3D: Expanding Data Investigations to Integrate Data Science Practices and Processes

Abstract

The goal of this session is to highlight how data science practices and processes can be integrated into courses that use data-intensive investigations. Statistics education experts often recommend that instructors provide opportunities for students to use a four-phase or five-phase investigative cycle to investigate data. In our NSF-funded project, we built on the work of these experts to expand such frameworks to include the practices, processes and dispositions used by data scientists and other professionals who work with large data. We will share a six-phase Data Investigation Process framework that incorporates data science practices and processes into existing statistics education frameworks, and share a guide to unpack detailed considerations for each phase that can be used to guide thinking while engaged in an investigation and be used by instructors and curriculum developers to make decisions about instruction and curricular materials. This interactive session is appropriate for anyone who engages learners in data investigations and/or wants to learn about how data science practices and processes can be incorporated into courses where data is investigated.

Participants will discuss frameworks they use to support their students in exploring and investigating data. Participants will also engage with a large data set to consider key aspects of a Data Investigation Process and guide using CODAP, a free web-based data visualization and analysis tool. Discussion will focus on how instructors can incorporate data science practices and processes into their existing courses.