I am prepping a new Intro to Data Science course, the core of which will be R for Data Science.
My ~30 students will typically have no programming background, and I'd like to avoid any stumbling blocks I can. At the same time, I think that collaboration, open science, and reproducible research are or should be necessary components of the class, and that the virtues of version control are not to be underestimated.
But I'm concerned that the stumbling blocks of Git will throw many off base - and frankly, my own limited proficiency in this won't help. One possibility is to use other repositories (such as the Open Science Framework), which serve the goals of publicly sharing docs and fostering reproducible science, but are less focused on sharing and improving code.
So there are fa number of possibilities: One is to require all students to set up GitHub accounts, another is to have students work in teams (and require GitHub proficiency from only one student in each group), another is to discuss GitHub as one repository-system among many tools for reproducible, collaborative research, still another is to focus just on the OSF,
and the last is to omit discussion of this stuff altogether. (Regardless, students will be using the Slack platform and Google Docs for other collaborative work).
Thanks so much for your thoughts - Kevin