Building Bridges for Data Science Education

• Activity Number: 388 - Building Bridges for Data Science Education
• Type: Invited
• Date/Time: Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics and Data Science Education
• Author(s): Mine Cetinkaya-Rundel* and Michael Posner* and Jeff Forbes* and Andrea Danyluk*
• Companies: Duke University and Villanova University and Duke University and Williams College
• Keywords: data science; interdisciplinary; collaboration; computing; education

Abstract

The ability to manipulate and understand data is increasingly critical to discovery and innovation, and many academic institutions have recently experienced the emergence of data science as the field that focuses on preparing undergraduates for the new data-driven era. Data science is inherently interdisciplinary and encompasses elements of statistics, computer science, and domain-specific knowledge, which suggests that data science curricula that are comprehensive and successful require interdisciplinary conversations and collaborations. This panel features faculty from computer and statistical science departments from research universities and liberal arts colleges who have been involved in such conversations and collaborations. The intended audience for this panel is everyone who is interested in what the two disciplines can learn from each other regarding building data science courses and curricula as well as those interested in building such collaborations.