This is a session of Topic 9: Technology in statistics education



The emerging concepts of “data science” and “big data” for educational purposes
Organizers
- Robert Gould (United States) : Session chair
- Hadley Wickham (United States)
Abstract
Introductory statistics courses are typically designed to develop an understanding of statistical inference in the context of data collected from (typically small) formal studies. However, our cultures and economies are surrounding by “streams” of data whose collection is guided not by the intent of individuals, but instead by algorithms. The vast size of these data sets, their dynamic nature, and their complex structure require a new set of tools that combine statistics and computer science. This session will raise questions about how the structure and content of the statistics curriculum may need to be altered to teach students to live and work in the data deluge, and hopefully provide some answers too.
Papers
Paper | Title | Presenter / Co-author(s) |
9C1 | Exploring “white flight” via open data and big data | James Ridgway (United Kingdom) Sean McCusker (United Kingdom) James Nicholson (United Kingdom) |
9C2 | Teaching data science to teenagers | Amelia McNamara (United States) Mark Hansen (United States) |
9C3 | Integrating big data into the science curriculum | Daniel Kaplan (United States) Paul Overvoorde (United States) Elizabeth Shoop (United States) |