After one year of shadowing Professor Elspeth Garman, I’ve taken over lecturing the Mathematics course to the first-year undergraduates studying Biochemistry at the University of Oxford.

A little over ten years ago I was a class tutor on this course and always liked it, partly because it is a challenge: I think many of the students do not expect there to be an explicit maths course, yet biology is getting more and more quantitative. I stopped shortly after my first child was born and jumped at the chance to get involved again.

This year was, of course, a challenge given the Covid pandemic, so the lectures had to be recorded using Panopto, which is the University’s online lecture platform. That in turn meant the lecture notes had to be electronic so they needed converting from OHP (overhead projector) slides. OHPs are good for mathematics as you can cover bits up, you can draw on them during the lecture and, crucially for maths, they are portrait whereas Keynote/Powerpoint slides are landscape.

During my degree, the lecturer would often do write maths on a never-ending roll of acetate on the overheard projector – when they needed more room they would turn a handle and more acetate would roll up. Just like a roller chalk board.

Why am I saying all this? Well, it is to make the point that mathematics, in particular algebra, is really a *portrait* subject and so doesn’t work, to my mind, on conventional *landscape *slides.

After much thought I decided to use jupyter-notebooks. The advantages of these are

- they can be portrait and you just keep on scrolling (like a website)
- within the cells you can write Markdown and also MathJax, which is a subset of the mathematical typsetting language in LaTeX.
- it would be easy to plot graphs since I could write MatPlotLib/Python code that draws inline graphs
- I could convert the notebooks to LaTeX and then render them, thereby automatically creating lecture notes from the notebooks.
- there are options for interactivity e.g. animating graphs, using HTML graphs, adding links etc.

So I ended up making the jump from OHP slides to jupyter-notebooks. Although the notebooks are currently stored in a private GitHub repo, I hope to make them openly available, with an appropriate licence, in the future. An example from the slide introducing differentiation is shown below.

In the next posts, I’ll describe my experience of using jupyter-notebooks and the feedback I’ve got from the students.