Demystifying computational thinking

By Valerie J. Shute, Chen Sun, Jodi Asbell-Clarke. 2017

1,254 citations recorded by the source corpus.

Subfields: Computer Science Applications, Developmental and Educational Psychology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/10a69c008fa0c9a37b2bb398c85b11feeb4ada4a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

1. Daniel Duckworth
2. Young Hoan Cho
3. Tim Friedman
4. W. Schulz
5. J. Fraillon
6. John Ainley

In Developmental and Educational Psychology

1. Young Hoan Cho
2. W. Schulz

Citations in the corpus

• Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education (2022, background): “…improving computational thinking (CT), a set of skills including decomposition, abstraction, algorithm design, debugging, testing/simulation, heuristic reasoning, and generalization, is being accentuated to understand and use AI effectively to solve problems (Shute et al., 2017; NRC, 2010).”
• IEA International Computer and Information Literacy Study 2018 Assessment Framework (2019, positive): “More recently, Wing’s (2006) article on CT has been regarded by researchers as the catalyst, or at least as a common point of reference, for the re-emergence of interest in CT (see, for example, Barr and Stephenson 2011; Bower et al. 2017; Grover and Pea 2013; Shute et al. 2017; Voogt et al. 2015).”