EDUC-MS08

Using modelling in mathematical biology as an educational tool: from schools to higher education

Tuesday, June 15 at 11:30am (PDT)
Tuesday, June 15 at 07:30pm (BST)
Wednesday, June 16 03:30am (KST)

SMB2021 Follow Tuesday (Wednesday) during the "MS08" time block.

(Natasha Ellison, University of Sheffield, UK), Alexander Fletcher (University of Sheffield, UK), Nick Monk (University of Sheffield, UK)

Description:

Our session aims to reflect upon the uses of mathematical biology as a teaching tool in mathematics lessons in both higher education and prior to university. Our speakers are experienced teachers who demonstrate engaging students in mathematical biology research with successful outreach activities. Furthermore, the speakers discuss enhancing pedagogical practices of teachers with their research and understanding the transition of knowledge into undergraduate education. Good pedagogical practice in both schools and universities of the UK and the US is visited in this session with an aim to share good practice in teaching mathematics with applications from the biological sciences.

Joanna Wares and Marcella Torres

(Department of Mathematics and Computer Science, University of Richmond, USA)

"Making Sense of COVID-19: Mathematics and Data Science Activities Across the Curriculum"

We present mathematical modeling and data science activities created around analyzing and interpreting COVID-19 data. Some of these activities and projects address complex social issues related to COVID-19 such as inequality in testing, wealth distributions, or disparity in health outcomes. Preliminary data suggest that COVID-19 disproportionately impacts minorities and low-income households. Much of the instructional guidance provided for the activities and projects is easily adaptable to a remote learning environment, and each activity includes reflection and discussion in addition to the quantitative work. Mathematical topics covered include: modeling the spread of infectious disease, hypothesis testing, simulation, and data fitting. In addition, we share some of our experiences in teaching these activities across the curriculum, from workshops for high school students, throughout the calculus sequence, to upper-level differential equations courses.

Padmanabhan Seshaiyer

(George Mason University, Fairfax, Virginia, USA)

"Educational frameworks for upskilling the next generation workforce in mathematical biology"

In this talk, we will introduce some novel educational frameworks that provide the opportunity to not only engage students in the tools to represent, understand, analyze and solve real world problems in mathematical biology but also engage them in using tools to make data-driven informed predictions. Such upskilling approaches can help students to become life-long learners going beyond a content-based education in mathematical biology to also include a competency-based training. In particular, mathematical biology must include a variety of learning approaches including experiential learning, inquiry-based learning, challenge based learning and interdisciplinary problem-based learning. In this talk, we will consider some authentic tasks that incorporate a shared collaborative experience with innovative pedagogical practices to advance teaching and learning of mathematical biology in the 21st century.

Perry Hartland-Asbury

(Radley college, UK)

"Modelling Mathematics in Secondary Schools"

A whistle-stop tour looking at how modelling of mathematical modelling (and Biology in particular) is incorporated into UK secondary school teaching, from Key Stage 3, GCSE and A-level teaching.

Thomas Woolley

(Cardiff University, UK)

"Interactive mathematical biology: how to create your first shiny app"

This will be a live coding session in which I demonstrate how to turn the discrete logistic equation into an interactive applet that students can explore. Once you generate one app you can generate many others, or even get kids learning how to write their own codes. I’ll start with the basics in a spread sheet package, so very little coding knowledge will be needed. However, it will be useful if you download R: https://www.r-project.org/ Download R studio as a developer environment (the free one is fine) https://www.rstudio.com/products/rstudio/download/ Make a shiny account. This is the service that will host the app. https://www.shinyapps.io/ Finally, having a github account as somewhere to store your code and make it accessible is also useful. https://github.com/ By providing interactive applets you allow anyone to explore the mathematics of reproduction, modelling and chaos. This experimentation can be a useful tool for clarifying ideas for secondary school students all the way to graduate students. For those who want a sneak peak, we’ll try to create something like https://thomasewoolley.shinyapps.io/Discrete_logistic_equation/, the code for which can be found here https://github.com/ThomasEWoolley/Discrete_logistic_equation

Hosted by SMB2021 Follow

Virtual conference of the Society for Mathematical Biology, 2021.