August 4, 2020
Version control is an essential element of a reproducible workflow deserving due consideration among the learning objectives of statistics courses. This panel will discuss experiences & implementation decisions of several contributing faculty--teaching different courses at different institutions-- who have successfully integrated git into one or more statistics courses in order to teach version control. The various approaches described highlight lessons learned and implementation strategy based on student audience, course type, software choices, and assessment practices with a goal of providing the audience motivation for why github is needed and demonstrate a range of implementations across a variety of courses and student populations.
- Nick Horton: Welcome and introduction
- Matt Beckman: Motivation (slides; PDF)
- Adam Sullivan: Industry & Academic Preparedness (slides; PDF)
- Hunter Glanz: Git & GitHub Basics (slides? video?)
- Maria Tackett (video): Coming soon...
- Panel: Experiences implementing Git as learning objective in statistics courses
- Mine Cetinkaya-Rundel (video): Common themes (Coming soon...)
- Panel: Q & A
- Preprint (in review): Implementing version control with Git as a learning objective in statistics courses
- eBook: Happy Git and GitHub for the useR by Bryan et al. (link)
- Blog: Teach Data Science by Glanz, Hardin, & Horton (link)
- eBook: Data Computing by Kaplan & Beckman (link)
- Ch 9. Collaboration & Reproducibility with Git
- Appendix. GitHub-RStudio Configuration
- eBook: Reproducibility in Science (link)
- rOpenSci (link)
- GitHub Guides: Hello World
- Cal Poly STAT 431 Git/GitHub setup guide (link)
Matthew Beckman Penn State University mdb268 [at] psu [dot] edu
Hunter Glanz Cal Poly State University hglanz [at] calpoly [dot] edu
Nicholas Horton (Chair) Amherst College nhorton [at] amherst [dot] edu
Adam Sullivan Takeda Pharmaceutical Company Ltd adam.sullivan1 [at] takeda [dot] com