Understanding the world around us is a growing necessity for the whole public, as citizens are required to make informed decisions in their everyday lives about complex issues. Systems thinking (ST) is a promising approach for developing solutions to various problems that society faces and has been acknowledged as a crosscutting concept that should be integrated across educational science disciplines. However, studies show that engaging students in ST is challenging, especially concerning aspects like change over time and feedback. Using computational system models and a system dynamics approach can support students in overcoming these challenges when making sense of complex phenomena. In this paper, we describe an empirical study that examines how 10th grade students engage in aspects of ST through computational system modeling as part of a Next Generation Science Standards-aligned project-based learning unit on chemical kinetics. We show students’ increased capacity to explain the underlying mechanism of the phenomenon in terms of change over time that goes beyond linear causal relationships. However, student models and their accompanying explanations were limited in scope as students did not address feedback mechanisms as part of their modeling and explanations. In addition, we describe specific challenges students encountered when evaluating and revising models. In particular, we show epistemological barriers to fruitful use of real-world data for model revision. Our findings provide insights into the opportunities of a system dynamics approach and the challenges that remain in supporting students to make sense of complex phenomena and nonlinear mechanisms.

了解我们周围的世界对于整个公众来说越来越有必要，因为公民需要在日常生活中就复杂的问题做出明智的决定。系统思维（ST）是一种很有前途的方法，可以为社会面临的各种问题制定解决方案，并被认为是一个跨领域的概念，应该整合到教育科学学科中。然而，研究表明，让学生参与科学技术是具有挑战性的，尤其是在随着时间的推移而发生的变化和反馈等方面。使用计算系统模型和系统动力学方法可以帮助学生在理解复杂现象时克服这些挑战。在本文中，我们描述了一项实证研究，该研究考察了十年级学生如何通过计算系统建模参与科学技术的各个方面，作为符合下一代科学标准的基于项目的化学动力学学习单元的一部分。我们展示了学生解释现象内在机制随时间变化的能力的增强，这种变化超越了线性因果关系。然而，学生模型及其随附的解释范围有限，因为学生没有将反馈机制作为其建模和解释的一部分。此外，我们还描述了学生在评估和修改模型时遇到的具体挑战。特别是，我们展示了有效利用现实世界数据进行模型修正的认识论障碍。我们的研究结果提供了对系统动力学方法的机遇和支持学生理解复杂现象和非线性机制方面仍然存在的挑战的见解。