This spring, I taught an undergraduate class on chess engines. I probably learned more than any of my students.

As a senior in college, I was the instructor, lecturer, grader, master of ceremonies, and grand poobah of COLL 110: Artificial Intelligence for Chess, 6-7 P.M. every Tuesday for the whole semester. In theory, I had a faculty advisor, but he was busy most of the time, so at the end of the day, it was my rodeo and I got to figure it all out on my own. I thought it was a great experience!

I’m writing this post for a few reasons: first, I want to write down the things I wish that I had known before I started teaching, in the hopes that other soon-to-be teachers might take this to heart. The other reason is to compile my own thoughts on the matter, since I’ll possibly revive this class in the future, and want to have some notes while it’s fresh in my mind.

You’re not even their second priority

If you’re teaching a topic, you’re probably really passionate about it (unless, of course, the department forced you to teach the class). At the very least, I am. Chess engines are cool. Lucky for me, students taking a COLL course get little in the way of credit for the class, so most of my pupils were also pretty stoked about it. At the end of the day, though, they’re not getting a Ph.D. in this stuff, and they’ve got half a dozen other classes on top of work, family, friends, and this weekend’s party to think about.

To an instructor, this tends to manifest as an air of boredom with the whole topic. Often, the students aren’t actually bored! They just don’t have the time or energy for the topic that I do.

The fix, I think, is to meet students where they are. The hard (and rewarding) part of teaching a class is that I needed to digest reams of material into brief, easily-comprehensible components. I have the patience to trawl through uncommented C++ code and ancient forum posts to figure out how to build a good chess engine, but the students shouldn’t need it.

I’m not a hundred percent certain of the exact mechanisms of how, yet. In my experience, I learn the most when I struggle; if a student can shortcut through all the hard parts on, for example, an assignment, they’re not going to learn very much. On the flip side, when most students struggle, they just give up. Somehow I need to make assignments which thread the needle between being too hard to solve and too easy to learn anything.

Students have wildly varying backgrounds

Chess engines are a relatively niche topic in computer science, so I was quite surprised to see that my class section was completely full at the start of the semester. It seems as though most of the students had been clickbaited by my mention of AI in the title, which is more a callout for classical artificial intelligence than it is for the modern machine-learning approaches.

Although a handful of students dropped the course, I was eventually left with about a dozen students whose experience and programming skill varied wildly. Some of my students had finished little more than an introductory computer science course, while others were more qualified than I was.

This presents a fundamental problem: how do I come up with a curriculum which is complex enough to excite the experienced students without completely losing the less experienced ones? The cynical answer is “you can’t,” but I did give it a fair attempt, and I think it turned out OK. Typically, I tried to integrate a mix of skill levels into my lectures; for instance, when discussing the representation of squares and directions, I spent a few minutes explaining how they could be modeled with torsors, but not so long that I would lose the students who neither knew nor cared about group theory.

Assignment design is harder. I tried to give interesting challenges by leaving bonus tasks on every assignment, and for the final project, I gave a choose-your-own-adventure assignment which allowed students to pick a task that matched their skill level. However, I’m not convinced that I perfected this approach, so I will need to think more deeply on how do design “multi-level” projects for a mixed student body.

Engagement falls off in the first ten minutes

COLL 110 was a standard lectures-and-assignments college class - I lectured during our scheduled meeting time, then students did their projects on their own. Having tried this, I think that this is just not the future of education. This mode of teaching is designed mostly for the lecturer’s convenience, but it’s a terrible way to foster student understanding.

The fundamental reality is that it’s impossible to listen actively for a long period of time. It was even worse in my case: I was teaching a blow-off class at the end of the day, so students were already tired and didn’t feel any pressure to keep up. The net result was that only about half of my students were really paying attention at a time, which is pretty bad if you want them to actually learn anything.

I’m certain that I will need to use a different format for lessons in the future. Flipped classrooms are popular these days, so I might try that, but I also feel that pre-recorded lectures are a little soulless. I might try a hybrid approach, integrating lectures with assignments.

In terms of engagement, one of the best lectures I ever gave was the introduction to Rust. This was because I got people to pull up the Rust Playground on their laptops, so they were actively running and debugging code in class and I could work with them. Moving forward, I want to try stuff like this some more: fully-interactive in-class content which revolves around student experimentation.

Easier said than done, though. Getting people to code in person is actually quite difficult, and if there’s only one of me, I can’t keep up with every student at once. COMP 140, the introductory CS class at Rice, manages this with a small army of TAs who can keep up with all the students, but I don’t have any TAs to do that for me.

Nobody goes to office hours

On every assignment, one of my students would write something like this in the comments of their submission.

// This doesn't work and I don't know why.
// I didn't have enough time to figure it out.

And, invariably, every single time, the problem with their work was something that I could have (and would have happily) explained to them at office hours or even in an email. It saddens me greatly to see these kinds of submissions, since it’s evidence of a completely solvable problem.

I really love getting to work with students one-on-one. It often reveals gaps in understanding that aren’t obvious in lecture or in assignments, and also shows me where I’m failing to cover material. One of my best experiences when holding office hours was when I got to explain how the function call stack works to an underclassman, and it was really fulfilling to see how it “clicked” for them. When students show up to office hours, it’s extremely valuable for me and for them.

I think that there are a few reasons that students don’t like to show up to office hours. The first, simplest reason, is simply availability. I think a lot of students start their projects far later than they really ought to, and so by the time that they get stuck, there aren’t any office hours between then and the due date. The easiest fix is to make office hours available on the same day that assignments are due, so that I can be available when students are working on the assignment.

The second issue is comfort: sometimes, students feel like they’re imposing on their instructors’ time by showing up to office hours. This isn’t helped by the fact that some professors can be downright mean to their students at office hours, which can leave a bad taste in students’ mouths, even for other classes. When I spoke to one of my instructional advisors about this, she recommended that I refer to office hours as “student hours” instead, in order to set the expectation that it’s there for the students’ benefit.

Takeaways

I didn’t come away from teaching this class feeling like I had mastered the art of pedagogy, or even thinking that I was half decent. I suspect that the core challenges that I faced were much the same as with any other class, though perhaps exacerbated by COLL 110’s status as an elective.

Even then, I think it was a great opportunity for me to learn and grow as a person, and has helped me a lot, especially in writing, public speaking, and professional communication. If you’re on the fence about teaching, you should definitely give it a try, if only because interacting with students is such a rewarding experience.

Thanks to Shreyas and Charlie for reviewing this article.