Module in Computational Thinking

Introductory guide to computational thinking

Computational thinking is a problem-solving approach based on fundamental thinking processes that incorporate four cornerstones: decomposition, pattern recognition, abstraction, and algorithm (Wing 2006).

In the first step, complex issues are broken down into smaller components and then it’s essential to find some similarities among other problems. The next move focuses on the most important components of the problem and ignores less relevant details. And the last stage provides a step-by-step solution to the complex issue. The planning phase of this process can be compared to thinking computationally, while the actual programming is like implementing directions (BBC 2020).

Computational thinking is a part of our daily life. Every morning when we leave for work, we always take a few steps to get there. Check the weather, dress appropriately, plan the quickest route, and perhaps grab a coffee or tea along the way. And this is called thinking computationally.

Throughout our lives, we have used computational thinking multiple times to solve different problems, but every time we face an entirely new dilemma, we forget to follow the same steps. The computational thinking module taught us to think in a different way about how we approach obstacles in our lives and that we can handle new challenges the same way as we solve them every single day.

This knowledge is especially important for me right now when I prepare for an intense academic year full of new challenges. While learning Python, JavaScript, and tools I've never studied before, decomposition, pattern recognition, abstraction, and algorithm will be immensely beneficial. Thinking computationally will enable me to turn new complex problems into simple ones and solve them efficiently.

In my experience as a journalist, I often encounter complex challenges, some of which seem insurmountable. Understanding how to break them down and come up with efficient solutions will be key to my future career. I am also confident that I will use the skills I gained during this module throughout my whole life- confidence and the ability to cope with complex issues as well as persistence in dealing with difficult challenges.

introductory to computational thinking

An introductory guide to Computational Thinking

Computational thinking is a problem-solving approach based on fundamental thinking processes that incorporate four cornerstones: decomposition, pattern recognition, abstraction, and algorithm.

Short biography of a famous computer scientist

Biography of Barbara Liskov - one of the first women in the United States who was awarded a PH.D. from the Computer science department and who won the A.M. Turing Award, the highest honor in computer science

Short reflection on what I have learnt

Computational thinking is a familiar aspect of our everyday life, but most people are unaware of it. I have always associated it with programming and until recently, I believed that it was useful mostly to those pursuing careers in computer science and technology