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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.