Schweiz 12/2016 (2016)
- Emerging Research, Practice, and Policy on Computational Thinking (Peter J. Rich, Charles B. Hodges) (2017)
- 2. Making Computer Science Attractive to High School Girls with Computational Thinking Approaches - A Case Study (Oshani Seneviratne)
- 4. Computational Thinking as an Interdisciplinary Approach to Computer Science School Curricula - A German Perspective (Jan Delcker, Dirk Ifenthaler)
- 5. Proto-computational Thinking - The Uncomfortable Underpinnings (Deborah Tatar, Steve Harrison, Michael Stewart, Chris Frisina, Peter Musaeus)
- 6. Medical Computational Thinking - Computer Scientific Reasoning in the Medical Curriculum (Peter Musaeus, Deborah Tatar, Michael Rosen)
- 7. Integrating Computational Thinking in Discrete Structures (Gerard Rambally)
- 8. A Computational Approach to Learning Programming Using Visual Programming in a Developing Country University (Ago MacGranaky Quaye, Salihu Ibrahim Dasuki)
- 10. Using Model-Based Learning to Promote Computational Thinking Education (Hong P. Liu, Sirani M. Perera, Jerry W. Klein)
- 11. Teaching Computational Thinking Patterns in Rural Communities (Carla Hester Croff)
- 12. Teacher Transformations in Developing Computational Thinking - Gaming and Robotics Use in After-School Settings (Alan Buss, Ruben Gamboa)
- 13. Computational Thinking in Teacher Education (Aman Yadav, Sarah Gretter, Jon Good, Tamika McLean)
- 14. Computational Thinking Conceptions and Misconceptions - Progression of Preservice Teacher Thinking During Computer Science Lesson Planning (Olgun Sadik, Anne-Ottenbreit Leftwich, Hamid Nadiruzzaman)
- 15. The Code ABC MOOC - Experiences from a Coding and Computational Thinking MOOC for Finnish Primary School Teachers (Tarmo Toikkanen, Teemu Leinonen)
- 16. Assessing Computational Thinking Across the Curriculum (Julie Mueller, Danielle Beckett, Eden Hennessey, Hasan Shodiev)
- 17. Assessing Algorithmic and Computational Thinking in K-12 - Lessons from a Middle School Classroom (Shuchi Grover) (2017)
- 18. Principles of Computational Thinking Tools (Alexander Repenning, Ashok R. Basawapatna, Nora A. Escherle)
- 19. Exploring Strengths and Weaknesses in Middle School Students´ Computational Thinking in Scratch (Kevin Lawanto, Kevin Close, Clarence Ames, Sarah Brasiel)
- 20. Measuring Computational Thinking Development with the FUN! Tool (Sarah Brasiel, Kevin Close, Soojeong Jeong, Kevin Lawanto, Phil Janisiewicz)
- 23. A Future-Focused Education - Designed to Create the Innovators of Tomorrow (Laurie F. Ruberg, Aileen Owens)
- 24. Computational Participation - Teaching Kids to Create and Connect Through Code (Yasmin B. Kafai, Quinn Burke) (2017)
- 2. Making Computer Science Attractive to High School Girls with Computational Thinking Approaches - A Case Study (Oshani Seneviratne)
- Programmiert auf Erfolg (Maximilian Nowroth, Max Haerder) (2017)
- ECDL Module Computing - Syllabus Version 1.0 (ICDL Foundation) (2017)
- ICDL Computing - Learning Material (ICDL Foundation) (2017)
- Misconceptions About Computer Science (Peter Denning, Matti Tedre, Pat Yongpradit) (2017)
- Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, Seattle, WA, USA, March 8-11, 2017 (Michael E. Caspersen, Stephen H. Edwards, Tiffany Barnes, Daniel D. Garcia) (2017)
- Evaluation and Impact of a Required Computational Thinking Course for Architecture Students (Nick Senske) (2017)
