The Lab Under The Stairs - Introductory Project - 2.04

The Lab Under The Stairs - Introductory Project

2.04 - Computational Thinking

Part 1 - Terminology and Definitions

Computational Thinking is the most important skill that you can have entering the Engineering field. It is the set of skills and abilities that allow engineers to solve problems ranging from very basic to incredibly complex.

Today your task is to do some research into computational thinking and be ready to illustrate it with some examples.

Please be ready to answer the following questions:

Please use this BBC article on Computational Thinking to answer the following questions:

Explain the differences between Decomposition, Abstraction, Pattern Recognition, and Algorythms

Use the following video about solving problems with Computational (and Design) Thinking to answer the following questions:

How did the engineers at Google use Abstraction and Pattern Recognition to improve how Pegman works?

Part 2 - Algorithms

Algorithms are a key part of Computational Thinking. They are the systems that make decisions in computer systems. Listen to the following podcast from 99% Invisible about what algorithms are and how they affect your life. Use this podcast to answer the following questions:

What are some examples of algorithms that can affect your life that the podcast uses?
How do these examples decompose human traits and activities into numbers to be fed into the algorithm?

The Age of the Algorithm - 99% InvisibleOn April 9, 2017, United Airlines flight 3411 was preparing to take off from Chicago when flight attendants discovered the plane was overbooked. They tried to get volunteers to give up their seats with promises of travel vouchers and hotel accommodations, but not enough people were willing to get off the flight. So United ended up

Part 3 - Decomposing Problems

Check out the following video from EngineerGuy about the deconstructed process of manufacturing a pop can. Be ready to snwer the following questions:

What part of the process best illustrates the idea of deconstructing a problem?
In what way does the process resemble an algorithm?
What terms did the video use that you were not familiar with?

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