Computational thinking: a key skill in the 21st century
The spread of coronavirus is leaving a wide swath of economic damage in its wake. In the shutdown phase alone, up to 53 million US jobs were vulnerable—a term used to encompass permanent layoffs, temporary furloughs, or reductions in hours and pay. While leisure and hospitality accounted for most of the earliest layoffs and furloughs, the share from industries such as retail trade, manufacturing, nonessential healthcare, and professional services has been growing. It is estimated that up to 57 million US jobs are now vulnerable, including more and more white-collar positions.
The emergence of CT has accompanied the rise of AI (Artificial Intelligence), which could make 65% of current workplace skills irrelevant in five years.
So could CT be the way to bridge that gap between hard and soft skills? Yes, because not everybody will be in need of hard programming proficiency.
Computational thinking is more than just computer science. It focuses on problem-solving and has four pillars: decomposition, pattern recognition, abstraction, and algorithms.
- Decomposition: Breaking down larger problems, processes, or data and complexities into smaller more manageable parts.
- Pattern recognition: Looking for and identifying patterns or trends to help understand, make a connection, or to distinguish differences, as a way to negotiate understanding.
- Abstraction: The process of ignoring or removing the less important details to better understand a problem or find a solution/negotiate meaning.
- Algorithm Design: Developing a process for problem-solving that includes step by step instructions and for working through a problem or completing a task/challenge.