Experience and Lessons Learned from Using SIMIODE Modeling Scenarios

Abstract

We share our experience and lessons learned from using Systemic Initiative for Modeling Investigations and Opportunities with Differential Equations (SIMIODE) modeling scenarios in our Differential Equations I class at Middle Tennessee State University. Specific projects with Python codes are presented. Discussions are brought forth on how to “best” teach differential equations with modeling approaches while maintaining the balance with the theory. Python notebooks are attached in the Appendix and available at GitHub.

Keywords:

• Differential equations
• modeling scenario
• SIMIODE
• logistic equation
• SIR model

Additional information

Notes on contributors

Wandi Ding

Wandi Ding conducts research on mathematical biology, computational biology, optimal control, mathematical modeling, ordinary and partial differential equations, difference equations and hybrid systems, with applications to population dynamics, disease modeling, natural resource management and systems biology. She also contributes as editor to a number of publications inclulding the Society for Mathematical Biology (SMB) Digest. Her activities permit rich family time, outings in nature, and painting.

Ryan Florida

Ryan Florida is an undergraduate student majoring in Physics & Astronomy, Mathematics and Computer Science at Middle Tennessee State University.

Jeffery Summers

Jeffery Summers is an undergraduate student majoring in Physics & Astronomy and Mathematics at Middle Tennessee State University.

Puran Nepal

Puran Nepal is an undergraduate student majoring in Mathematics at Middle Tennessee State University.

Ben Burton

Ben Burton is an undergraduate student majoring in Physics & Astronomy at Middle Tennessee State University.