computational thinking

computational thinking

1. pattern recognition

   • involves finding the similarities or patterns among small, decompone of the four cornerstones of Computer Science. It osed problems that can help us solve more complex problems more efficiently.
   • classification, which attempts to assign each input value to one of a given set of classes (for example, determine whether a given email is "spam" or "non-spam"). However, pattern recognition is a more general problem that encompasses other types of output as well.

2. abstraction

   • one of the four cornerstones of Computer Science. ... Abstraction is the process of filtering out – ignoring - the characteristics of patterns that we don't need in order to concentrate on those that we do. It is also the filtering out of specific details. People also ask
     • allows us to create a general idea of what the problem is and how to solve it. The process instructs us to remove all specific detail, and any patterns that will not help us solve our problem. This helps us form our idea of the problem. This idea is known as a 'model'.
   • Computer languages can be processed with a computer. An example of this abstraction process is the generational development of programming languages from the machine language to the assembly language and the high-level language.

3. algorithmic

   • expressed as or using an algorithm or computational procedure.
   • always unambiguous and are used as specifications for performing calculations, data processing, automated reasoning, and other tasks. As an effective method, an algorithm can be expressed within a finite amount of space and time, and in a well-defined formal language for calculating a function.

4. Decomposition

   • one of the four cornerstones of Computer Science. It involves breaking down a complex problem or system into smaller parts that are more manageable and easier to understand. The smaller parts can then be examined and solved, or designed individually, as they are simpler to work with.