Round 2 of BILD 5 is in the books! I am so proud of how this quarter went — I think I made big improvements in my teaching, and I truly felt myself growing in confidence whilst having fun too.
Notably, this quarter I had my largest classes ever: 350 students in BILD 5, and 250 in BIPN 100. This was both exhilarating and terrifying. I can still vividly picture the first day of the quarter, high on adrenaline before my first lecture, pacing up and down the 8th floor of HSS, trying to simultaneously hype myself up and calm myself down. Although large classes do have their limitations, there was nonetheless something truly special about seeing so many people going through a shared experience together. I loved hearing the explosion of noise during lecture when my students would turn to their neighbors to discuss a problem, and soaking in the energy as hundreds of voices started talking at once.
This quarter, I kept approximately a third of my lectures unchanged from last time, I made light edits to another third, and I completely revamped the final third. In particular, the revamps were to more explicitly center the conceptual intuition behind statistical principles, even if that meant foregoing some mathematical completeness/satisfaction (see my previous post about the context and aims of BILD 5). Take Confidence Intervals as an example. When I taught this topic last quarter, I could feel myself steadily losing more and more students as the lecture went on. I think I spent too long trying to break down each component of the formula (e.g. where exactly does the 1.96 value come from?), that it obscured the conceptual principles I actually cared about my students learning (e.g. What even is a confidence interval in the first place, and what can and can’t one tell you? Why does it make intuitive sense that increasing the confidence level corresponds to widening the interval?). Although it initially felt painful to remove some math, I ultimately had to remind myself that in the future, none of my students will ever hand-calculate a confidence interval, but they may very well need to look at one and interpret what it means (and also what it doesn’t).
Another major content shift was to emphasize data visualization as a running throughline all quarter long, as opposed to treating it as just a standalone topic at the beginning. For some context, I do already have a couple of lectures early in the quarter that explicitly address exploratory data analysis and visualization. But in the past, as the quarter progressed, I’d naturally shift my attention to the newer topics (e.g. hypothesis testing, verifying the assumptions of parametric tests, transforming lognormal data) and deprioritizing old ones. This led to an interesting pattern in my students’ Final Projects, where some students autopiloted to running statistical tests (e.g. performing normality tests, transformations, t-tests, ANOVA) and forgot to ever visualize their data. As a result, several students failed to detect an obvious outlier in their otherwise normally distributed dataset, which led them down a rabbit hole of performing unnecessary transformations and needlessly complicated analyses. This quarter, I tried to address this by interweaving exploratory data visualization into every lecture, highlighting how this was always the first step regardless of the topic of the day. t-test lecture, visualize first, ANOVA lecture, visualize first, chi-squared lecture, visualize first. Despite my concerns that this would start feeling tiresome, I think it was ultimately the right move, and it really drilled the importance of looking before you leap into analysis.
I also made significant updates to the assignments, especially the weekly Coding Labs. Last time I taught BILD 5, since I was so swamped with just getting the class off the ground, I felt that I didn’t give my students sufficient practice problems, nor did I challenge them enough with hard questions. This time round, I increased the length of each Coding Lab by 50%, and I gave the students more difficult multi-step problems that required them to integrate their programming skills and their statistical thinking. For example, I might give a clinical dataset and ask the students to calculate a confidence interval, leaving the students to realize for themselves that they’d need to filter the dataset before computing the interval. Or asking the students to run an ANOVA, only for the students to realize that they had to tidy the data before they could do so. It was SO fun to see the students come to these a-ha moments, especially when they realized they had to redeploy a tool from several weeks earlier in the course. I also tried to incorporate more open-ended questions (e.g. make any graph you want with the remaining columns of this dataset and make it the most beautiful visualization you can), because I wanted my students to feel more creative ownership over their work. It was very charming to see they came up with — for instance, one student went to office hours just to figure out how to turn every dot on her scatterplot into a flower, since she was making a graph about floral sepal length.
