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Agent-Based Modeling and Simulation in Mathematics and Biology Education
Erin N Bodine1, Robert M Panoff2, Eberhard O Voit3
1Department of Mathematics and Computer Science, Rhodes College, 2000 N. Parkway, Memphis, TN, 38112, USA. bodinee@rhodes.edu.
Bulletin of Mathematical Biology
|July 30, 2020
Summary
Agent-based models (ABMs) are powerful computational tools for simulating complex biological systems. This work discusses their application and pedagogical value in biology and mathematics education.
Area of Science:
- Computational Biology
- Mathematical Modeling
- Educational Technology
Background:
- Agent-based models (ABMs) are increasingly utilized for studying biological systems due to computational advancements.
- ABMs are effective for modeling processes with stochasticity, nonlinear interactions, and spatial heterogeneity.
Purpose of the Study:
- To provide a synopsis of the agent-based modeling approach for simulating biological systems.
- To discuss the role and limitations of ABMs in biology and mathematics classrooms.
Main Methods:
- Review and synthesis of agent-based modeling principles.
- Discussion of ABM applications in biological system simulation.
- Analysis of ABM integration into educational curricula.
Main Results:
- Agent-based modeling offers a robust framework for understanding complex biological phenomena.
- ABMs serve as valuable pedagogical tools for teaching biological and mathematical concepts.
Conclusions:
- Agent-based models are versatile tools for both scientific research and educational purposes.
- Understanding the limitations of ABMs is crucial for effective implementation in classrooms.
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