Computational Thinking in K–12

By Shuchi Grover, Roy D. Pea. 2013

1,110 citations recorded by the source corpus.

Subfields: Computer Science Applications, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/0244fa3e5129b1532c98418f91c90c6a0fa54120

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In Computer Science Applications

In Developmental and Educational Psychology

Citations in the corpus

Which cognitive abilities underlie computational thinking? Criterion validity of the Computational Thinking Test (2017, background): “While CT involves thinking skills to solve problems algorithmically (e.g., Brennan & Resnick, 2012; Grover & Pea, 2013), intelligence (i.e., general mental ability or general cognitive ability) involves primarily the ability to reason, plan and solve problems (Gottfredson, 1997).”
Designing for deeper learning in a blended computer science course for middle school students (2015, methodology): “Deeper learning is increasingly seen as an imperative for helping students develop robust, transferable knowledge and skills for the twenty-first century.”
Demystifying computational thinking (2017, background): “An exact definition of CT, however, remains elusive (Barr, Harrison, & Conery, 2011; Grover & Pea, 2013).”
Constructionist Gaming: Understanding the Benefits of Making Games for Learning (2015, background): “…shift toward constructionist gaming that is propelled by several developments, including the initiative to promote computational thinking (Grover & Pea, 2013; Wing, 2006), a need to broaden participation in computing (National Research Council, 2011), and a wider emergence of a…”
Defining Computational Thinking for Mathematics and Science Classrooms (2016, background): “A number of recent definitions have been proposed for computational thinking without a consensus emerging (Grover and Pea 2013).”
A validity and reliability study of the computational thinking scales (CTS) (2017, background): “…that it contains continuity by getting help from the computing and computers in the solution of the complex problems (e.g. Barr and Stephenson 2011; Grover and Pea 2013; Lee et al. 2011; Sengupta et al. 2013; Wolz et al. 2011), it is very distinguishing in many levels in the abstraction and…”