2026 CMS Winter Meeting
Montreal, Dec 11 - 14, 2026
Post-secondary Mathematics and Statistics Education in the genAI Era: Adaptations and Impacts on Teaching and Learning, and Departmental Policies
Org: Chantal Buteau (Brock University), Ami Mamolo (Ontario Tech University), Alejandro Martín-Gonzalez (Université de Montréal) and Kitty Yan (University of Toronto)
[PDF]
Org: Chantal Buteau (Brock University), Ami Mamolo (Ontario Tech University), Alejandro Martín-Gonzalez (Université de Montréal) and Kitty Yan (University of Toronto)
[PDF]
- JASON BRAMBURGER, Concordia University
From Solving Problems to Seeing the Mathematics: AI, Access, and Assessment in Applied Mathematics Teaching [PDF]
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Generative AI is creating new opportunities to improve accessibility, integrate computation into applied mathematics, and reconsider what students should learn. AI-generated transcripts and translations can make online course materials available to a much wider audience, while AI-assisted coding can turn computation into a stepping-stone toward deeper mathematical understanding rather than a separate technical prerequisite. AI can also support curriculum development by helping instructors refine learning goals and design exercises that emphasize comparison, interpretation, and synthesis instead of routine application. As conventional problems become easier to automate, greater emphasis can be placed on explaining definitions and results, connecting ideas across a course, and interpreting what computed answers mean. These changes encourage students to see the broader mosaic of modern applied mathematics rather than a collection of isolated techniques. At the same time, in-person tests and hard-copy assignments remain valuable for obtaining reliable evidence of individual learning.
- CARMEN BRUNI, University of Waterloo
- CHANTAL BUTEAU AND ALEJANDRO MARTÍN-GONZALEZ, Brock University and Université de Montréal
- SCHINELLA D’SOUZA, University of Toronto
- CODY HYNDMANN, Concordia University
- JEAN-FRANÇOIS MAHEUX, UQAM
- JÉRÔME PROULX, Université de l'Ontario français -- UQAM
Some (naïve) reflections about mathematics in a GenAI era [PDF]
- CHANTAL BUTEAU AND ALEJANDRO MARTÍN-GONZALEZ, Brock University and Université de Montréal
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In this presentation, I build on issues of the history of computer science to draw some parallels between the advent of computer science in mathematics and the current GenAI era (for mathematics) that we are actually living in. These parallels are addressed through raising a series of distinctions that were historically made in computer science and strongly grounded in mathematical issues and related technologies. The intention through these parallels and distinctions is to offer an occasion for reflecting on our current state of GenAI affair in mathematics and its potential for what might be a not-too-far future in (university) mathematics education and teaching.
- CAMERON REDSELL-MONTGOMERIE, Mohawk College
- ALISTAIR SAVAGE, University of Ottawa
From solution generator to learning partner [PDF]
- ALISTAIR SAVAGE, University of Ottawa
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Rather than asking whether students should use AI, we are asking how AI can be designed to support the kind of learning we actually want. I will describe experiments with custom AI tutors for first-year mathematics and some of the opportunities and challenges we have encountered.