This paper is from Session 3A: Developing undergraduate data science programs grounded in statistics
which comes under Topic 3: Statistics education at the post-secondary level
Paper 3A3 (Tuesday 10th, 14:00-15:30)
Challenges and opportunities for undergraduate data science major and minor degree programs
Presenter
- Johanna Hardin (Pomona College, United States)
Co-author
- Nicholas Horton (Amherst College, United States)
Abstract
Recent curricular working groups (e.g., the ASA Undergraduate Guidelines for Statistics Programs and the Park City Math Institute Data Science Guidelines) have provided useful guidance for undergraduate programs in statistics and data science. We review these guidelines, compare and contrast them, and explore successful implementation strategies and problematic hurdles for the teaching of statistics and data science at the post-secondary level. What key emphases from data science (e.g., the increased role of computation and communication) need to be further infused in statistics programs? How can these topics be integrated to ensure that students emerge with the capacity to “think with data”? What are some of the other issues that we need to address to ensure that statistics is interwoven into our data science programs?