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Updated: Aug 13, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
Teaching the Modeling of Human-Environment Systems: Acknowledging Complexity with an Agent-Based Model.
Maria Haensel1, Thomas M Schmitt1, Jakob Bogenreuther1
1University of Bayreuth, Professorship of Ecological Services, Bayreuth Center of Ecology and Environmental Research (BayCEER), Universitätsstraße 30, Bayreuth, 95447 Germany.
Agent-based modeling effectively teaches complex systems and programming skills. Even students with limited backgrounds can successfully use complex models for research and discuss limitations.
Area of Science:
- Environmental Science
- Computer Science
- Education
Background:
- Agent-based modeling (ABM) is valuable for teaching complex systems and programming.
- Teaching often simplifies complex human-environment interactions, neglecting model interdependencies.
- Master's students require tools to understand complex system modeling.
Purpose of the Study:
- Evaluate student ability to manage complexity in a pre-built ABM.
- Assess research project outcomes, methods, and limitation acknowledgment.
- Determine if complex models are suitable for teaching system dynamics.
Main Methods:
- Utilized a pre-built agent-based model for teaching land use policy impacts.
- Students conducted group research projects using the model.
- Evaluated project goals, methods, and discussion of model limitations.
Main Results:
- Most students, regardless of prior experience, successfully used the complex ABM.
- Students effectively conducted research projects and analyzed model limitations.
- Complex models are viable for teaching, not overly simplistic ones.
Conclusions:
- Teaching complex systems does not require overly simplified models.
- Complex ABMs can be effectively used by students with adequate support.
- Recommend using realistic, complex models with theoretical grounding for education.
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