beanz Magazine

Computational Thinking

Randy Robertson on Flickr

The ability to identify patterns, decompose large problems into small parts, develop algorithms to solve problems, and generalize to find solutions.

In certain circles there is a fairly well-known game called fizzbuzz. When played correctly, the outcome looks as follows:

1, 2, fizz, 4, buzz, fizz, 7, 8, fizz, buzz, 11, fizz, 13, 14, fizzbuzz, ...

Can you identify any patterns?

In the its current state, the fizzbuzz sequence likely appears as a hodgepodge of numbers and funny-sounding words. But if we break it into its two main parts, the patterns become much clearer:

Let us start with what I call the fizz portion:

1, 2, fizz, 4, 5, fizz, 7, 8, fizz, 10, 11, fizz, 13, 14, fizz, …

Now consider the buzz part:

1, 2, 3, 4, buzz, 6, 7, 8, 9, buzz, 11, 12, 13, 14, buzz, …

Did you notice that the fizz part of the pattern can be described as counting by one and replacing every third number with the word fizz? Likewise, in the buzz part of the pattern every fifth number is replaced with the word buzz. The original sequence is formed by combining the fizz pattern with the buzz pattern.

Pattern recognition and decomposition are two characteristics of computational thinking, a fundamental skill for computer science. In this case we took a complicated sequence and decomposed it into two strands to help us recognize what numbers are replaced by fizz, and what numbers are replaced by buzz.


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