#### Computational Thinking Resources

Students need methods for problem solving that can be applied to their future STEM career or prepare them for college study. Whether a student’s career path involves biology, transportation, or sales doesn’t matter--all those things often involve solving big problems, dealing with big data sets and creating solutions. A skill set in problem solving using Computational Thinking opens doors for anyone in any area.

In her 2006 article, entitled Computational Thinking, Jeanette Wing argued that “computational thinking is a fundamental skill for everyone, not just for computer scientists. To reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability.”

## Collection Contents

### Decomposition

by Janet Pinto

The resources in this collection will aid in teaching the concept of decomposition to your students. The late Stanford University Professor George Pólya once said, \"If you can\'t solve a problem, then there is an easier problem you can solve: find it.\" This advice can be applied to any problem. For example, how does one go about eating an elephant? One mouthful at a time! This goofy analogy actually provides great insight into the first step of problem solving through Computational Thinking. Big, complex problems are comprised of smaller, and more easily solved subproblems or tasks. The process/strategy of logically identifying these smaller problems and determining how to use the combined solutions to solve the bigger problem is called decomposition.
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### Algorithm Design

by Janet Pinto

Algorithms are step by step instructions to get something done or the set of rules describing how something works. A recipe, or a set of dance steps, or the storyboard for an animation are algorithms. This collection includes resources that will help in teaching algorithm design to your students.
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### Pattern Recognition

by Janet Pinto

This collection includes resources that will be helpful in teaching students the concept of Pattern Recognition. Being able to recognize patterns is a fundamental step in the process of problem solving with computational thinking because the patterns help you determine what operations can and need to be done. This is critical in moving forward in computational thinking, especially if the goal is utilizing computers to automate and streamline a process. If the same operation occurs again and again, it may be able to be entered once and repeated.
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### Abstraction and Pattern Generalization

by Janet Pinto

This collection includes resources you may use when teaching this concept to your students. The key to abstraction is to be able to identify and filter out or ignore the details not necessary to solve the problem. From there, a model (equation, image, word, simulation, etc.) can be developed to represent all the important variables. A variable is a changing value that can be represented by a number, letter, word, blank, image, etc. Often, the value of one variable will determine, or be dependent upon, another. In these examples, you can see how the value of the second variable, or input, is dependent on the value of the first variable or input. Abstraction allows you to create a generic representation of a problem.
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