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# e-Learning Modules

e-Learning Modules

In this self-paced learning experience, we will take an in-depth look at each of the seven computational thinking strategies separately. This professional development resource is designed to work flexibly with educators and their demanding schedules.

## e-Learning Module Overview

Each module should take 10–15 minutes and includes:

1. Pre-test
3 questions
2. Video
5-8 min
3. Post-test
3 questions
4. Certificate

## e-Learning Module Guide

A variety of professional learning resources and exercises have been developed to increase educator proficiency in applying computational thinking practices to classroom instruction while also deepening understanding of computational thinking.

## Computational Thinking

Computational thinking isn’t so much about what computers do, but how they do it. This module provides an introduction to the seven core problem-solving strategies that comprise computational thinking and gives you the tools you need to bring this 21st century skill into your classroom, no matter what curriculum you’re teaching.

## Developing Algorithms

From following a recipe to getting ready in the morning, algorithms are sets of step-by step instructions on how to complete a given task. This module discusses how, through developing algorithms, humans can think like computers by creating detailed sets of instructions that produce an intended result.

## Finding Patterns

From natural science to computer science, we can find examples of patterns visually anywhere we look. In this module we’ll see how the computational thinking strategy of finding patterns can help your students find the root cause of any given problem and plan for the future.

## Building Models

Whether it’s a draft outline, a mathematical model or a 3D prototype, the strategy of building models is all about visualizing data, and using the power of computers to highlight the problems and make predictions before events happen in real-life.

## Analyzing Data

By analyzing data, we can identify connections between things or people. In this module, we’ll talk about analyzing different types of data across every academic discipline and how this computational thinking strategy helps our students understand, make meaning of, and even predict real-world outcomes.

## Collecting Data

This module covers how you can use the computational thinking strategy of collecting data in your classroom to engage your students in a whole new way. We’ll discuss what data is and why collecting data is an essential skill that our students will need to solve the problems of tomorrow.

## Abstracting Complexity

The word “abstract” means many different things, but in the world of computational thinking, abstraction is all about problem-solving. In this module, we’ll discuss how the computational thinking strategy of abstraction gives students the skills to solve many problems with one solution.

## Decomposing Problems

When faced with big projects, it’s easy to get caught up on the weeds or try to put things off until the last minute. This module covers why the computational thinking strategy of decomposing problems is so important—it teaches our students that they can tackle any problem by breaking it down into manageable pieces.

## e-Learning Module Guide

A variety of professional learning resources and exercises have been developed to increase educator proficiency in applying computational thinking practices to classroom instruction while also deepening understanding of computational thinking. Successful use of this professional learning guide will result in educators being able to:

• Define computational thinking as a problem-solving process.
• Explain how computational thinking strategies can help break down complex problems.
• Identify opportunities for students to express their content knowledge using computational thinking.
• Provide multiple examples of how computational thinking impacts our daily lives.