- Improving Students' Learning and Achievement in CS Classrooms through Computational Creativity Exercises that Integrate Computational and Creative Thi (Duane F. Shell, Leen-Kiat Soh, Abraham E. Flanigan, Markeya S. Peteranetz, Elizabeth Ingraham) (2017)
- Evaluation and Impact of a Required Computational Thinking Course for Architecture Students (Nick Senske) (2017)
- Eingebettete Systeme - LOG IN 185/186 (2017)
- Einstieg ins Programmieren mit dem Raspberry Pi (Emil Müller, Aegidius Plüss) (2017)
- Einstieg ins Programmieren mit dem Raspberry Pi (Emil Müller, Aegidius Plüss) (2017)
- fnm Magazin 1/2017 (2017)
- Nicht nachdenken, programmieren! (Adrian Lobe) (2017)
- Remaining Trouble Spots with Computational Thinking - Addressing unresolved questions concerning computational thinking. (Peter Denning) (2017)
- International Conference on Computational Thinking Education - Hong-Kong, 13.-15.07.2017 (Siu Cheung Kong, Josh Sheldon, Robert Kwok-yiu Li) (2017)
- Computational Thinking as a Key Competence - a Research Concept (Amelie Labusch, Birgit Eickelmann)
- Computational Thinking as a Key Competence - a Research Concept (Amelie Labusch, Birgit Eickelmann)
- Coding as a Playground - Programming and Computational Thinking in the Early Childhood Classroom (Marina Umaschi Bers) (2017)
- Computational Thinking - A Beginner's Guide to Problem-Solving and Programming (Karl Beecher) (2017)
- ICER 2017 - Proceedings of the 2017 ACM Conference on International Computing Education Research, ICER 2017, Tacoma, WA, USA, August 18-20, 2017 (Josh Tenenberg, Donald Chinn, Judy Sheard, Lauri Malmi) (2017)
- Conceptions and Misconceptions about Computational Thinking among Italian Primary School Teachers (Isabella Corradini, Michael Lodi, Enrico Nardelli) (2017)
- Principled Assessment of Student Learning in High School Computer Science (Eric Snow, Daisy Rutstein, Marie A. Bienkowski, Yuning Xu) (2017)
- Growth Mindset in Computational Thinking Teaching and Teacher Training (Michael Lodi) (2017)
- Conceptions and Misconceptions about Computational Thinking among Italian Primary School Teachers (Isabella Corradini, Michael Lodi, Enrico Nardelli) (2017)
- Lifelong Kindergarten - Cultivating Creativity through Projects, Passion, Peers, and Play (Mitchel Resnick) (2017)
- Coding - Computer + Unterricht Nr. 107/2017 (Stefan Aufenanger) (2017)
- 21st Century Skills
- Einen Rechner braucht es nicht (Christian Kleinhanß)
- Coding-Kenntnisse hamstern (Holger Schmidt)
- 21st Century Skills
- Creating the Coding Generation in Primary Schools (Steve Humble) (2017)
- Informatische Bildung zum Verstehen und Gestalten der digitalen Welt - 17. GI-Fachtagung Informatik und Schule (Ira Diethelm) (2017)
- Zieldimensionen für frühe informatische Bildung im Kindergarten und in der Grundschule (Nadine Bergner, Hilde Köster, Johannes Magenheim, Kathrin Müller, Ralf Romeike, Ulrik Schroeder, Carsten Schulte)
- Zieldimensionen für frühe informatische Bildung im Kindergarten und in der Grundschule (Nadine Bergner, Hilde Köster, Johannes Magenheim, Kathrin Müller, Ralf Romeike, Ulrik Schroeder, Carsten Schulte)
- Analysis of the relation between computational thinking skills and various variables with the structural equation model (Hatice Yildiz Durak, Mustafa Saritepeci) (2017)
- Demystifying computational thinking (Valerie J. Shute, Chen Sun, Jodi Asbell-Clarke) (2017)
- Computational Thinking als internationales Zusatzmodul zu ICILS 2018 - Konzeptionierung und Perspektiven für die empirische Bildungsforschung (Birgit Eickelmann) (2017)
- Lernen und Lehren mit Technologien: Vermittlung digitaler und informatischer Kompetenzen - Erziehung & Unterricht 7&8/2017 (2017)
