Baba Yaga’s Wandering Professor

Baba Yaga is hard to categorize.

Depending on whom you ask, she is a Slavic witch, a folkloric ogress, a wise and helpful woman, or a combination of all three. She travels through the forest on a flying mortar, carries a pestle as a weapon, and—most famously—lives in a wandering wooden house balanced on two ginormous chicken legs. The house is arguably just as, if not more, unpredictable as its occupant. It wanders through the forest, turning, stopping, disappearing, and reappearing wherever it pleases.

Lately, I have found myself thinking about Baba Yaga while sitting in Emerson 105.

Not because my professor is a witch. Not because Emerson Hall has sprouted chicken legs and decided to move out of the Yard. And, most unfortunately, not because I have discovered a magical alternative to learning statistical analysis and coding with R.

It is because my introduction to quantitative methods in the Government department at Harvard has felt strangely similar to stepping into a house that refuses to stay put.

I enrolled in Gov 50: Data Science for the Social Sciences expecting a “welcome to coding Gov concentrator who has no interest or experience with coding” introductory class. That last word seemed fairly straightforward: introductory. I imagined being shown the foundations of coding, having unfamiliar words and concepts broken down, and being given grace for making mistakes while gradually becoming less intimidated by the quantitative side of a concentration that, for many of us, is otherwise firmly rooted in the humanities.

The course description seemed to promise exactly that: “no previous experience with statistics or statistical computing required.”

For a student whose last exposure to coding was HTML during sophomore year of high school, I’ve learned that “no experience required” does not mean “you will be fine without much guidance.” It means almost the opposite. The course is supposed to meet you where you are. Instead, I feel like I was handed the map only after Emerson 105’s legs had already decided where the journey would take us.

Part of the issue is that Gov 50 doesn’t seem to be a consistent experience. Students who took it in previous years describe something far different from my own encounter. Some remember a course that lacked structure and relied too heavily on AI for assignments, while others describe a far more technically demanding curriculum. The role and expectations of coding shift entirely depending on who is teaching.

Of course, professors should be allowed to teach differently. A university would be a miserable place if every classroom felt identical. But there is a difference between a course having a personality and a course having an identity crisis. This distinction becomes particularly glaring when the course is a department requirement. Gov students do not all arrive with the same academic background, and for many, this course is their first encounter with R, statistical modeling, or a mode of reasoning focused strictly on quantitative data.

I do not think that Gov 50 should be inherently easier. Yes, I believe the current course assumes too much prerequisite knowledge and does not feel like an introductory course. But regardless of course expectations, I believe the department should structure Gov 50 clearly. There is something uniquely frustrating about struggling with material when you cannot tell whether the subject itself is difficult or whether you simply haven’t been given the baseline structure needed to learn it.

If a Gov 50 student spends forty minutes trying to figure out why their command is returning an error, they have not necessarily spent forty minutes learning political science analysis. I should be able to leave a class having learned something new, not with five new questions that will take 20 Google searches and two hours of office hours to somewhat understand. Technical skills have an important place, but when they obscure a course’s intellectual purpose, the introductory bridge has failed. Too often, it feels as though the bridge is being built while we are already walking on it.

Further, I have concerns about how we use lecture time. Gov 50 centers on learning two quantitative languages—statistical analysis and coding. Yet class time is insufficient to teach both, so we scramble to find our own solutions for learning the latter.

Just last week, I attended my CA’s study hall hours before our Monday lecture. I expected to meet a few other peers struggling with a homework problem that referred to concepts and material never explained in lecture, section, or the textbook readings. Later that day, in lecture, I learned that over 40 students attended his office hours with questions about the homework that even he struggled to understand and conceptualize. When given the chance to provide feedback and ask questions about the homework during the last ten minutes of lecture, my professor appeared confused and defensive about the negative experience most of us had with the assignment. What followed was an influx of posts on Sidechat—“Gov 50 is so heinous we are all screwed” and “Appreciating my stats prof even more after hearing about the atrocities of Gov 50”—and rightfully so.

Given the stereotypes of Gov concentrators, it is easy to dismiss these complaints as just a lack of motivation, but—I digress.

Harvard likes to tell us that learning here is supposed to be exploratory, and I believe it. But that exploration requires some direction. This is not to say that I am against adjunct professors. They are not inherently worse educators. However, placing them in introductory courses—especially when their topic and specialty are on the more niche side of the field—creates an environment where the entire class is tied to their self-interest rather than the department’s expectations. These required introductory courses must be taken seriously enough that the quality of a student’s education is not entirely dependent on who happens to teach the course that year. Yes, professors should be given room to experiment. They should be given room to teach differently and authentically. But the college must establish and enforce a baseline. That baseline must set common objectives, clear expectations, consistent resources, and enough support so that students encountering an entirely new subfield are not left to fend for themselves. Otherwise, the college risks leaving students more confused after a semester’s worth of lectures, without having achievedhavingand failing to achieve its goal of teaching skills and instilling newfound interests.

Baba Yaga’s house can wander because wandering is the point. Its instability is part of the story. A required introductory course does not have that luxury.

When I walk into Emerson 105, I do not need the walls to stay perfectly still, nor do I need every professor to teach the same way. I do not even need the course to be easy. I just want to know that when I walk out, I will have actually been somewhere.

Madi Kang’29 (madisonkang@college.harvard.edu) hopes to one day inherit a wandering house, preferably with legs that do not resemble chickens’.