Problem Solving in the Digital Age: Getting Started with Computational Thinking and Design

Overview

In the Information Age, problems look different. Information comes at us faster than ever before, and our ability to solve problems depends on us being able to make sense of and synthesize this information. We must also design new solutions using all available technology and tools.

Digital-age problem solving combines three key skills and concepts essential to understanding and solving problems in the information age: data literacy, design thinking, and computational thinking. Data literacy is the ability to analyze, interpret, and tell stories using complex sets of data. Design thinking is the ability to understand problems and develop creative solutions. Computational thinking is the process of expressing solutions so that humans and computers can understand them.

Throughout this MOOC-Ed, you'll have the opportunity to dig into digital-age problem solving, engage with its component skills and concepts, and learn how to integrate them into your instructional practice. This course will not be heavy on coding, and you won't need to know any code going in - it will focus on how to integrate digital-age problem solving in a practical way into your classroom.

Syllabus

Unit 1: What is Digital Age Problem Solving?
In this unit, you'll learn about the course design and course requirements, and have a chance to meet your fellow participants. You'll also learn about the three primary components of digital-age problem solving: computational thinking, design thinking, and data literacy.

Unit 2: Identifying Problems
In this unit, we'll introduce the first phase of the design process: "Understanding the Context". We'll focus on the computational thinking skills of data collection, analysis, and representation. You'll also have the opportunity to explore these concepts on your own, share with the group, and brainstorm applications to your practice.

Unit 3: Making Sense of Problems
This unit will transition from identifying problems to breaking them down in order to determine possible solutions. We'll focus on the "Defining the Problem" phase of the design process, with a specific focus on the computational thinking skills of problem decomposition, abstraction, and parallelization. You'll experience these skills by completing a simulated activity with a problem that you select, and you'll have an opportunity to brainstorm how you can use these concepts in your classroom.

Unit 4: Creating Solutions
Now that we know how to identify contexts and break down problems, the next step is to begin creating solutions. In this unit, we'll focus on the "Creating Solutions" phase of the design process, with a focus on the computational thinking skills of parallelization, algorithm development, automation, and simulation. You'll experience these skills in simulations, and discuss how these concepts can be integrated into your classroom.

Unit 5: Assessing Solutions
This final unit will transition to the “Evaluate, Reflect, Revise” phase of the design process, with a focus on the computational thinking skills of simulation and automation, along with a revisiting of data collection and analysis. It will also serve as a capstone for the course, allowing you to reflect on what you've learned and connect back to the beginning of the design cycle.