Learning From Our Limits
Why NYU was wrong to fire an instructor because his class was “too hard.”
When I was a Ph.D. student, I found myself at a crossroads. I had gone to grad school to study writing—how students write, how we teach them, and how to do that work better. So I joined a field called “rhetoric and composition,” or sometimes “writing and rhetoric,” or just “writing studies.” People tended to make fun of this field online, presenting it as the worst kind of liberal arts silliness, but I felt the importance of these topics was obvious—the way we write matters, and the way we argue matters. “Rhetoric,” though a term with bad press, simply means the art of persuasion.
I have written the story of my disillusionment with my field at length, so I won’t belabor it here. Suffice it to say that, by the time I was getting my Ph.D. at Purdue University, it had become clear that there wasn’t a place for me in the field. My professors were all smart, supportive, and kind, but the field simply didn’t respect the pedagogical work that I saw as core to its mission. No one wanted to write dissertations on the boring topic of how better to teach students to write research papers, and our journals and conferences were filled with esoterica that had no interest to me—high “theory” in the French style, pop culture analysis, research on podcasting and website-building. I liked my professors and my peers and generally enjoyed grad school, but I despaired at my inability to find a place for myself in the field.
For a little while, I permitted myself the fantasy of escaping into another discipline. I had at one point followed my academic interest down a rabbit hole regarding the assessment of the range of vocabulary in a given text. This seems intuitively simple—just look at the ratio between the total number of words in a text and the number of them that are new, right? But in fact, for technical reasons, such an assessment is far more complicated. And vocabulary assessment was only one small piece of a far larger world of computational linguistics, a world that fascinated me.
For a time, I fooled myself into thinking that I could be a part of that world. And I did work hard, reading lots of papers, trying to get a handle on the extent of the field, attempting to learn its controversies and extant problems. But my limits were always staring me in the face. I had never taken calculus, and though I had learned to grind through math as an undergraduate, it was never intuitive for me. I had used a handful of premade programs to do some of the analysis I was interested in, but it was clear that I had to learn to code myself. I dutifully bought a book on Python and followed along with some online courses. And, over time, I had an experience I’ve had several times before and since: I learned my limits. After countless hours banging my head into my desk, trying to get the code to work, one drunken night I found acceptance. I would never be a computational linguist or similar. I worked my tail off, and yet my coding skills remained meager at best; I studied and studied, and yet inevitably found myself staring at algorithms I simply couldn’t understand. I did publish a study, but it was ultimately a simple correlational analysis, a bit of academic ambulance-chasing. My efforts at learning had taught me something, just not what I had hoped to learn—they had taught me that I would never be good at this.
Eventually, I found a synthesis that worked for me. I became, at least, conversant in frequentist statistics. I developed skills related specifically to language assessment and testing; I was lucky to work in Purdue’s Oral English Proficiency Test program, where we administered an internally-developed test of oral English for international graduate students. That experience led to my dissertation research on tests of college learning like the Collegiate Learning Assessment+, and eventually to a job in academic assessment at Brooklyn College in the City University of New York system. I largely let go of my interest in algorithmic approaches to language assessment, as I knew I would never really understand the algorithms. I do, still, follow the research a little bit. But almost a decade later, I sit comfortably as someone who knows what he is not.
Recently, an adjunct professor at New York University was fired. Once a celebrated tenured chemistry professor at Princeton, Maitland Jones Jr.’s employment at NYU was cut short because of a student petition. The students complained of an imperious attitude and lack of flexibility, but the fundamental issue was that Jones’s Organic Chemistry course was simply too hard—too many students failed, and too many students who were used to receiving As received Cs. It was a direct conflict between Jones’s standards and his students’ expectations of their own success.
This firing over a question of educational rigor has inspired a lot of concern, including from me. Of course, as this is a culture war issue, some have taken to the ramparts to insist that the fired professor must have been a bad teacher if so many students rebelled, that the students have a right to be taught how they want given that they’re paying tens of thousands of dollars a year for college, that the “weed out” element of organic chemistry exists to perpetuate the doctor cartel…
Whatever the case, I want to suggest that the students who launched the petition were denying themselves a central element of education: figuring out what you’re not good at. Failing. Trying to learn, and failing to do so. This is an element of education as vital as learning what you’re good at, the act of self-discovery of one’s own lack of ability. All of us have limits, natural limits on what we can learn and do in academic fields. Some exceedingly rare individuals appear to be brilliant at everything, but for the rest of us, there’s a whole suite of topics and skills that we will never perform with any facility. And if colleges insist on reducing rigor to the point that learning those limits becomes impossible, something will have been lost.
In my own time as a graduate student in the humanities and as an administrator in the City University of New York, I was dismayed by the ongoing assault on rigor, with arguments against homework, against grading, and against taking attendance. Many in academia default to any position that seems pro-student, due to a desire to be “the cool professor” or through tendentious political definitions of the purpose of higher education. But such people tend to define “pro-student” as meaning whatever students want, when of course part of the point of being an educator is to do what’s best for students that they may not want to do themselves. I believe that rigor is essential to providing students with value for their tuition dollars, as I personally have been brought closer to the level of my potential thanks to professors who made serious demands of me. I have also learned the limits of that potential thanks to those teachers, who helped me to understand what I was and was not good at.
My first book, The Cult of Smart, was about a lot of things. But perhaps at its core lay the basic point that not everyone can be good at everything, including in academics, and yet our educational debates stem from the notion that tweaking policy can eventually, inevitably give every student what it takes to be a Stanford-educated coder at Google. This, of course, is nonsense. We are all bound by limits, academically. And what I would ask of those who defend NYU’s actions is simply this: if not now, when? If not college professors, who? In a world of helicopter parents and therapeutic culture, who else helps students undertake the difficult, essential work of learning their limits?
I do, in fact, defend the basic practical and moral logic of weed-out classes. At Purdue we had a notoriously difficult first-year engineering program; I was told by another grad student that something like one in three students who arrived at campus intending to be engineers would eventually graduate with engineering degrees. And a graduate instructor friend of mine in the electrical engineering department explained the idea simply. If early engineering classes were easy, and most students passed them, then some of those students would inevitably run up against their academic limits later in their academic careers, at which point starting over with a new major would be harder and more expensive. And even if the university made all engineering classes artificially easy, eventually our graduates would find themselves in a job market that would be unforgiving of their lack of ability, or in jobs where they would be destined to fail because of the things they could not do. You can kick the can further and further down the road, but sooner or later, ability will out, and not everybody has ability.
That is a fact that all of us must come to learn in time. I prefer the upfront mercy of weed-out classes to the long-term cruelty of letting students chase dreams that will ultimately go unfulfilled. We know what it looks like in artistic fields with no gatekeepers—would-be actors and screenwriters and musicians and novelists who hang on too long, never being gently but firmly told that they don’t have what it takes. They therefore never have any reason to let go of unlikely dreams and build more stable and financially rewarding lives.
When I attempted to make myself into a computational linguist, I was both the square peg and the hammer. And what I found in time was that I could not force myself into the round hole of my ambitions. It was a tough lesson, one that involved dozens of hours of work that were misguided—misguided, but not wasted, as I did indeed learn a special lesson about who and what I was not.
Freddie deBoer is a writer and academic. He lives in Brooklyn.
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