Computational Thinking

Abstract

An introduction to computational thinking that traces a genealogy beginning centuries before the digital computer. A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation; eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, “computational thinking” has become part of the K–12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview, tracing a genealogy that begins centuries before digital computers and portraying computational thinking as pioneers of computing have described it. The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as “computers”) who performed complex calculations as teams engaged in CT long before electronic computers. The authors identify six dimensions of today's highly developed CT—methods, machines, computing education, software engineering, computational science, and design—and cover each in a chapter. Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.

A Systematic Review of Computational Thinking Approach for Programming Education in Higher Education Institutions

“…According to Denning and Tedre [2] (pp.10), the historical perspective of computational thinking exists even before the emergence of electronic computers. However, since the discussion of CT by Wing [12]-centred on the fundamental knowledge for computer programming, it has fast become popular in the computer science domain [11,1].…”

“…Computational thinking (CT) has the capacity to improve programming education by building the problem-solving and algorithmic skills of learners [1]. CT involves having thinking skills, i.e., "ways of thinking and practicing that are sharpened and honed through practice"-Denning and Tedre [2] (pp.6). Among other skills, CT are envisioned to make the developing of programming and problem-solving skills a flexible experience.…”

Media Literacy Education in the Age of Machine Learning

“…In the first decades of modern computing, from the 1950s to 1960s, computing education was primarily the purview of higher education institutions, and K-12 educational initiatives were few and far between. A number of pioneering initiatives for teaching computing in schools did arise, among them the Little Man Computer instructional model of computers, the Dynabook laptop computer for children, and the Logo programming language for education (Guzdial & Boulay, 2019;Denning & Tedre, 2019). Yet, aside from Logo, none of them succeeded to bring computing to K-12 schools at a large scale.…”

“…As large-scale roll-outs of bringing programming to K-12 schools faltered for various reasons, starting from a severe lack of teachers who knew programming, the balance shifted to "computer literacy" courses (Denning & Tedre, 2019). Computer literacy was conceived as skills of using computer programs and applications, including word processing, basic databases, sketchpads, and rudimentary expert systems.…”

“…The latest wave of bringing computing to schools started in 2006, with the K-12 computing education catchphrase "fluency" being replaced by "computational thinking" (Wing, 2006;Guzdial, 2015;Denning & Tedre, 2019). Now the time was ripe for action: parents, policymakers, politicians, and teachers were all experiencing the computer revolution first hand, and were eager to support bringing computing education to schools (Mannila et al, 2014).…”