Making ODEs Come Alive With Python
Linear algebra and differential equations through dynamic models.
Presented by:
Hyeeun Jang, Abilene Christian University
Hear it from the author:
Transcript:
Key Words:
Python, Ordinary Differential Equations, Active Learning
Abstract:
When working with systems written in matrix form, students often don’t clearly see how this connects to the ideas they learned in Linear Algebra. I use Python to help students visualize eigenvalues, phase portraits, and solution behavior. This helps them recognize how concepts from linear algebra naturally appear in ordinary differential equations (ODEs). I will share some examples and student work.
Outcomes:
1. Discuss how Python helps students connect matrix concepts to phase portraits.
2. Share examples of Python code.
3. Generate ideas for strengthening connections between linear algebra and ODEs.
References:
Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223–231. https://doi.org/10.1002/j.2168-9830.2004.tb00809.x
Perdikaris, P. (2018). Mathematics and Python: A student’s introduction to computational modeling. Springer.
Boyce, W. E., & DiPrima, R. C. (2017). Elementary differential equations and boundary value problems (11th ed.). Wiley.