Lynette Hudiburgh and Lisa Werwinski (Miami University)
Schedule
Wednesday, May 17 at 1:00 p.m. to Thursday, May 18 at noon
Abstract
Data visualization is a perfect vehicle to teach students to summarize data graphically and numerically, as well as the importance of context in statistics. We believe that it is imperative to provide students in introductory statistics courses with the tools to create their own data visualizations. In so doing, we equip our students with the ability to make sense of data around them, to understand how displays can be misleading, and to become critical consumers of data and statistics. The data visualization group project, which includes the following six components: group contract, data set submission, data viz sketch/plan, rough draft, presentation, and final draft, is designed to expose students to this important field and, hopefully, to encourage them to pursue further coursework in statistics and/or data visualization.
The goals for this project are:
- To promote active learning and equip students with a relevant and marketable skill: In today’s age of big data, the ability to visualize data and communicate their story is a crucial skill to possess.
- To build communication skills: Students must present and communicate their process and results.
- To facilitate team-building and group work: Students will be required to work within a team in future work environments.
- To develop critical thinking and statistical thinking; encourage students to think deeply about data and information.
- To avoid misleading visualizations: Communicate the story of the data in a truthful, insightful, and enlightening manner.
- To encourage creativity and engender appreciation for the application of statistical thinking to analyzing and exploring data.
- To engage students that may not traditionally be enthusiastic about taking a statistics course.
During the first part of the workshop, participants will be given a brief presentation outlining the underlying principles associated with data visualization and the project. Conference participants will form teams of three to four people to work through the project as students. Teams will be able to select from five data sets that we provide. Each group will share their data visualization project so that we can debrief the experience from a student perspective. The second part of the workshop will focus on pedagogical issues such as implementation, adaptations to fit different class types (face-to-face, online, etc…), scaffolding, and assessment. Past student projects will be shared. Participants will be provided with copies of all project related materials.