In this talk we discuss our ongoing project of integration of CT, and in particular, Python programming, into a large math for life sciences course. This project involves many moving parts - from working on changing students’ attitudes toward programming and addressing the anxieties of many who

claimed to have never seen computer code, to designing coding activities which are meaningful and complement the material that is taught in the course.

We will focus on coding activities and the way they enriched mathematics instruction. Coding brought forward aspects of calculus that are not covered extensively and which students, lacking adequate exposure, find difficult and confusing. For instance, working with a function as a discrete object naturally introduces the need to approximate derivatives and integrals, and thus shines a bright light onto the secant line approximation and Riemann sums. Using Python, we are able to push biological models farther to make them more “palpable,” and thus more meaningful. As well, Python notebooks (Jupyter) seem to be a good way to introduce, through experimentation, new math material.