Explanations of phenomena in chemistry are grounded in discussions of particulate-level behavior, but there are limitations to focusing on single particles, or as an extension, viewing a group of particles as displaying uniform behavior. More sophisticated models of physical processes evoke considerations related to the dynamic nature of bulk solutions, in which an ensemble of molecules exists with a distribution of values that vary with respect to different parameters (e.g., speed, kinetic energy, etc.). Viewing phenomena as a varied population instead of a homogenous solution has been identified as a foundational idea that is critical for reasoning in chemistry, but little work has investigated how students reason about these ideas and how instructors can support students in viewing phenomena as a distribution of states. In this qualitative study, during semi-structured interivews twelve undergraduate general chemistry students were provided with frequency distribution graphs (number of molecules vs. speed, number of molecules vs. kinetic energy) and were asked to provide explanations and make predictions. The design and analysis of this study was informed by coordination class theory, a model within the knowledge-in-pieces perspective of cognition that defines a concept as a combination of approaches for obtaining information (read-out strategies) and a cluster of knowledge elements used to draw conclusions (causal net). Framing the varied population schema as a coordination class, this work focuses on the interaction between features students attended to in distribution graphs and the ideas they discussed. Analysis indicates students have productive resources for reasoning about a varied population in general terms, but these ideas are not necessarily activated when interpreting graphs, as reflected in the students’ readout strategies. Moreover, we posit that one of the barriers toward interpreting distribution graphs was the inappropriate application of covariational reasoning. As a practical consideration, we encourage interested instructors to review the Appendix, which provides a short summary of the main findings and suggestions for practitioners.

中文翻译：

---

学生的解释和图形表示的使用：通过将各种人口图式建模为协调班而提供的见解

对化学现象的解释以对颗粒级行为的讨论为基础，但是在关注单个粒子或作为扩展（将一组粒子视为显示均匀行为）方面存在局限性。物理过程的更复杂模型引起了与整体溶液动力学性质相关的考虑，其中分子的整体存在，其值的分布相对于不同参数（例如，速度，动能等）有所不同。）。将现象视为多样化的群体而不是均质的解决方案已被认为是对化学推理至关重要的基础思想，但是很少有研究调查学生如何对这些思想进行推理，以及导师如何支持学生将现象视为物质的分布。状态。在这项定性研究中，在半结构化的实习课程中，向十二名本科化学专业的学生提供了频率分布图（分子数与速度，分子数与动能的关系），并被要求提供解释和做出预测。本研究的设计和分析是通过协调分类理论进行的，协调分类理论是认知的逐层知识模型，该模型定义了概念作为获取信息的方法（读出策略）和用于得出结论的一组知识元素（因果网络）的组合。将不同的人口图式作为协调班来进行，这项工作着重于学生在分布图中所关注的特征与他们所讨论的思想之间的相互作用。分析表明，学生一般而言都具有用于推理各种人口的推理的生产资源，但是在解释图形时，不一定要激活这些想法，这反映在学生的读出策略中。此外，我们认为，解释分布图的障碍之一是协变推理的不适当应用。出于实际考虑，我们鼓励感兴趣的教师复习附录，