A major component of Reedy Creek's Digital Sciences magnet theme is Computational Thinking. So, what is Computational Thinking?
What are the components of Computational Thinking?
Explicit series of steps and procedures that can be followed with reproducible results.
Algorithms are like recipes. If you know what ingredients you’ll need, what temperature the oven should be set at, and in what order and how to combine the various ingredients, your finished product should turn out the same each time.
Observing and analyzing data, situations, or a series of events to understand repeating elements or series of elements.
Pattern recognition is like waking up later than normal to try to get some more sleep. After arriving at school tardy every time you wake up later, you recognize that changing your schedule will determine whether or not you are on time.
Abstraction is the ability to gain universally true insights from a specific example. This happens by removing unneccesary information or material until core insights can be discovered. For example, you might draw a circle to represent a ball. The important characteristic was that the ball was round, so you abstracted it into a circle.
Abstraction is like using shapes to represent more detailed figures. (i.e. instead of ) You are removing some of the detail to get to a core truth -- a representation that still communicates your idea.
Decomposition is breaking down a complex idea or subject into smaller component parts.
Decomposition is like taking apart a completed LEGO structure until you just have a collection of different LEGO bricks.
Want to learn more about Computational Thinking? Visit the CT Student Resources Page!
Why is it important for us to learn Computational Thinking? Visit the Why CT? Page
Text Source: The Friday Institute, 2016 https://place.fi.ncsu.edu/course/view.php?id=54