Along with Rachel Schwartz, Catherine Newman, Jaime Oaks, and Sarah Flangan, I am an author on a preprint reviewing common technologies and teaching practices in teaching computation to biologists. In it, we review some of the technologies that educators might choose to use to deliver a course in computational biology. We also review the evidence for various strategies for teaching, including various ways to incorporate live coding and active learning into class.

I’m immensely proud of this paper for a few reasons. Weirdly, the inspiration for this paper came from Twitter. In the linked thread, we really saw that a lot of early career folks are struggling to keep up with the glut of educational technologies on the market. What is RStudio Server? When is that what I want, compared to a JupyterHub? Do I need to pay for hosting to teach computational biology?

This year’s iEvoBio theme was “Enabling the next generation of computational biologists.” So I decided (as the current head of iEvoBio) to put a little money into getting speakers to have this discussion at the meeting. Organically, this discussion became a meeting, and the meeting became a paper.

Something that I think is really cool about this manuscript is that the authors are from different types of institutions (R1s, PUIs) that attract different types of students. And so we decided to pay special mind to the challenges our real students have faced. What happens for students who can’t afford the latest and greatest laptop? Or who might go on deployment over the weekend and be without their personal computer? All of the challenges we discuss in this paper are real. The solutions we cite are solutions we use.

This manuscript is currently a preprint. If you see things that you think should change, you can make a difference! On the right hand side of the screen, you should see a link to post comments. We welcome your feedback! This is an F1000 preprint, and the reviews will be visible to readers as they become available, which is pretty cool.