Back to School (again!): November Reflections

What happens when the Director of a Teaching and Learning Centre isn’t sure she’ll pass a first-year undergraduate course?

As I’m writing this, the final exam for my first-year computer science course is a week away. I don’t know yet how this story ends. What I do know is that there have been nights where I’ve stared at my screen and thought:

“Maybe I’m just not cut out for this.”

That’s a vulnerable thing to admit when you’re serving as the Director of a teaching and learning centre, when you have spent decades studying and working in higher education, leadership, and organizational development. And yet, I’ve had marks come back low enough, and confusion that has run deep enough, that it has genuinely felt like I might not make it to end of the course. I can’t help but wonder, if I am feeling like this, what is happening to students who don’t have the same power and privileges that provide me with the protective buffers I have?

The hidden cost of rigour

We are great at saying that university is “rigorous.” What we don’t say is that rigour often comes with a cost: anxiety, shame, and quiet exit. I walked into this course thinking I understood the student experience. I’ve spent years listening to and working with students. But what I hadn’t felt in a long time was the day-to-day texture of it:

• the anxiety of not knowing if you’re on the right track
• the emotional toll of working endlessly and still coming up short
• the evaporating confidence when there’s a mismatch between “I am following this lecture” and “I can answer this exam question”
• how much courage it takes to ask for help when you already feel behind
• the quiet shame of looking around and thinking, “Is it just me?”
• the very real temptation to drop the course so you won’t have to feeling this out of place

We tend to label the students who persist as “resilient,” as if that’s something they simply brought with them. This resilience has looked more to me like daily acts of resistance against the pull of self-doubt. I have also learned that course design choices either support that resistance, or they make it harder. Our marking schemes, exam formats, pacing, and prerequisite assumptions can either soften or sharpen the edges of student anxiety, often without us even realizing.

I’ve also been reminded what it feels like to be a true beginner again: not just “a bit out of my depth,” but regularly encountering concepts, notation, and tools for which I have no prior schema. Being a true beginner can be cognitively tiring and emotionally exposing. There’s a deep humility in that and it has affirmed for me that learning is relational: not knowing is okay if we are willing to listen, to try, and to connect with and respect each other’s knowledges.

Alongside the hard parts, there have been genuine flashes of joy: the first time a piece of code finally compiled and behaved as expected; the moment a recursive definition actually started to make sense. Those small “I can do this” moments are disproportionately powerful in sustaining effort. As an educator, I’m reminded that it is not fluffy to help students notice and name what’s going well, it’s integral in keeping them engaged with difficult material.

It’s been disorienting to inhabit multiple identities at once: a first-year student who is often lost; a lifelong learner with more degrees than anyone needs; and the Director of the MacPherson Institute. If someone like me, with institutional knowledge, long experience as a learner, and relative power, hesitates to ask basic questions or feels like they don’t belong, what does that suggest about the emotional hurdle for a student in their very first semester? These questions have sharpened my sense of how much courage it takes simply to show up and admit confusion.

Learning with my son, with AI, and against the grain

For most of my academic life, my strengths served me well: I can read deeply, write analytically, and connect conceptual ideas. This course has demanded a different kind of thinking and learning, writing and debugging code, tracing recursive definitions, drawing out tree diagrams and reasoning through edge cases, memorizing heavily detailed properties for multiple-choice midterms and exams. It has felt, at times, like being dropped back into the first years of my B.Sc., except now I also am working full-time, studying in an MBA part-time, transitioning to a new home in the empty-nesting phase of life, and working with a brain that can no longer pull off all-nighters.

The most interesting part is that I’m not doing this alone. I’m doing it with my son. Trevor’s approach is radically different from mine: “Just try it. See what the compiler says. If it doesn’t work, find a way to fix it.” Where I want theory, pre-reading, and carefully constructed understanding before I touch the keyboard, he is willing to dive in, break things, and learn from the debris. He searches the web, tests, iterates. It’s messy and fast and, frankly, brilliant. Watching him has made something click for me: students are already experts in surviving our courses. They are constantly hacking together strategies to make things work under conditions we educators only partially see or understand. Seeing this reminds me how important it is to view students as learning co-designers. They have the best “on the ground” tactics using wide breadths of technologies, and they really are well-positioned to be not just recipients of teaching, but co-constructors of learning strategies.

I’m not just learning alongside my son. I’m learning with him. I’m learning from him. His trial-and-error approach has shifted how I think about learning strategies, and how often our high-stakes assessments don’t make enough space for this kind of exploratory, iterative learning.

Like many students, I’ve also experimented with tools like AI in this course, especially to help coach me through prerequisite calculus (which is rusty for me after thirty years). AI has helped me to identify where my understanding is thin, to get explanations in different words, and even to debug code I had written that just would not work. I believe that the work I’ve submitted is indeed my own, a product of my own struggles, informed by the added learning and lessons from this “coach on the side.” Sometimes that coaching has been genuinely helpful. Sometimes it is misaligned with the course’s framing or the instructor’s expectations, or outright wrong. Being able to discern the difference is fundamental to its use, but beginners do not often know enough to recognize its limits in a particular area. It has made me more aware of how students are triangulating between lectures, peers, online resources, and AI. It also makes it important for instructors to be explicit about where those tools are helpful, where they are risky, and how to use them critically.

I have felt an enormous range of emotions while taking this course. I have had the opportunity to experiment with new technologies, learn new concepts, experience new perspectives and generally take myself out of my comfort zone. While I may never become an expert computer scientist, I know this experience has been an important exercise in gaining a unique student perspective at a moment of both great disruption and deep introspection in the teaching and learning sector.