With Johanna Hardin (Pomona College), Victoria Woodard (University of Notre Dame), & Nicholas Horton (Amherst College)
In a seminal paper, Nolan and Temple Lang (2010) argued for the fundamental role of computing in the statistics curriculum. In the intervening decade the statistics education community has acknowledged the importance of computational skills to statistics and data science. There remains a notable gap, however, between our classroom use of the computer as a tool and the importance of computational thinking as a skill to be honed. We propose focusing on the computer as part of the thinking process and not only a tool for implementing mathematical theory. In this breakout session we will discuss the how and why of computational thinking as an important aspect of the statistical classroom; brainstorm activities and structures for providing students practice; and discuss how to assess whether or not students have successfully attained an ability to think computationally in parallel with implementation of statistical techniques.
Participants will have the opportunity to engage in breakout-sessions on:
- What aspects of computational thinking that are most important?
- What activities help students develop better statistical computational thinking?
- How can we assess the students’ level of computational thinking?
We hope participants leave with:
- The sense that the computer provides a mechanism for students to experience the entire statistical analysis cycle and to deepen their understanding of fundamental statistical concepts such as variability, inference, and design.
- At least one idea for how to scaffold more computational thinking into the statistics classroom.
- At least one idea for how to assess computational thinking