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Computational thinking practices in the science and mathematics classrooms
as proposed by David Weintrop and colleagues

Data Practices
 Collecting Data
 Creating Data
 Manipulating Data
 Analyzing Data
 Visualizing Data

Modeling & Simulation Practices
 Using Computational Models to Understand a Concept
 Using Computational Models to Find and Test Solutions
 Assessing Computational Models
 Designing Computational Models
 Constructing Computational Models

Computational Problem Solving Practices
 Preparing Problems for Computational Solutions
 Programming
 Choosing Effective Computational Tools
 Assessing Different Approaches/Solutions to a Problem
 Developing Modular Computational Solutions
 Creating Computational Abstractions
 Troubleshooting and Debugging

Systems Thinking Practices
 Investigating a Complex System as a Whole
 Understanding the Relationships within a System
 Thinking in Levels
 Communicating Information about a System
 Defining Systems and Managing Complexity
Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education & Technology, 25(1), p. 135
Our research is supported by the Social Sciences and Humanities Research Council of Canada.