I’ve started teaching my University of Trento class, Applied Statistics for High-throughput Biology. In contrast to my usual classes of 20-60 MPH students, this one is 7 PhD students. Such a small class size feels like such a luxury, and allows me to explore some new teaching methods while I develop this course. It is the first course I will offer with all materials online using Github, with recorded going online as well. Since I want my students to learn R programming, and how to write reports using literate programming, I’m creating all the lectures using R Markdown, which blends R programming with the Markdown wiki markup language, sort of like the markup language used by Wikipedia (but simpler). This might be a form of “eating my own dogfood“, i.e. using what I’m trying to sell to my students. It’s nice because anything that I present in class, the students can see exactly how I did.
My motivations for putting the course online are twofold:
- airing my course to the world definitely adds motivation to do the best I can in preparing for each class
- since my salary and Fulbright award are publicly funded by taxpayer dollars, I feel a responsibility to make as much of my work public as I can.
The U.S. National Institutes of Health has formalized this latter responsibility for sharing of data and publications generated from federally-funded research. I’m supportive, and my only criticism would be that some of the policies don’t go far enough, such as allowing publications to be behind a paywall for a year plus any “online early access” time before becoming publicly available. I try to favor favor publishing in open-access journals when I can, although as an individual early-career researcher I feel like I can only do that so much, and where the fit and impact of the journal are comparable to alternatives.
I’ve made a summary of these and other teaching materials I’ve put online at www.waldronlab.org/teaching.