NSF-BSF: Learning the concept of Dynamic Equilibrium across disciplines with SystEms Augmented Mechanistic Representations

动态平衡（DE）是系统科学中引人入胜的一个方面。DE描述了不断发生变化的情况，但它们相互抵消。例如，我们的身体保持恒定的温度，而周围的环境可能是热的或冷的，或者生态系统保持周期性的人口水平，即使捕食者和猎物死亡和繁殖。理解这样的动力系统如何保持稳定是理解世界秩序和模式的基础。因此，理科生理解这个概念，帮助他们发展科学能力是至关重要的。尽管DE的概念很重要，但是很多人很难理解它。稳定性和变化之间的对比令人困惑，因此人们倾向于认为系统是静态的。PI的工作表明，通过引入可视化模型和模拟，学生在学习科学时获得了更深入的理解和更投入。然而，将这种现象与元素相互作用的方式联系起来仍然存在一个问题。项目通过进行一系列的研究和软件设计迭代来解决这个问题。该项目开发了一系列可能的基于计算机的表示，这些表示可以支持对DE的更连贯的理解。对这些候选表示进行测试，并选择一个获胜者。获胜者将成为模型和模拟的新工具。这些增强的模拟然后被用来创建科学单元。该团队与科学教师合作，建立关于DE现象的学习单元。跨文化比较将探讨在美国和以色列学校中获胜的代表是如何不同地学习的。该提案有两个主要目标：(1)构建一个理论上和认知上可行的学习DE的框架，以平衡机制和因果关系与鲁棒性和一般性；(2)开发一个扩展表征，将系统特征覆盖在机制过程上，研究人员称之为SEAM（系统扩展机制）表征。构建DE框架涉及四个方面的研究：(1)分析与DE相关的科学教育标准；(2)对学生英语学习理念的研究文献分析；(3)调查科学家关于DE的显性和隐性交流；(4)研究学生对DE的直觉。SEAM表征的开发包括3个研究：(5)设计3名有经验的科学教师的候选人；(6)基于三种表征的学习研究，最终对美国和以色列学生的学习进行跨文化比较；(7)协商选择最终SEAM代表。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Learning the concept of Dynamic Equilibrium across disciplines with SystEms Augmented Mechanistic Representations A fascinating aspect of systems in science is dynamic equilibrium (DE). DE describes situations, in which changes continually happen, but they balance each other out. Examples include our body maintaining a constant temperature while the surroundings can be hot or cold, or an ecosystem maintaining cyclical population levels even as predators and prey die and reproduce. Understanding how such dynamical systems remain stable is fundamental to understanding order and pattern in the world. Thus, it is crucial that students of science come to understand this concept, helping them develop science proficiency. Despite the importance of the concept of DE, it is hard for many people to understand. The contrast between stability and change is confusing so people tend to think of the system as static. The PI’s work has shown that by introducing visual models and simulations, students get a deeper understanding and are more engaged when learning science. Yet, there still remains a problem with connecting the phenomenon to the way the elements interact. The project addresses this problem by conducting a series of studies and software design iterations. The project develops a range of possible computer-based representations, which can support a more coherent understanding of DE. These candidate representations are tested, and a winner chosen. The winner becomes a new tool added to the models and simulations. These augmented simulations are then be used to create science units. The team works with science teachers to build learning units on DE phenomena. A cross-cultural comparison will explore how the winning representation is differently learned in US and Israeli schools. The proposal has two main objectives: (1) construct a theoretically and cognitively viable framework for learning DE that balances mechanism and causality with robustness and generality, and (2) develop an augmented representation that overlays systemic features upon mechanistic processes, what the investigators call SEAM (SystEms Augmented Mechanistic) representations. Creating the DE framework involves four studies: (1) analysis of science education standards related to DE; (2) analysis of the research literature on students’ ideas regarding DE; (3) investigating scientists’ explicit and implicit communication regarding DE; (4) research into students’ intuitions regarding DE. Developing the SEAM representation involves 3 studies: (5) design of three candidates with experienced science teachers; (6) learning research with the three representations, culminating in a cross-cultural comparison of students’ learning in the US and in Israel; (7) deliberative selection of the final SEAM representation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.