An Introduction to Computational Thinking

What is Computational Thinking?

Computational Thinking is a problem-solving method that allows concepts from computer science to solve complex challenges. It involves cognitive processes that encourage breaking down issues into smaller and more manageable fragments. Whilst it also involves formulating algorithms, identifying patterns and devising efficient solutions. Computational thinking requires analysing problems in detail to understand them, using detailed and clear ways to identify problems and solutions as well as reasoning for every phase of the process.
There are four parts within Computational Thinking:

  • Decomposition
  • Abstraction
  • Pattern recognition
  • Algorithm design

Decomposition is the idea of breaking down issues into smaller and more manageable fragments. Abstraction is the thought process of focusing only on the important information within the problem. Pattern recognition requires identifying similar issues in the information to identify patterns and organise the data. Finally, algorithm design is an accumulation of all other parts previously stated but also includes testing and debugging.(Brooks, 2023)

Why is it important for Computer Science?

Computational Thinking provides a foundation for computer science and programming. Computer scientists are able to develop their problem-solving skills which allows them to understand systems and better handle data. This enhances the skills needed to create software, algorithms and computation models. Computational Thinking skills are also applicable to everyday life.(kev@innovativeteachingideas.com, 2023)

Why is it important for a career in Cyber Security?

By applying Computational Thinking skills, cyber security professionals can better understand computer systems, networks and software as well as the patterns they display. This can encourage the identification of potential security threats and attacks in a timely manner. Moreover, by using the skills to identify issues it is likely that this will encourage the development of effective security measures such as security protocols and systems to protect data and networks from threats. In addition, the important skills enable the development of algorithms which can influence the creation of a secure way to safeguard data. This can protect sensitive information from unauthorised access. Finally, Computational Thinking allows a way to improve on assessing and managing risks in a systematic approach which enables a more practical approach to issues.