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Computational thinking skills are versatile approaches to problem solving that include:
- Gathering and organizing data to investigate questions and communicate findings
- Expressing procedures as algorithms (that is, a series of logical, precise, repeatable steps that delivers an expected result) to reliably create and analyze processes
- Creating computational models that use data and algorithms to simulate complex systems
- Using and comparing computational models to develop new insights about a subject
We see these practices of computational thinking benefitting cutting-edge research and everyday life. For example, when a hurricane is approaching, a meteorologist on TV may use a computational model to demonstrate the various paths that the storm may take as any number of interdependent variables change. An astrophysicist may similarly use computational thinking practices to develop simulations and new theories about the collisions of black holes.
The implications of computational thinking stands to impact learning across ages and disciplines in K-12 education.
Advocating for computational thinking throughout the K-12 curriculum does not replace or compete with efforts to expand computer science education: on the contrary, it complements them. Where computer science is not yet offered, integrating computational thinking into existing disciplines can empower educators and students to better understand and participate in a computational world. And schools already teaching coding and computer science will benefit from weaving computational thinking across disciplines in order to enrich and amplify lessons that are beyond the reaches of computer science classes.
Read the full article about advancing computational thinking in K-12 education by Colin Angevine at Digital Promise.