- Coding als Baustein der digitalen Grundbildung (2017)
- Informatics in Schools: Focus on Learning Programming - 10th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2017, Helsinki, Finland, November 13-15, 2017 (Valentina Dagiene, Arto Hellas) (2017)
- 15. Solving Everyday Challenges in a Computational Way of Thinking (Bernhard Standl)
- 15. Solving Everyday Challenges in a Computational Way of Thinking (Bernhard Standl)
- Schule digital - der Länderindikator 2017 - Schulische Medienbildung in der Sekundarstufe I mit besonderem Fokus auf MINT-Fächer im Bundesländervergleich und Trends von 2015 bis 2017 (Ramona Lorenz, Wilfried Bos, Manuela Endberg, Birgit Eickelmann, Silke Grafe, Jan Vahrenhold) (2017)
- Handbook of Technology Education (Marc J. de Vries) (2017)
- 28. Robotics in Technology Education (Martin Fislake) (2017)
- 28. Robotics in Technology Education (Martin Fislake) (2017)
- Kids & Codes (Christoph Drösser) (2017)
- Regula: erste Schritte ins Programmieren - Grundlagen der Informationstechnik spielerisch lehren und lernen (Armin Ruch) (2018)
- Digitalisierung - Herausforderungen und Chancen für die Schule (Rudolf Minsch, Roger Wehrli) (2018)
- Digitalisierung: Diese sieben Dinge braucht die Schule der Zukunft (economosuisse) (2018)
- Proceedings of the 49th ACM Technical Symposium on Computer Science Education, SIGCSE 2018, Baltimore, MD, USA, February 21-24, 2018 (Tiffany Barnes, Daniel D. Garcia, Elizabeth K. Hawthorne, Manuel A. Pérez-Quiñones) (2018)
- Computational Thinking for All - An Experience Report on Scaling up Teaching Computational Thinking to All Students in a Major City in Sweden (Fredrik Heintz, Linda Mannila) (2018)
- Introducing Computational Thinking through Non-Programming Science Activities (Youwen Ouyang, Katherine L. Hayden, Julie Remold) (2018)
- Effective Models for Integrating Computational Thinking into NYC Elementary Schools - A Proposed Research Agenda (Abstract Only) (Thea Charles, Amber Oliver, Kate Mulloy) (2018)
- Reported Development of Computational Thinking, Through Computer Science and Programming, and its Benefits for Primary School Students - (Abstract Only) (Caitlin Duncan) (2018)
- Computational Thinking for All - An Experience Report on Scaling up Teaching Computational Thinking to All Students in a Major City in Sweden (Fredrik Heintz, Linda Mannila) (2018)
- Hello World 4 (2018)
- Coding kann doch jedes Kind (Fanny Jiménez) (2018)
- Computer Science Education - Perspectives on Teaching and Learning in School (Sue Sentance, Erik Barendsen, Carsten Schulte) (2018)
- 3. Computational Thinking (Shuchi Grover)
- Programmieren in der Primarschule hilft, Probleme eigenständig lösen zu lernen (2018)
- Teachers as Designers of Learning Environments (Alejandro Paniagua, David Istance) (2018)
- Scale or Fail - Moving beyond self-selected computer science education in Switzerland (Alexander Repenning) (2018)
- Schulblatt Thurgau 2/2018 (2018)
- Die Schule der Zukunft und der Sprung ins digitale Zeitalter - Wie sieht eine zukunftsfähige Lernkultur aus, in der die Nutzung digitaler Technologien eine Selbstverständlichkeit ist? (Dominik Petko) (2017)
- Die Schule der Zukunft und der Sprung ins digitale Zeitalter - Wie sieht eine zukunftsfähige Lernkultur aus, in der die Nutzung digitaler Technologien eine Selbstverständlichkeit ist? (Dominik Petko) (2017)
- EdMedia 2018 (2018)
