Computational Thinking

Computational Thinking

1. Abstraction

   • For example we don't need to know when the dog barks.
     • A dog barks.
   • Removing unnecessary detail in a problem to simplify it.

2. Decomposition

   • Breaking down a problem into smaller, more manageable parts.
   • Solving a crime. Decomposed steps: 'what crime was committed when the crime was committed where the crime was committed what evidence there is if there are any witnesses if there have recently been any similar crimes'.
   • It is important in problem solving. This is because trying to solve a large problem all at once is more difficult than solving one step at a time.

3. Pattern Recognition

   • Identifying repeating elements and grouping them together.
   • Repeat two times: move left, move right (2).

4. Algorithms

   • Set of step by step instructions to solve a problem.
     • A structured English algorithm uses short, structured sentences to express the instructions.
   • Flow chart
     • Diamond
       • Decision
         • A question that can be yes or no.
     • Rectangle
       • Process
         • Something that happens.
     • Rectangle with smooth sides.
       • Terminator
         • Start and end of a flow chart.