Facing the reality that a majority of Canadian students are using generative AI for schoolwork, more educators are bringing artificial intelligence into their university classrooms, setting clear rules and encouraging students to use it responsibly — and with a critical eye.
That’s forcing instructors to rethink how they teach and assess students since — outside of concerns about academic integrity — institutions tend to leave decisions about AI use to individual faculty.
These university professors explain how they’re weaving AI into their courses and how they’re guiding students to learn what they’re expected to.
An AI teaching assistant
Antonello Callimaci prioritizes answering student queries promptly — dedicating four blocks of time daily to do so. But when the Université du Québec à Montréal accounting professor is unavailable (or students are hesitant to reach out directly), Bobby’s got his back.
Bobby is an AI agent “teaching assistant” that Callimaci built last year by training ChatGPT on the hundreds of assignments, presentations, notes and recorded lectures he’s prepared over the years for one of his courses. Accessible 24/7, Bobby’s responses come straight from Callimaci’s content and also point students back to him for further clarification.
“He’s able to summarize material. He’s able to build sample exams. He is able to answer specific questions,” Callimaci said.
The agent can handle sophisticated requests, too, he said.
With studies showing most high school, college and university students across Canada embracing AI tools like ChatGPT, educators are scrambling to come up with rules to prevent cheating. Quebec is one of the few provinces to issue guidelines.
For instance, a student who used Bobby all last semester requested it review past interactions to see what had given him the most trouble. The results pointed him to areas needing extra study before the final exam — which Callimaci has kept old-school: paper and pencil, no tools or devices allowed.
“It’s a learning tool, but you cannot count on Bobby to do your work,” he said.
‘Reaction dialogues’ with AI
Political science professor Joseph Wong has long used weekly readings to push first-year students to grapple with new ideas and diverse perspectives for his seminar in Munk One, a small-group undergraduate program at the University of Toronto that explores global public policymaking.
Since generative AI hit the public sphere, however, he’s reimagined how to keep his students engaged in that same productive mental struggle.
For instance, his final assignment used to be a magazine-length feature article proposing a solution to a global challenge. Now students produce a three-minute TikTok video, accompanied by a written reflection about making it.
In a similar vein, the traditional reaction papers he previously assigned alongside weekly readings are out; they’ve now become “reaction dialogues” with AI. After finishing the readings, students submit their back-and-forth discussion with an AI agent: a chat where they’ve ideally delved deeper into what stood out for them.
It lets students practise effective AI prompting, Wong says, but like the earlier reaction paper, these interactions can also highlight how deeply students engaged with the material — or even their frustration if the chatbot conversation goes awry.
“What I’m assessing is to what extent are they now not only wrestling with the reading, but also wrestling with their conversation partner, with the AI,” Wong said.
Still, he remains on the lookout for students’ analytical and critical progression.
“As educators, we have to continually remind them of the value of learning the material and the value of learning those skills.”
Engaging students with AI
Sidney Shapiro has been using AI and machine learning for a decade, but the tools available today are helping him quickly adapt lessons to be more engaging and relevant for students.
Five years ago, one programming course basically had students “watch me type [code] for two and a half hours,” recalled Shapiro, an assistant professor of business analytics who teaches in both University of Lethbridge’s school of business and department of computer science.
Recently, in that same course, he tapped generative AI to quickly develop code based on impromptu suggestions from students — a medical clinic for superheroes, cows dressed in colourful sweaters — and was able to zip through a series of “hilarious” exercises that made for creative, memorable learning.
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In another instance, he turned the tables on a disengaged student when he used ChatGPT to quickly translate that day’s slide deck into “skibidi toilet, Ohio-type of talk,” Shapiro said, which he then presented.
“This student told me [it was] the most cringe class they’ve ever been to, and it was so super embarrassing — but they remembered everything, so it worked out perfectly.”
Each semester, Shapiro is tinkering with automation and AI usage (as permitted by his institution’s policies), but he sticks with certain fundamentals, including an emphasis on foundational skills such as reading and thinking critically, learning to write concisely and being transparent about using AI.
“I don’t think students have to be experts at everything now because there are AI helpers that do a lot, but they still do need critical thinking … so they can recognize when there’s a trap, when there is something that doesn’t make sense and how to fix it,” he said.
If educators pretend that AI doesn’t exist, “the reality is that many people will use it anyway, but they’ll feel guilty about it and not learn how to use it properly.”
Reconsidering assessment, objectives
Maggie McDonnell builds AI into every course she teaches. Her undergraduate, professional writing program students at Concordia University start out by researching the benefits and drawbacks of AI use across various industries, for instance, and also work with her to determine an AI policy for all of their assignments.
Meanwhile, in the Université de Sherbrooke’s Master Teacher Program, she and colleagues have scrapped an annotated bibliography assignment for an upcoming course — “one of the things that AI can do in like a minute and do really well.” Instead, they’ve chosen another way for students to demonstrate their research, synthesis and communication skills (and if they use AI for it, they must disclose that).
McDonnell says that some students may still use AI as a shortcut, especially in general or required courses they don’t see the value of. But in the career-oriented classes she teaches, she finds students see the relevance of engaging with AI effectively and ethically. They’re also OK when she prohibits AI for certain tasks.
Even so, incorporating this new technology has meant McDonnell must regularly reimagine how she’s assessing students, reconsider learning objectives and “come up with new stuff all the time” — invoking the challenge and excitement of when she started teaching 25 years ago.
“There will always be ways for people to get around what it is you’re trying to ask them to do, so do we want to become enforcers and police things or do we want to find other ways to engage [students to] show us the same learning?” she said.
“Part of the challenge for us as educators is to take that step back and say ‘Is what I’m asking them to do … the important thing or is it how they got [there] that’s important?'”
