With Gemma Mojica, Heather Barker, Taylor Harrison, Hollylynne Lee, & Asli Mutlu (NC State University), Rick Hudson (University of Southern Indiana)
This session will highlight how data science ideas can be infused in introductory statistics courses in ways that support inferential reasoning. By providing opportunities for students to create and test models through simulations, instructors can assist students in building strong arguments in which they evaluate evidence to make inferences. Participants will engage in tasks that use hands-on approaches and CODAP, a free web-based data visualization and analysis tool, to build and test models, conduct simulations, and use different visualizations and measures to support inferences. The session will include a focus on choosing and designing tasks that provide modeling approaches and support inferential reasoning. Discussion will focus on opportunities modeling and simulation based activities provide for engaging students in inferential reasoning and how instructors can use different techniques in their courses to support students’ argumentation. Activities shared were designed in an NSF-funded project and are useful in a variety of courses.