Since my decision to eschew keeping a timelog while on sabbatical, I’m wondering how I can be reflective about my “work” in a qualitative (rather than quantitative) way. One possibility is by writing a periodic blog post; I’m unimaginatively naming the series “Sabbatical Diary”. So what did I do last week related to my role in academia as a teacher-scholar?
I’ve started to learn Category Theory. When I stumbled across theoretical biologist Robert Rosen’s work about how to abstract what makes a system “alive”, I had significant trouble following the math. I deemed it to be Set theory because I recognized the symbols used when I learned rudiments of set theory way back in secondary school. I now recognize that Sets are simply one type of entity in the broader Category Theory. I’m returning to this because a mathematician friend has come up with a potential way to quantify emergent systems and I want to figure out if this abstract math can be operationalized to study chemical systems of interest to which I can provide microscopic data. Being on sabbatical, I have both the time and motivation to tackle this for now; I might give up if it does not look promising. One has to know when to cut one’s losses and move on.
In the mornings, I’ve been working my way through a textbook on Category Theory (by Spivak). I have to read very slowly soaking in the definitions and translating in my mind what the abstract symbols mean. These were relatively straightforward in the beginning, but by Friday morning, I was starting to run into trouble when I encountered homomorphism sets. I had a vague notion of what these were, but kept moving forward. Then I encountered pullbacks (fibre products) and was stymied. I caved and called up a genAI chatbot to give me concrete examples and some intuitive notions of how to think about these abstractions.
My use of genAI chatbots thus far has mostly been in chemistry, my field of expertise. I’ve been exploring its capabilities (which are improving as they evolve) as an aid in teaching and research. Most of my “experimenting” is poking around how it might help student learn chemistry – how it might be useful and how it might mislead. My working hypothesis is that if you have an expertise in an area, you can effectively leverage genAI’s capabilities to automate or synthesize tasks at hand; you also have the ability to quickly extract genAI’s ideation capabilities pruning out the useful nuggets and discarding the chaff. Conversely, the novice superficially interacts with genAI to get “surface” knowledge and can’t tell when or if they are being bamboozled. Worse, I suspect using genAI gives my students the illusion of knowledge – which is shattered when some of them take an in-class closed-book exam.
This morning I needed more genAI help as I started trying to understand monoids. Asking genAI to give me practical examples in chemistry is helping. That being said, I can see that part of my challenge is that many of the definitions in Set theory that I worked through last week haven’t really sunk into my long-term memory. I know these only superficially rather than deeply. It’s also why I’m having trouble moving forward. I laughed at myself as I recall the many times I’ve told students they need to memorize definitions because these are the building blocks of the terminology we will use in chemistry. If you don’t have these at your fingertips, you will stumble a lot like a blind person in the dark as we advance into subsequent concepts that build on these definitions. We’ll see if I can practice what I preach. I’m impatient and want to quickly get to the point to see whether this background will actually be useful in my research. (I am skimming over some parts in my reading and not working through the harder exercises. Just like some of my students.)
Two hours per day is about what I can handle on Category Theory before my brain feels fried. I also need time to digest some of the information I’m learning and let my brain do some consolidation when I’m asleep. The rest of my mornings last week were spent reading lighter material, usually but not exclusively education-related. I’ve also resumed writing more blog posts this month; I think I’ve gotten to the point where I couldn’t care less that armies of bots are scraping my writing to train commercial genAI models. I think writing regularly (without genAI help) is useful to me as a skill and in clarifying my thoughts.
My afternoons last week were spent on trying to tie up the many loose ends on a research project. I want to write up a paper that incorporates the work of one of my research students who will be applying to grad school next year, so it will be nice if she can have a peer-reviewed paper in the bag on her CV when she is applying. When attempting to consolidate the work into a coherent and publishable story, one always finds that certain threads need to be nailed down, in my case by doing further computational experiments. So I’ve been setting up jobs, running them, and doing data analysis. I feel I’m getting closer to a coherent story, and the question is when enough is enough. Research is inexhaustible. You pull on one thread and it leads to three more.
Okay, that’s it for Diary entry #1. I don’t know if there will be more. I do know that I have many more thoughts swimming in my head.