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


(Wednesday 16th, 10:55-12:25)

The emerging concepts of “data science” and “big data” for educational purposes


Organizers


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

PaperTitlePresenter / Co-author(s)
9C1Exploring “white flight” via open data and big dataJames Ridgway (United Kingdom)
James Nicholson (United Kingdom)
Sean McCusker (United Kingdom)
9C2Teaching data science to teenagersAmelia McNamara (United States)
Mark Hansen (United States)
9C3Integrating big data into the science curriculumDaniel Kaplan (United States)
Elizabeth Shoop (United States)
Paul Overvoorde (United States)