COMPUTATIONAL THINKING
Although the concept of computational thinking originated from computer science, it has however been
extended to other fields of study such as economics, Arts, mathematics, physics etc (Mishra and Yadav 2015).
it has become a ubiquitous concept, influencing scholars and researchers from other
fields of study (Bundy 2007). This is because computational thinking is a problem solving skill, a systematic approach
to solving problems.It involves breaking down seemingly difficult problems into smaller pieces so that they can be understood
by humans and solved by computers. Computers are literal with instructions thus the need for breaking
down instructions into smaller pieces. (Mooney and lockwood, 2017)
There are several components of computational thinking, they include:
- Decomposition:
- this involves taking apart problems into smaller pieces. Complex problems are simplified by dividing them into smaller sub-units such that they are easier to manage.
- Abstraction: entails removing irrelevant details and focusing on the details that matter. It involves allowing the relevant detail to represent the other details, to generalize (wing 2010). For example, a calendar is an abstraction of time, we focus on the date relevant to us while eliminating other dates
- Pattern recognition:
- entails finding similar patterns in different objects, identifying common elements in problems or systems, what problems have in common, and using previous results to decide(Woolard and sellby 2013)
- Algorithm:
- This is a step-by-step solution to solving a problem, it is formulating rules to follow to solve a problem (landauer 2020)
THE IMPORTANCE OF COMPUTATIONAL THINKING IN COMPUTING
The application of computational thinking in the field of computing is important, Computational thinking comes before programming problems must be broken down into smaller pieces when working on a project. The most important task to focus on in building a software or carrying out a project, is to conceptually solve the problem before translating it into code.Breaking down the problem into smaller units and solving the problem conceptually before translating it into a programming language will ensure accuracy.The field of computing is laden with daunting problems, programming languages which can be intimidating, but with this problem-solving skill one is able to overcome the phobia associated with this field(Davies 2008). Thinking through a problem first before attempting to solve it, to results to precision. Precision is a very important factor in programming, being able to effectively express a problem in a natural language aids precision in writing the code and eventually solving the problem. Pseudocodes has been provided for expressing the problem. precise expression of the problem ensures the codes are without errors. (Olsen 2005)