Talks

Talks#

Computational Teaching and Learning in Mathematics at UBC

  • Patrick Walls

  • Department of Mathematics

  • University of British Columbia

  • patrickwalls.github.io

  • Abstract: We have been using Python, Jupyter, Syzygy, GitHub, nbgrader, CanvasAPI and Jupyter Book in various combinations in several undergraduate courses in the Department of Mathematics at UBC since 2015. We will describe our approach to computational teaching and learning including instructional design, open educational resources, auto-graded assessments and TA training.

Supporting the Integration of Numerical Computing in Physics Education

  • Danny Caballero

  • Department of Physics and Astronomy

  • Department of Computational Mathematics, Science and Engineering

  • Michigan State University

  • dannycaballero.info

  • Abstract: Numerical computing has transformed modern science, enabling researchers to analyze vast datasets, simulate complex experiments, and gain insights into intricate systems. Despite its critical role, computing remains underrepresented in most science curricula. In this talk, I will address the pressing need to integrate computational training into physics education and present research exploring challenges across all scales—from institutional structures to individual student understanding. I will discuss how these findings can drive the computational revolution in science education by informing institutional incentives, teaching practices, course activities, and assessment tools. Additionally, I will examine the opportunities and challenges posed by generative artificial intelligence, highlighting ongoing research in this area. This work is supported by Michigan State University’s CREATE for STEM Institute, the National Science Foundation, the Norwegian Agency for Quality Assurance in Education (NOKUT), the Norwegian Research Council, and the Thon Foundation.