True Confessions from the Grading Trenches
It happened on a Wednesday—the kind of Wednesday that arrives in the middle of a grading cycle and quietly steals your personality. I had been working through a stack of papers that all needed thoughtful, individualized feedback, yet somehow required me to repeat the same five clarifications about APA formatting, thesis coherence, and the difference between analysis and summary. After the seventh iteration of “This section would benefit from clearer synthesis,” I could feel my brain flattening into a procedural instrument.
By mid-afternoon, I had slipped into that familiar grading trance: the rhythm of read, assess, comment, encourage, repeat. It’s a rhythm that is both meditative and numbing; a kind of pedagogical autopilot that keeps the work moving but slowly drains the creative oxygen from the room.
To keep myself human, I toggled over to my AI assistant, a habit I’ve developed during long grading stretches. We have a rhythm of our own: I bring the context, the nuance, the pedagogical judgment; it brings the structure, the clarity, the occasional spark of phrasing that helps me articulate what I already know but am too tired to say elegantly.
At least, that’s how it usually works.
But on this particular Wednesday, something shifted. I found myself typing literal, clipped, almost mechanical sentences—the kind that come from brain drain, the inevitable symptom of grading for too many hours. And the AI? It responded with imagery. With metaphor. With a kind of playful expansiveness that I normally bring to the table.
We had, without warning, traded places.
I was the one being literal. It was the one being metaphorical. And the moment was so unexpected, so pedagogically revealing, that it snapped me out of my grading trance entirely.
The Pedagogical Insight
What struck me most about that moment wasn’t the novelty of an AI generating a metaphor. It was the realization that I had slipped so fully into the mechanics of teaching that I had abandoned one of my own cognitive signatures. I am, by training and temperament, a metaphor-maker. I teach through analogy, story, and conceptual reframing. I help students understand complexity by giving them something to hold onto—an image, a comparison, a narrative thread.
But fatigue has a way of sanding down the edges of our pedagogical selves. After hours of grading, I wasn’t thinking like the teacher I am; I was thinking like a machine processing inputs. My language had become transactional. My feedback had become efficient. My mind had become literal.
And in that vacuum, the AI stepped into the role I had momentarily abandoned.
It didn’t “take over” in the dystopian sense. It simply filled the space I had left open. It became expansive because I had become narrow. It became imaginative because I had become procedural. It became metaphorical because I had become literal.
The reversal revealed something I hadn’t fully articulated before:
Teaching is not just what we do; it’s a cognitive stance we inhabit. And under pressure, we can slip out of that stance without noticing.
The Broader Teaching Application
The more I sat with that role reversal, the more I realized it wasn’t really about AI at all. It was about teaching identity, and how easily we slip into familiar roles, how tightly we hold them, and how subtly they can erode under the weight of repetition.
Every educator knows the feeling: the semester hits its midpoint, the grading piles up, and the work becomes more about throughput than creativity. We start teaching from muscle memory. We give feedback from habit. We rely on the cognitive shortcuts that help us survive the volume but quietly flatten the nuance.
And then something unexpected happens: a student question, a classroom moment, or in my case, a surprisingly poetic AI jolts us out of the groove and reminds us of the pedagogical spirit we momentarily misplaced.
These disruptions matter. They remind us that teaching is not a static identity but a dynamic posture. They show us that our pedagogical selves are not fixed; they are responsive to context, energy, and attention. They reveal that the qualities we value most in our teaching—curiosity, metaphor, play, and expansiveness—are not automatic. They require care and cultivation.
The AI didn’t “teach” me in the traditional sense. But it did something pedagogically adjacent: it surprised me back into myself.
Lessons from the Role Reversal
That brief moment of trading places with my AI didn’t just amuse me. It clarified several practical lessons about how faculty can work with AI without losing themselves in the process.
- Notice when you’ve slipped into the literal. Fatigue can flatten even the most imaginative teacher. When your feedback starts sounding like a procedural checklist, it may be time to pause—or to let AI reflect back the narrowing of your own voice.
- Let AI surprise you back into your pedagogical self. The most valuable thing AI did that afternoon wasn’t generating a metaphor; it was reminding me that I had stopped doing so. Sometimes the disruption is the teaching moment.
- Use AI not to replace your voice, but to restore it. When AI drafts structure or phrasing, it frees you to re-enter the work with more presence, nuance, and care. AI can handle the scaffolding; you bring the humanity.
- Treat AI as a cognitive partner, not a cognitive crutch. The goal isn’t to outsource thinking. Instead, notice when your thinking has drifted and use AI as a prompt to return to your fuller, more expansive teaching stance.
- Build intentional pauses into your workflow. If the AI starts sounding more like you than you do, that’s not a sign of its brilliance; it’s a sign you need a break. So take one.
These small practices help ensure that AI enhances rather than erodes the qualities that make teaching meaningful. They also keep the “trading places” moment where it belongs: as a gentle nudge, not a new normal.
The Takeaway
What I took from that moment was surprisingly simple: our tools can only disrupt us if we allow ourselves to be surprised. In the middle of a long grading day, when my thinking had narrowed to the most literal version of myself, the AI didn’t replace my teaching; it reminded me of it. It nudged me back toward the imaginative, metaphor-making stance that fatigue had temporarily muted.
In a time when faculty are being asked to integrate AI into their work with equal parts enthusiasm and caution, this may be the most useful lesson I can offer: AI is not here to take our roles. But it can reveal when we’ve stepped out of them.
In the end, the role reversal wasn’t a threat at all—it was a mirror, reflecting the moment I had drifted from my best teaching self.
The experience affirmed something I’ve always believed but had momentarily forgotten: good teaching requires presence, imagination, and the willingness to be startled back into ourselves.
And sometimes, on a Wednesday in the middle of a grading marathon, that reminder arrives from the least expected collaborator.
Sherrie Myers Bartell, PhD, teaches MBA students at the University of the People and serves as Chief of Administration and Policy Analysis at Bartell Chiropractic Center. A conceptual theorist and essayist, she writes about the evolving relationship between faculty and AI, with a focus on how educators sustain presence, imagination, and pedagogical identity in technology‑rich learning environments.