Haensel Maria, Schmitt Thomas M, Bogenreuther Jakob
University of Bayreuth, Professorship of Ecological Services, Bayreuth Center of Ecology and Environmental Research (BayCEER), Universitätsstraße 30, Bayreuth, 95447 Germany.
J Sci Educ Technol. 2023;32(2):256-266. doi: 10.1007/s10956-022-10022-z. Epub 2023 Jan 16.
Agent-based modeling is a promising tool for familiarizing students with complex systems as well as programming skills. Human-environment systems, for instance, entail complex interdependencies that need to be considered when modeling these systems. This complexity is often neglected in teaching modeling approaches. For a heterogeneous group of master's students at a German university, we pre-built an agent-based model. In class, this was used to teach modeling impacts of land use policies and markets on ecosystem services. As part of the course, the students had to perform small research projects with the model in groups of two. This study aims to evaluate how well students could deal with the complexity involved in the model based on their group work outcomes. Chosen indicators were, e.g., the appropriateness of their research goals, the suitability of the methods applied, and how well they acknowledged the limitations. Our study results revealed that teaching complex systems does not need to be done with too simplistic models. Most students, even with little background in modeling and programming, were able to deal with the complex model setup, conduct small research projects, and have a thoughtful discussion on the limitations involved. With adequate theoretical input during lectures, we recommend using models that do not hide the complexity of the systems but foster a realistic simplification of the interactions.
The online version contains supplementary material available at 10.1007/s10956-022-10022-z.
基于主体的建模是一种很有前景的工具，可让学生熟悉复杂系统并掌握编程技能。例如，人类 - 环境系统存在复杂的相互依存关系，在对这些系统进行建模时需要加以考虑。在教学建模方法中，这种复杂性常常被忽视。对于德国一所大学的一组不同背景的硕士生，我们预先构建了一个基于主体的模型。在课堂上，该模型用于教授土地利用政策和市场对生态系统服务的建模影响。作为课程的一部分，学生必须两人一组使用该模型进行小型研究项目。本研究旨在根据学生的小组作业成果评估他们应对模型中所涉及复杂性的能力。所选指标例如有他们研究目标的恰当性、所应用方法的适用性以及他们对局限性的认识程度。我们的研究结果表明，教授复杂系统无需使用过于简单化的模型。大多数学生，即使几乎没有建模和编程背景，也能够应对复杂的模型设置，开展小型研究项目，并对其中涉及的局限性进行深入讨论。在讲座中提供足够的理论输入后，我们建议使用不掩盖系统复杂性但能促进对相互作用进行现实简化的模型。
在线版本包含可在10.1007/s10956 - 022 - 10022 - z获取的补充材料。
