Academic Teaching is Hard
A few months ago I got an opportunity to teach a single course for 3rd-year BSc students at Innopolis University (Russia). The title was “System Software Design.” The size of the group was about 150 people and the duration was 8 weeks. I was supposed to give them sixteen lectures, two lectures per week. And I was asked to examine their knowledge by the end of the course. Pretty much a normal job for a university teacher. And you know, in my opinion, I failed most parts of it. Here is what I learned.
I’ve got a lot of experience of giving speeches at software conferences, workshops, meetups, and so on. Usually, such a speech is 30-40 minutes long with 10-15 minutes for Q&A at the end. Then, you just walk away and relax.
Here it was something completely different. First, the lecture takes 90 minutes with a small five-minute break in the middle. Second, I had to give two lectures straight. Third, I had two lectures on Tuesday and two on Wednesday. Thus, I had 180+180=360 minutes of teaching every second week. 360 minutes! It’s similar to 10 conference speeches! Imagine how much it takes to prepare ten conference speeches. All my evenings and weekends were completely occupied with this. The lesson I’ve learned: start preparing your course long before the first day of it and expect to spend a lot of time on it.
It seems that for some/most students, my course was not so much about learning something new, but about getting the “A” grade. They started bugging me right from the beginning of the course: how exactly will you examine our projects and how will the grading decision be made? I don’t blame them, I blame myself: I didn’t give them a Syllabus at the beginning of the course. Somewhere in the middle of the course I wrote it up, see here.
In Lieu of an Exam
Instead of examining their knowledge I decided to ask them to create some software, using the knowledge they supposedly got at the lectures. It was a good decision, because I can’t even imagine how much time an oral examination of 150 people would take and how subjective it would be. There was another option though: a questionnaire with right and wrong answers. But still, it would take a lot of time to create one. Asking them to make a piece of software was a better choice, until I realized that I didn’t know how I could objectively evaluate it.
In the Syllabus I suggested some criteria, but they were far from being objective. The only objective one was the number of stars their repository would acquire on GitHub. By the way, all of them reached the highest required number: fifteen. Some of them got more than forty, which, according to my plan, was the point: to show them that good software with a small boost (by the stars given to you by friends-and-family) can easily gain larger popularity.
By the way, I’m still dreaming about a software package or a hosted service, which would go through any GitHub repository and make a quality analysis of it. Not the quality of code, but the quality of process, documentation, discipline, communications, etc. Such a software may use Machine Learning to make non-deterministic guesses about the internals of a repository. It may also benchmark thousands of GitHub repositories and then evaluate the given one against those which are the best.
Without such software I had to review their repositories one by one. Which took me an entire day. TAs did their review before me, which was helpful too.
There were not only lectures, but also practical tasks, called “Labs.” I had three Teaching Assistants (TA), each of which had one third of my students. The TAs were also teaching them software design, trying to go along with the content I was giving at the lectures. Did it work well? It didn’t. And it was 100% my fault.
Each TA has their own ideas about software design, about software quality, about management, about many other things. If I wanted to do it right, I would have had to “teach” the TAs first, spending some time for this before starting the course. Maybe I would have even had to give them some guidelines, explaining my expectations. This would be very helpful, since TAs interact with students much more than the lecturer. I, being a standing-up teacher, was not able to discuss things with students: I was mostly delivering them my thoughts. TAs and Labs are where the discussions are happening.
Thus, the lesson I’ve learned: before starting teaching, make sure your TAs understand your content well. Very well.
At my first lecture there were about 120 people in the room. At the last one there were ten. I’m not sure exactly why, but there are a few possible reasons. First, maybe the lectures were boring. Well, can I make them 12 times more fun next time? I doubt it.
The second possible reason is that I didn’t check their attendance. I told them right at the beginning of the course: “I don’t care about your physical presence here, I only care about the product you create in eight weeks.” Maybe this was a mistake, but I still think that forcing students to attend lectures is disrespectful.
Third, maybe most of them found it more comfortable to watch the recorded lectures on YouTube instead of going to the class. I was trying to publish videos in just a few days after each lecture. Was it a mistake? Maybe so, but I still believe that video content is king. By the way, each lecture out of sixteen published, was already watched at least a thousand times on YouTube. A few dozen students in the room versus a thousand people on YouTube: who do you think is more important?
Thus, if you want your class to be full each time: 1) entertain them, 2) make grades depend on attendance, and 3) don’t publish videos until after the exam (or don’t record at all). But I won’t do either of those. I’m fine with ten people in the room, thousands on YouTube, and a few very interesting products created by those who most probably never attended (I discuss them below).
There were four possible grades to give: A, B, C, and D. The failing one was “D”, but”C” was not good either. Students formed small groups of up to four people. Each group created their own GitHub project (actually, three groups out of fifty made them in GitLab) and I reviewed them. Here is how I distributed my marks:
Formally speaking, I gave “A” marks to 2+6+22 people (including “A+” and “A++”) marks, but I felt obligated to emphasize the difference between excellent and good projects even through they are in the same formal “A” category: that’s why there are extra “A++” and “A+” marks. Of course, there was a possibility to give “A” only to those who are “A+” and “A++” in my classification, shifting the rest of the schedule down and giving many more “C” marks, but I was afraid that this would lead to a lot of complaints. Put simply, I chickened out.
Now, to reward those who got “A++” and “A+” I’m publishing their projects here, and their accounts. They may consider this blog post as my personal letter of recommendation for each of them. If you, dear reader, are a potential employer of these guys, I highly recommend them.
Here they are the “A++” two:
Look at the quality of the repositories! Don’t judge them much by the quality of code or the usefulness of the products (even though they are useful) — the course was not about coding. The course was about organizing your code and making technical decisions. They, I believe, did very well, keeping in mind that they are students.
These are six “A+” repositories:
They are also pretty good.
Big thanks to Innopolis University and personally to its Dean, Prof. Giancarlo Succi, for giving me this opportunity to realize that being a teacher is very hard and … fun.
What a good teacher does?— Yegor Bugayenko (@yegor256) December 5, 2021