Thinking about computational thinking

Abstract

Jeannette Wing's call for teaching Computational Thinking (CT) as a formative skill on par with reading, writing, and arithmetic places computer science in the category of basic knowledge. Just as proficiency in basic language arts helps us to effectively communicate and in basic math helps us to successfully quantitate, proficiency in computational thinking helps us to systematically and efficiently process information and tasks. But while teaching everyone to think computationally is a noble goal, there are pedagogical challenges. Perhaps the most confounding issue is the role of programming, and whether we can separate it from teaching basic computer science. How much programming, if any, should be required for CT proficiency?We believe that to successfully broaden participation in computer science, efforts must be made to lay the foundations of CT long before students experience their first programming language. We posit that programming is to Computer Science what proof construction is to mathematics, and what literary analysis is to English. Hence by analogy, programming should be the entrance into higher CS, and not the student's first encounter in CS. We argue that in the absence of programming, teaching CT should focus on establishing vocabularies and symbols that can be used to annotate and describe computation and abstraction, suggest information and execution, and provide notation around which mental models of processes can be built. Lastly, we conjecture that students with sustained exposure to CT in their formative education will be better prepared for programming and the CS curriculum, and, furthermore, that they might choose to major in CS not only for career opportunities, but also for its intellectual content.

Defining a New 21st Century Skill-Computational Thinking: Concepts and Trends

“…(Barr, Harrison & Conery, 2011;Basawapatna et al, 2011;Berland & Wilensky, 2015;Bers, 2010;ISTE & CSTA, 2011;Denning, 2012;Furber, 2012;Guzdial, 2008;Kafai, 2016;Kilpeläinen, 2010;Lu & Fletscher, 2009;NAACE, 2014;Papert, 1996;Snapp & Neumann, 2015;Williamson, 2015;Williamson, 2016) ies. Basawapatna et al, 2011;Berland & Wilensky, 2015;Bers, 2010;ISTE & CSTA, 2011;Furber, 2012;Grover & Pea, 2013;Guzdial, 2008;Kilpeläinen, 2010;Lu & Fletscher, 2009;National Research Council, 2012;Papert, 1996;Park & Jeon, 2015;Wilensky & Reisman, 2006;Williamson, 2016;Wing, 2006) 1.4. Data organization 1 0 9 8 18 (Barr, Harrison & Conery, 2011;Berland & Wilensky, 2015;Bers, 2010;Guzdial, 2008;Kafai & Burke, 2014;Kilpeläinen, 2010;Papert, 1996;National Research Council, 2010;Sengupta et al, 2013;…”

“…Data organization 1 0 9 8 18 (Barr, Harrison & Conery, 2011;Berland & Wilensky, 2015;Bers, 2010;Guzdial, 2008;Kafai & Burke, 2014;Kilpeläinen, 2010;Papert, 1996;National Research Council, 2010;Sengupta et al, 2013;Williamson, 2016) 1.5. Basawapatna et al, 2011;Berland & Wilensky, 2015;Guzdial, 2008;Williamson, 2016) (Barr & Stephenson, 2011;Bundy, 2007;Denning & Freeman, 2009;Denning, 2012;Grover & Pea, 2013;Guzdial, 2008;Jacobson & Wilensky, 2006;Lu & Fletscher, 2009;Miller & Settle, 2011;National Research Council, 2012;Papert, 1996;Snapp & Neumann, 2015;Williamson, 2016;Wing, 2006;Wolz et al, 2011;Yadav et al, 2014) 2.2. Programming processes 0 0 9 4 13 (Aho, 2012;Basawapatna et al, 2011;Denning, 2012;Kafai, 2016;Lu & Fletscher, 2009;Wing, 2008) ies As observed in Table 2, CT was defined mostly within the context of problem solving, technology and thinking.…”

“…Under the topic of personal traits, concepts such as individual skills, cognitive factors and perspective were included (DeSchryver & Yadav, 2015;diSessa, 2001;Furber, 2012;Jacobson & Wilensky, 2006;Kafai & Burke, 2014;Lu & Fletscher, 2009;Park & Jeon, 2015;Snapp & Neumann, 2015) and specifications on personal traits were limited. It was considered that this was due to the fact that CT is a novel topic that requires further studies.…”

Improving the Computational Thinking Pedagogical Capabilities of School Teachers

“…Mishra and Yadav (2013) have argued that computational thinking goes beyond typical human-computer interactions within the school curriculum; instead, they argued that human creativity could be augmented by computational thinking, in particular with the use of automation and algorithmic thinking (Van Dyne & Braun, 2014). However, researchers argue despite the best efforts to articulate that computational thinking is more than just "programming", the misconception that the two are the same remains (Lu & Fletcher, 2009;Qualls & Sherrell, 2010).…”

Programming in Slovak Primary Schools

“…Recently, an interesting study by Selby (2013) Wing and several other authors call for incorporating computational thinking into formative education of children (Wing 2008), (Lu and Fletcher, 2009), (Lee et al, 2011) and (Hu, 2011). In some countries the focus is still on implementing informatics education only into secondary school, see e.g.…”