- Evidence of Computational Thinking in the After-School Makerspace from Written Project Documentation (Kevin Oliver, Jennifer Houchins)
- Evidence of Computational Thinking in the After-School Makerspace from Written Project Documentation (Kevin Oliver, Jennifer Houchins)
- Teaching How to Teach Computational Thinking (Anna Lamprou, Alexander Repenning) (2018)
- ICER 2018 - Proceedings of the 2018 ACM Conference on International Computing Education Research, ICER 2018, Espoo, Finland, August 13-15, 2018 (Lauri Malmi, Ari Korhonen, Robert McCartney, Andrew Petersen) (2018)
- Fostering Computational Thinking through Problem-Solving at School (Amelie Labusch) (2018)
- Using Computational Thinking to Transform Elementary Mathematics Instruction (Kathryn M. Rich) (2018)
- A Study on the Assessment of Introductory Computational Thinking via Scratch Programming in Primary Schools (Janne Fagerlund) (2018)
- Decomposition - A K-8 Computational Thinking Learning Trajectory (Kathryn M. Rich, T. Andrew Binkowski, Carla Strickland, Diana Franklin) (2018)
- Fostering Computational Thinking through Problem-Solving at School (Amelie Labusch) (2018)
- Constructionism 2018 - August 20-25, Vilnius, Lithunia (Valentina Dagiene, Eglė Jasute) (2018)
- Hello World 6 (2018)
- Login 189/190 (2018)
- Informatische Kompetenzen in der Grundschule - Sichtweisen und Bausteine (Marco Thomas)
- Informatische Kompetenzen in der Grundschule - Sichtweisen und Bausteine (Marco Thomas)
- Proceedings of the 13th Workshop in Primary and Secondary Computing Education, WiPSCE 2018, Potsdam, Germany, October 04-06, 2018. (Andreas Mühling, Quintin I. Cutts) (2018)
- Co-de - an online learning platform for computational thinking (Zimcke Van de Staey, Tobias Verlinde, Bart Demoen, Bern Martens) (2018)
- A congress for children and computational thinking for everyone (Barbara Sabitzer, Heike Demarle-Meusel) (2018)
- Infusing computational thinking into middle grade science classrooms - lessons learned (Veronica Cateté, Nicholas Lytle, Yihuan Dong, Danielle Boulden, Bita Akram, Jennifer Houchins, Tiffany Barnes, Eric N. Wiebe, James C. Lester, Bradford W. Mott, Kristy Boyer) (2018)
- A curriculum of computational thinking as a central idea of information & media literacy (Andreas Dengel, Ute Heuer) (2018)
- Co-de - an online learning platform for computational thinking (Zimcke Van de Staey, Tobias Verlinde, Bart Demoen, Bern Martens) (2018)
- Digitale Transformation - Beiträge zur Lehrerinnen- und Lehrerbildung 2/2018 (2018)
- Digitale Transformation in Bildung und Schule - Facetten, Entwicklungslinien und Herausforderungen für die Lehrerinnen- und Lehrerbildung (Dominik Petko, Beat Döbeli Honegger, Doreen Prasse) (2018)
- Digitale Transformation in Bildung und Schule - Facetten, Entwicklungslinien und Herausforderungen für die Lehrerinnen- und Lehrerbildung (Dominik Petko, Beat Döbeli Honegger, Doreen Prasse) (2018)
- Do We Really Need Computational Thinking? (Enrico Nardelli) (2019)
- CSU-Staatsministerin Bär fordert „Digitalkunde“ als Pflichtfach ab der Grundschule (Dietmar Neuerer) (2019)
- Should schools teach coding? (Andreas Schleicher) (2019)
- Informatik Spektrum Sonderheft: Bildung und Informatik - Volume 42, Issue 2, April 2019 (2019)
- Wie Mathematik und Informatik im Unterricht voneinander profitieren können - Teil I (Urs Hauser, Dennis Komm, Giovanni Serafini)
- Wie Mathematik und Informatik im Unterricht voneinander profitieren können - Teil I (Urs Hauser, Dennis Komm, Giovanni Serafini)
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