There was one addition to the assignments that I was especially proud of: having the students analyze data about themselves as a class. Before the quarter started, I added a few items to my standard pre-course survey — I asked students to self-report their Spotify listening age (if they used Spotify), how many Instagram followers they had (if they used Instagram), how many people they follow on Instagram, how many unread emails they had, and the like. As the quarter progressed, I’d interweave questions about this dataset into the assignments, once the students had learned the appropriate tools to answer them. For example, do transfer students have a higher Spotify listening age than non-transfer students? Is there a relationship between class standing and the number of unread emails you have? (Are first years more disorganized? Or have fourth-years given up on inbox zero?) Is there a correlation between how many people you follow on Instagram and how many followers you have yourself? (Did anybody in the class have an influencer-like profile, where they had many followers but followed very few people themselves?) I had lots of fun with this, as did the students.
Content updates aside, a final goal I had this quarter was to slow down. By this, I don’t mean slowing down in lecture, which is itself a separate and ongoing objective. Instead, I mean slowing down in my conversations with students, and trying not to rush through these one-on-one interactions. I realized this issue the last time I taught BILD 5, when I’d walk into my office hours to tens of students all stuck on different problems. Since I wanted to help as many of them as I could, I’d zoom from student to student, and I often found myself hastily declaring a matter resolved and preparing to walk away, when the student would say “Wait sorry, I’ve got another question”. Once I noticed this pattern (and I realized just how many students would apologize before asking a question), I realized that my pursuit of efficiency might be doing more harm than good. Although I genuinely enjoyed each conversation, I was inadvertently signposting that I wanted to be done with each interaction as expediently as possible, and potentially making students feel guilty for being a burden on my time. This quarter, I tried to do two things to address this. First, I began all my office hours with an explicit invitation for the students to introduce themselves to their neighbors and to help each other. That way, hopefully we’d not only have more issues resolve themselves, but also build a habit of students coaching each other as opposed to waiting in silence for me to arrive. Second, during my conversations with each student, when I felt a natural resolution to the conversation, I would try and count to 3 in my head before standing to leave, just to give each student a little extra thinking time, and for them to declare the issue resolved instead of me. This is all very much still a work in progress. I still get stressed when there’s a large group of students, since I don’t want them to feel like they came to office hours and waited all this time for nothing. Therefore, I’m still constantly having to remind myself: “There’s more to office hours than just talking to ME. There’s value in the students all being in the same room together, verbalising their thought process with each other.”
As always, I had a blast getting to know my students. Despite the large class size, I had the chance to chat with many students 1:1 during discussion sections, which I attended all quarter long (I don’t usually do this in my other lecture courses – but for BILD 5, I think there’s a real benefit to showing up each week and giving the students an encouraging nudge that they’re heading in the right direction). It was also extremely gratifying for me to see the students growing in confidence and overcoming their self-doubts about their math/statistics/coding abilities. At the end of the quarter, I asked each student to share their fondest memory from the course, and the responses were just so delightful and wholesome and made me smile. Here are just a few of them.
“I enjoyed all the coding. It was fun learning something you didn’t think you could ever understand or do.”
“I LOVED the Coding Labs with my whole heart. It was always an assignment I looked forward to at the end of every week. I also loved adding funky colors to all my graphs”
“My fondest memory was doing the Final Project. It was rough. I had work and had to study for my chem Final, so I was dying, but the feeling I had when I was done was amazing. I’ll think back on that with a sense of accomplishment”
“I kept thinking back to our first lecture where you said we would be able to understand code and complete the Final Project. I was so skeptical back then but now I realize you were right. I have learned so much about coding and statistics that I would have been overwhelmed with three months ago”
“My fondest memory of BILD 5 was telling Ming I used R in my research and seeing how happy he got.”
“My fondest memory of BILD 5 wasn’t just one memory, but a collection of all the time I was able to spend with my suitemates because of this class. We shared many laughs through the lectures, Coding Labs, studying, and the Final Project”
“When Professor Ming told us he took his first driving class this quarter and we all cheered for him!”
I’d be remiss if I didn’t end by acknowledging my incredible teaching team. Especially in a class like BILD 5, where there is so much 1-on-1 student interaction (and it involves learning a new skill that can be deeply frustrating), having amazing TAs makes all the difference. My TAs were just so kind and enthusiastic and fun, and I heard so many students express their appreciation for how approachable and cohesive the entire teaching team was. One of my favorite memories of the quarter was attending the UCSD Intermission Orchestra as a team to support our graduate TA, who plays viola in the orchestra, and going out for a celebratory end-of-quarter dinner afterwards (the food came out SO slow that we wrapped up dinner at midnight…) Having a great team just makes the job so fun. Onwards to next quarter!