Problem Solving Using Computational Thinking
Learn to solve complex problems using computational thinking strategies and real-world case studies.
Learn to solve complex problems using computational thinking strategies and real-world case studies.
Master the art of computational thinking to tackle complex problems effectively. This beginner-friendly course, taught by Chris Quintana, introduces key concepts such as abstraction, decomposition, pattern recognition, and algorithm design. Through real-world case studies in areas like airport surveillance, epidemiology, and human trafficking, you'll learn to apply computational thinking to diverse challenges. Gain practical problem-solving skills applicable across various fields, even without prior programming experience.
4.6
(1,239 ratings)
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English
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What you'll learn
Understand the core concepts of computational thinking
Apply abstraction and decomposition to break down complex problems
Develop pattern recognition skills for identifying trends and similarities
Design algorithms to solve problems systematically
Evaluate and refine solutions using computational thinking principles
Analyze real-world case studies using computational thinking approaches
Skills you'll gain
This course includes:
2.6 Hours PreRecorded video
9 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This course introduces students to computational thinking as a problem-solving approach applicable across various disciplines. The curriculum covers key computational thinking concepts including abstraction, problem identification, decomposition, pattern recognition, algorithm design, and solution evaluation. Through a series of real-world case studies in areas such as airport surveillance, epidemiology, and human trafficking, participants learn to apply these concepts to complex problems. The course emphasizes practical application, with students developing their own solutions to real-world issues. A final project allows learners to demonstrate their mastery of computational thinking in addressing a significant challenge.
Foundations of Computational Thinking
Module 1 · 2 Hours to complete
Case Study: Airport Surveillance and Image Analysis
Module 2 · 2 Hours to complete
Case Study: Epidemiology
Module 3 · 2 Hours to complete
Case Study: Human Trafficking
Module 4 · 1 Hours to complete
Final Project
Module 5 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Innovative Learning Design Expert
Dr. Chris Quintana is an Associate Professor at the Marsal Family School of Education at the University of Michigan, specializing in the intersection of learning sciences, human-computer interaction, and computer science. His research emphasizes learner-centered design processes aimed at developing educational technologies that enhance learning experiences. Dr. Quintana leads various initiatives, including the Learning Experience Design Certificate Program, where he explores the integration of immersive technologies and software-based scaffolding to support learners in engaging with new practices effectively.His course offerings on Coursera, such as "Exploring Generative AI for Learning Design" and "Learning Experience Design: Development and Evaluation," reflect his commitment to advancing educational methodologies. Through these courses, he equips educators and learners with innovative strategies to leverage technology in educational settings, ultimately fostering a more engaging and effective learning environment.
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4.6 course rating
1,239 ratings
Frequently asked questions
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