This is a busy week, so I really don’t want to be spending time updating a shared course that I’m not even teaching next semester… but I am getting to learn more about SSHing into a VM, and that’s legitimately cool.

Reread some feedback from a journal editor after a couple of days, and while I still disagree with it, it’s at least more reasonable than I remembered it being.

I will never not be angry about the term STEAM, even when it’s being used in good faith by people I respect.

We’re getting to the end of the semester here at the University of Kentucky, which is my traditional time to get overly introspective about grading. There’s a lot on my mind at the end of this semester, but one thing that has popped into my head tonight and that I think will be quick to write about is a dilemma that I’m facing this semester, when I’ve had faced more suspicions about student use of generative AI than in any previous semester. By way of context, my class policy is to: 1) discourage student use of generative AI, but 2) begrudgingly allow students to use it, but 3) require that they disclose its use.

For the past couple of years, my colleague Dr. Meghan Dowell and I have been working on a paper on students’ awareness of what data the Canvas learning management system collects (and subsequently makes available to certain stakeholders). I’m a fan of Nick Proferes’s paper [Information Flow Solipsism in an Exploratory Study of Beliefs About Twitter] and have long wanted to do something similar related to LMSs. This is even more Meghan’s area of specialty than mine, though, so I was grateful that she was also interested in the subject and took the lead in turning this idea into reality.

This semester, I have learned that: 1) if I have building toys on my desk, I will turn them into a robot, and 2) if I have a robot on my desk, I will fiddle with it during Zoom meetings.

McSweeney’s content on academia is always darkly hilarious, and this is no exception.

It’s uncomfortable for me to think about how close my “digital traces” research is to surveillance and YOLO data mining.

I love having a co-author who can provide the theoretical framing to turn my weird data from a dark corner of the internet into an interesting argument.

Glad I already have tenure or else I’d be a lot more worried about what my colleagues think of me holding my numb fingers under running water in the break room, still dressed in four layers of warm and reflective clothing and before I’ve had a chance to fix my helmet hair.

Between my kid’s nascent interest in search engines and my students’ using generative AI despite my discouraging it, I’m thinking a lot this week about directly teaching epistemology as a foundation for other concepts.

Currently feeling some Chidi Anagonye levels of nihilism about grading.

This morning, I’m realizing (and somewhat to my horror) that some of my reflection on whether to change up one of my classes essentially mirrors the ed psych debates about constructivism versus direct instruction that I found so intolerable in grad school.

Back in 2020-2021, I made the decision to pivot from Twitter as a research site in case data ever became less available—and so I could focus more on right-wing online spaces. It was a good call but still hilariously mistaken at the same time.

I teach in a tech-focused program, and I think it’s reasonable to ask how we’re going to address generative AI in our curriculum, but I still resent the expectation that we must jump on this bandwagon simply because it’s there.

My most recent research compliance completion certificate was clearly thrown together in a few lines of HTML. Not only does that feel especially phoned in, but it also makes it harder to save for my records, which is the only useful aspect of one of these certificates.

Before writing what I want to write, I want to make a few things clear. Teaching is an important and noble profession, I love being a teacher, and it’s possible (and often easy) to distinguish between better and worse ways of teaching. With that out of the way, I want to start off this post by arguing that teaching is less of “a thing” than learning is. That is, learning is the real phenomenon here, and teaching is sort of an auxiliary practice that aims to support learning but can’t ever quite be the same thing.

Teaching my project-focused WordPress class keeps me humble: I answer so many student questions with “I don’t know how to do that, but I know it’s possible. Let’s figure it out together.”

In our big content management systems class project this semester, students are knocking it out of the park in a way that makes me proud of them but also reassures me that maybe I understand this stuff despite no formal training after all.

Sometimes I feel like I’m nagging my data science students when I tell them to use function x in R instead of almost-identical function y. Other times, I remember that function y has awful output that makes grading their work a pain, and I stop worrying.

Some switch has recently flipped in my brain so that I can hand out Bs, Cs, and worse without being anxious about it. I still have real concerns about grading as a concept, but I’ve stopped worrying about taking off points as though I’m the one being penalized.

I do not believe in using AI detection software, but I reserve the right to be annoyed by the students whom I suspect of taking advantage of that belief.

I’m currently at the 2024 conference for the Society of the Scientific Study of Religion, where the Mormon Social Science Association always organizes a number of panels. (I presented on a reactionary Mormon Twitter hashtag earlier today!). MSSA traditionally has a Saturday evening no-host dinner, and as long as I’ve attended (okay, only since 2021), we’ve relied on a foodie board member to find a place for us to eat. Rick isn’t here this year, and somehow that got turned into my becoming responsible for finding us a restaurant to meet, eat, and chat at.

Wild to read this so soon after finishing Character Limit, because I’m getting very similar vibes.

That feeling when data you’re coding is just so bizarre that you don’t know what to make of it. Online communities are a heck of a thing to study.