July 27 – August 1, 2019
JSM (the Joint Statistical Meetings) is the largest gathering of statisticians and data scientists held in North America. Topics range from statistical applications to methodology and theory to the expanding boundaries of statistics, such as analytics and data science.
Tuesday, July 30
Data Science Education at the School Level
8:30 – 10:20 AM, CC-102
Rob Gould, Andee Rubin, Michelle Wilkerson, William Finzer, Anna Fergusson
Given data science, it makes sense that data science education should emerge as a discipline and concern. Universities have begun to build robust offerings and degree programs in data science.
But what about data science education at the school level? What does it look like? What is even possible? This panel will discuss research, practice, and development in data science education from middle grades through high school, and how that connects with what’s happening at the university. We’ll see what students and teachers can do to prepare for future courses in data science, or for a future as a citizen in a democracy where data science has a lot of influence.
Wednesday, July 31
Developing a Platform for Data Exploration
8:30 – 10:20 AM, CC-Four Seasons 1
For data and statistics to permeate K–14 classrooms, teachers and students need ubiquitous and seamless access to age-appropriate tools and environments designed for learning. In this talk we use the free, browser-based, open source Common Online Data Analysis Platform (CODAP) as a springboard for thinking about what such technology might look like and how it might come about. We look at ways that multiple linked data representations can help learners make sense of data. We consider some of the ramifications of giving students control over data structure. Finally, we demonstrate integrations of CODAP that take advantage of its flexibility as a platform.