Associate Professor, School of Education
Problem Solving Using Computational Thinking
What You'll Learn
- Recognize Computational Thinking concepts in practice through a series of real-world case examples.
- Develop solutions through the application of Computational Thinking concepts to real world problems.
5 Modules
10 Hours
2 hrs per module (approx.)
Rating
About Problem Solving Using Computational Thinking
Have you ever heard that computers "think"? Believe it or not, computers really do not think. Instead, they do exactly what we tell them to do. Programming is, "telling the computer what to do and how to do it."
Before you can think about programming a computer, you need to work out exactly what it is you want to tell the computer to do. Thinking through problems this way is Computational Thinking. Computational Thinking allows us to take complex problems, understand what the problem is, and develop solutions. We can present these solutions in a way that both computers and people can understand.
The course includes an introduction to computational thinking and a broad definition of each concept, a series of real-world cases that illustrate how computational thinking can be used to solve complex problems, and a student project that asks you to apply what they are learning about Computational Thinking in a real-world situation. This project will be completed in stages (and milestones) and will also include a final disaster response plan you'll share with other learners like you.
This course is designed for anyone who is just beginning programming, is thinking about programming or simply wants to understand a new way of thinking about problems critically. No prior programming is needed. The examples in this course may feel particularly relevant to a High School audience and were designed to be understandable by anyone.
You will learn:
-To define Computational Thinking components including abstraction, problem identification, decomposition, pattern recognition, algorithms, and evaluating solutions
-To recognize Computational Thinking concepts in practice through a series of real-world case examples
-To develop solutions through the application of Computational Thinking concepts to real world problems
Skills You'll Gain
- Analytical Thinking
- Computational Thinking
- Critical Thinking
- Decision Making
- Graph Algorithms
- Problem Solving
What You'll Earn
- Certificate of Completion:
- Certificates of completion acknowledge knowledge acquired upon completion of a non-credit course or program.
Welcome Message
Welcome to Problem Solving Using Computational Thinking, a beginner-friendly course that includes an introduction to computational thinking and a broad definition of each concept, a series of real-world cases that illustrate how computational thinking can be used to solve complex problems, and a student project that asks you to apply what they are learning about Computational Thinking in a real-world situation. This abbreviated syllabus description was created with the help of AI tools and reviewed by staff. The full syllabus is available to those who enroll in the course.
Course Schedule
Module 1: Foundations of Computational Thinking
- Reading: Welcome and Syllabus
- Reading: Help Us Learn More about You!
- Reading: Contributor Acknowledgements
- Video: Welcome to Computational Thinking
- Video: Example: Making a Cake
- Video: Introduction to the Graphic Organizer
- Reading: Introduction to the Graphic Organizer
- Graded Assignment: Foundations of Computational Thinking Practice Questions
- Discussion Prompt: Real-World Applications of Computational Thinking
- Reading: Would you like to plan your learning journey with Michigan Online?
- Graded: Foundations of Computational Thinking Quiz
Module 2: Case Study: Airport Surveillance and Image Analysis
- Reading: Introduction to Airport Surveillance Case-Study
- Video: Image Analysis: Importance of Computational Thinking - Part 1
- Discussion Prompt: Image Analysis: What Would You Do?
- Video: Image Analysis: Importance of Computational Thinking - Part 2
- Discussion Prompt: Other Applications
- Video: Image Analysis: Abstraction and Algorithms
- Reading: Airport Surveillance Case-Study Check-In 1
- Video: Image Analysis: Algorithms, Optional Advanced Video
- Video: Image Analysis: Evaluating Solutions
- Reading: Airport Surveillance Check-In 2
- Video: Image Analysis: Problem Identification and Decomposition
- Graded Assignment: Airport Surveillance Practice Questions Set 1
- Graded Assignment: Airport Surveillance Practice Questions Set 2
- Graded: Airport Surveillance Case-Study Quiz
Module 3: Epidemiology
- Reading: Introduction to Epidemiology Case-Study
- Video: Epidemiology: Introduction and Problem Identification
- Discussion Prompt: Using Computational Thinking in Public Health
- Video: Epidemiology: Problem Identification Part 2
- Video: Epidemiology: Abstraction and Decomposition
- Reading: Epidemiology Case-Study Check-In 1
- Reading: Up Next: Rafael's Algorithm
- Video: Epidemiology: Algorithms and Evaluating Solutions - Part 1
- Video: Epidemiology: Algorithms and Evaluating Solutions - Part 2
- Discussion Prompt: Understanding the Problem
- Reading: Epidemiology Case-Study Check-In 2
- Video: Epidemiology: Conclusion
- Graded Assignment: Epidemiology Practice Questions
- Reading: Stay in touch on University of Michigan online courses
- Graded: Epidemiology Case-Study Quiz
Module 4: Case Study: Human Trafficking
- Graded Assignment: Next Case: Potential Applications of Computational Thinking to Human Trafficking
- Reading: Introduction to Human Trafficking Case-Study
- Video: Human Trafficking: Importance of Computational Thinking
- Video: Human Trafficking: How Computational Thinking May Apply - Part 1
- Video: Human Trafficking: How Computational Thinking May Apply - Part 2
- Reading: Human Trafficking Case-Study Check-In
- Graded Assignment: Human Trafficking Practice Questions
Module 5: Final Project
- Reading: Introduction to the Final Project
- Reading: Final Project Part 1. Background and Context
- Reading: Final Project Part 2: Graphic Organizer and Project Justification
- Reading: Final Project Part 3: Project Justification
- Reading: Final Project Part 4: Algorithm depiction
- Reading: Course Feedback
- Reading: Create innovative learning environments for students with Introduction to Learning Experience Design
- Reading: Keep Learning with Michigan Online
- Graded: Final Project
Grading Policy
Learners must earn an 80% for an overall passing grade. There are three quizzes worth 45% of your final grade and a final project worth 55%.
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Beginner Level
No prior experience required
