January Newsletter - Out With the Old, In With the Plagues


Jilly MacKay


January 31, 2024

Well, we made it precisely two weeks into January before we were all hit by another nursery plague.

I had a conversation with a colleague who’s preparing for their parental leave, and I may have seemed a little apocalyptic when I was talking about the sheer number, intensity, and sustained length of periods of illness that comes from having a child in some form of public care or schooling. I also found myself in a BlueSky thread on the same topic, which was incidentally the first time I felt BlueSky really came alive as a social media for me.

As I write this, my daughter’s nursery room which is usually in the double digits comprised of only her and two other very small children, so I anticipate the next bout of illness imminently. Compounding this we have entered the terrible twos. Parenting life is very stressful at the moment.

So in some ways, work is a welcome respite!

Work Stuff

I am delighted to say that our textbook chapter on Educational Research is now published. As always, I talk a wee bit more about the process over on the publication record. Suffice to say I’m really pleased with this chapter.

The one teaching concept that I now use which I didn’t use two years ago when I wrote the chapter, is the idea of quantitative and qualitative data being different sides of a spectrum of structure, which I talk about in this OER lecture.

We also had a visit from the medical college’s Clinical Education division. It was great to A) meet those folk, many of whom are new since my last dealings with the group, and B) be reintroduced to all the work we do at the vet school. I realised recently that in 2018-2019 I was seconded to work with our Information Services Group, in 2020 we obviously had Covid, and then I was on mat leave. I do feel like I’m getting back to grips with my work at the vet school now, and that’s reassuring.

Stuff from around the web

An interesting article on GitHub’s CoPilot AI which does not hugely inspire confidence regarding the impact of ‘AI’/large language models on code quality.