Past events

• Past years:  https://fmboire.github.io/uocms/

Fall 2026:

• Stacey Smith? (University of Ottawa) October 2, 2026  Education Colloquium

Title: Can a large life-sciences calculus class benefit from being flipped?

• • Prof Smith? (the question mark is part of her name) is a Professor in the Department of Mathematics and Statistics and is cross-appointed to the School of Epidemiology and Public Health of the Faculty of Medicine.  Her research centres on the mathematical modelling of infectious diseases.  She is a prolific author and a gifted public speaker, with dozens of high-profile media appearances through which she advocates (often with a touch of humour) for mathematical research.

Abstract: Recent educational theory emphasizes the benefits of flipped-classroom courses, which actively support the development of complex metacognitive skills and allow both students and instructors greater flexibility in tailoring the learning process to individuals. With the advent of AI, classroom teaching needs to change, and change quickly. However, flipping a large classroom without additional resources requires adapting strategies from smaller flipped classrooms, and the effects of these strategies at larger scales have not been explored for STEM courses. We implemented flipped-classroom techniques in one section of a large-scale undergraduate Calculus for the Life Sciences course. We then compared final exam results between course sections, and built a predictive model to understand how flipped-classroom techniques influence student success. While course averages were not significantly different across sections, high-achieving students in the flipped-classroom section were more successful at solving higher-complexity problems than their high-achieving peers in traditionally taught sections. However, lower-achieving flipped-classroom students struggled more than their lower-achieving peers at rote problem-solving tasks. Flipping a large classroom appears to improve learning of higher-complexity strategic skills, but it may come at the cost of deeper conceptual understanding for some students. Instructors of larger-scale courses should balance these priorities while designing and teaching a flipped-classroom STEM course. 

• Markus Riedle (King's College London) September 4, 2026

Title: Modelling Random Perturbations in Time and Space: Two Approaches to SPDEs

Abstract:

Stochastic partial differential equations (SPDEs) provide a mathematical framework for systems evolving in time and space under random perturbations. They arise naturally in fields such as engineering, economics, population dynamics, meteorology, physics, and seismology. The randomness may represent external or internal fluctuations, genuinely random future events, or uncertainty in the underlying model. There are two principal ways of formulating SPDEs. In the random field approach, the solution is described directly as a random function of time and space, while in the infinite-dimensional approach, the SPDE is interpreted as a stochastic evolution equation in a suitable function space.

In this talk, I will introduce these two viewpoints, explain how randomness can be modelled in each setting, and discuss the relationship between the two approaches. Particular attention will be paid to Gaussian and non-Gaussian noise, including random perturbations with jumps, and to the mathematical representations of randomness distributed over time and space.