Why computational thinking

We start by defining the problem: We want to calculate the total cost of the doughnuts. My honest reaction when seeing this problem statement is to grab my phone and start adding the cost doughnut by doughnut.

Computational thinking offers us a far better, less laborious, and joint-saving way. We can decompose the problem into smaller steps. Once we know this, we can calculate the total cost. Now, with an organized list of the number of doughnuts and cost per type, we recognize that each item on the list follows the same pattern , which allows us to construct an equation to calculate the total cost for each doughnut type.

Because we know National Cupcake Day is coming up and that treats never fail to lift my spirit, how can we leverage this work to help our colleagues similarly create a budget for those? With the equations used to solve the problem, we can abstract a template with two formulas for calculating the total cost. The formula — with the noise and complication from the initial problem removed — is now an accessible tool.

We can then further extend the transfer of knowledge from this experience to ensure a reliable output every time by constructing an algorithm so that we and others can replicate it for more sweet celebrations. As was hopefully represented in this computational thinking example, this process is a shift in how we approach problem solving. With a formulaic process, we can navigate complexity and stay focused on what is important, without losing site of the solution amongst all the noise.

There are four key techniques cornerstones to computational thinking:. Each cornerstone is as important as the others. They are like legs on a table - if one leg is missing, the table will probably collapse. Correctly applying all four techniques will help when programming a computer. Our working definition for computational thinking divides key concepts of computing into two categories: foundations and practices. Foundations are the cognitive processes necessary to engage in computing.

Practices combine the foundations with additional skills and knowledge to solve an applied problem, whether that end result is a computer program, a better comprehension of a biological ecosystem, or an increased appreciation of how human migration patterns relate to geographical locations. To start building those computational thinking skills, exploring programming is a surefire way to do it. Of course, this is just one of many reasons why kids should learn to code.

If you or your child need an extra incentive, though, it lies in these incredibly versatile thinking skills! The mindset and experience needed to succeed as a programmer has value well outside the STEM world. By building their computational thinking, kids will become more effective communicators, planners, critical thinkers, and problem-solvers.

So what are you waiting for? There are plenty of great coding courses to help you get started today! Virginia started with iD Tech at the University of Denver in and has loved every minute since then!

A former teacher by trade, she has a master's in education and loves working to embolden the next generation through STEM. Outside the office, you can usually find her reading a good book, struggling on a yoga mat, or exploring the Rocky Mountains.

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