As our technologies have rapidly developed and manipulating those technologies has emerged as a key college- and career-ready skill, teaching students how to program, question, and manipulate digital devices has become commonplace in our schools.  But coding is the application of learning. Before students can effectively perform these tasks, they must understand the concepts behind that application.

Computational Thinking is the prerequisite skill for understanding the technologies of the future. By explicitly teaching, and allowing space for the development of, computational thinking, teachers can ensure that their young students are learning to think in a way that will allow them to access and understand their digital world. Teaching computational thinking, in short, primes students for future success. Furthermore, it can be integrated into existing routines and curricula.

BBC outlines four cornerstones of computational thinking: decomposition, pattern recognition, abstraction, and algorithms.

  • Teaching Decompostion: Teaching decomposition to young learners means that students are invited into problem-solving scenarios.
  • Teaching Pattern Recognition: Pattern recognition, as a cornerstone of computational thinking, begins with the basic ABAB pattern creation that is taught in the primary grades and extends to more complex layers of thinking.
  • Teaching Abstraction: Abstraction is focusing on the information that is relevant and important. It involves separating core information from extraneous details.
  • Teaching Algorithms: Algorithmic thinking involves developing solutions to a problem. Specifically, it creates sequential rules to follow in order to solve a problem. In the early grades, kids can learn that the order of how something is done can have an effect.

Read the full article about developing computation skills by Kristen Thorson at Getting Smart.