Guest editorial
| DOI | https://doi.org/10.1108/ILS-05-2019-139 |
| Published date | 13 May 2019 |
| Pages | 254-265 |
| Date | 13 May 2019 |
| Author | Eric M. Meyers |
| Subject Matter | Library & information science |
Guest editorial
Learning to code, coding to learn: youth and computational thinking
Introduction
Professor Jeannette Wing's provocative and influential paper entitled Computational Thinking
appeared in the March 2006 issue of Communications of the ACM; in the 13 years since,
educators, computer scientists, policy makers, and technologists have been working to define
this conceptual space, measure it, and assess the role that computer science can and should
play in the education of young people. Although Wing is by no means the first person to notice
that computer science can play an important role in developing problem solving capacities in
youth across the curriculum (Papert, 1980;Clements and Gullo, 1984;Harel and Papert, 1990;
diSessa, 2001, to name just a few), her call to arms fuelled increasing research attention and
policy interest (Aho, 2012;Cooper and Cunningham, 2010;Guzdial, 2008; Wang, 2015, Wing,
2008;Wing and Stanzione, 2016). With this special issue of the Journal of Information and
Learning Sciences, we propose that computational thinking (CT) is a generative space residing
between the learning sciences and information sciences, drawing on concepts of cognition and
development (e.g. motivation and self-regulation), the system sciences (e.g. algorithmic
representation and design of data structures) and areas of shared or interdisciplinary concern
and interest (e.g. digital literacy, problem-solving, making and creativity).
But, what is CT? And how does it relate to critical thinking, not to mention pressing issues of
digital literacy, and children's readiness to engage with contemporary digital media? Succinctly,
CT can be defined as “the process of recognising aspects of computation in the world that
surrounds us, and applying tools and techniques from Computer Science to understand and
reason about both natural and artificial systems and processes”(Royal Society, 2012,p.29).
Further definitions, including those offered by the College Board and National Science
Foundation, identify key thought processes and techniques that help us operationalize CT as a set
of practices that can be taught and fostered, including abstraction and pattern generalization;
systematic processing of information; symbol systems and representation; algorithmic notions of
flow and control; structured problem decomposition; iterative, recursive, and parallel thinking;
conditional logic; efficiency and performance constraints; debugging and systematic error
detection (Grover and Pea, 2013). This list shares a number of common points with the
curriculum taught in mathematics and science; however, there clearly are procedures and habits
of mind, such as abstraction and debugging, that are distinctive and not likely to be taught in
general K–12 courses (Wang, 2015). CT has some overlap with general problem-solving
processes that form the basis of information literacy models as well, but the emphasis on
understanding algorithmic flow and symbolic representation suggests significant differences.
Scholars are making the case that CT is its own form of literacy, one that complements other
knowledge domains, but occupies its own place in the curriculum (Barr and Stephenson, 2011;
Guzdial, 2008).
In this editorial article, I will briefly, though not exhaustively, review research from
diverse perspectives on CT, first from educationand the learning sciences, then from library
and information science. I will then opine on the challenges confronting society by applied
computer science that lacks a consideration of diverse human values and propose a way
forward that relies an ethically grounded education in CT. I conclude with brief summaries
of the articles that represent this special issue and additional areas of future consideration
that the editors look forwardto seeing published in this journaland other venues.
ILS
120,5/6
254
Informationand Learning
Sciences
Vol.120 No. 5/6, 2019
pp. 254-265
© Emerald Publishing Limited
2398-5348
DOI 10.1108/ILS-05-2019-139
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