ECR DBER DCL: Investigating Undergraduate Chemistry Students’ Reasoning and Conceptual Change Related to Graphs of Particulate-Level Variability

本科化学课程的一个重要学习成果是理解和预测原子和分子行为的能力。原子或分子的类型、数量和其他特征决定了它们是否相互作用以及如何相互作用。在美国国家科学基金会EHR核心研究（ECR）项目的支持下，该项目旨在通过研究学生解释和使用原子和分子及其相互作用的图形表示的能力的发展，为国家利益服务。这项研究将包括两项研究：(1)分析学生在学习普通化学课程过程中对原子和分子的图形推理和想法；(2)学生如何在合作课堂环境中对图表进行推理。这项研究有望加深对学生使用图表进行推理的能力如何随时间变化的理解。这些关于学生学习的证据可以帮助教育研究者，并将更好地支持学生对化学关键概念的知识发展。由于所有科学、技术、工程和数学（STEM）领域都涉及图形推理，因此项目发现可能适用于其他STEM领域。因此，将本研究的研究成果转化为实践，最终有可能改善STEM课程的教学和学习，并通过增加在这些研究领域取得成功的学生人数来造福社会。该项目将探索学生如何学习不同的种群模式，即在粒子水平上，系统内单个粒子有一系列状态，这被假设为化学学习的阈值概念。此外，该团队将研究学生如何使用与不同人口模式相关的图形表示来解释和推断。尽管与微粒级系统相关的图形模型很流行，也很重要，但关于普通化学学生如何解释和从这些模型中做出推论的基于理论的定性描述相对较少。与微粒级别的可变性相关的模型，如分布图和反应坐标图，尤为重要。该项目的研究目标是：(1)描述普通化学课程序列对单个学生在颗粒水平上与可变性有关的概念结构的影响，包括他们从图形表示中解释和推断的能力；(2)描述协作学习活动中学生联合意义建构的即时动态。为了实现目标1，我们将进行一项研究，在整个两个学期的本科普通化学序列中，我们将对与不同人口模式相关的图形模型进行多次半结构化访谈。这将涉及到使用眼球追踪技术来分析表征中的特征，学生参加这些表征来补充他们的口头解释。此外，访谈将考察学生连接和使用知识元素来推断化学性质（如扩散、反应速率和平衡）的方式。对于目标2，项目团队将调查学生群体的话语和动态，因为他们参与了以图形推理为重点的协作学习活动，旨在强调系统中的可变性。对这两个目标的分析将通过协调类理论和微遗传学习分析方法进行。该项目的成功与否将由一个由化学学科专家和教育研究专家组成的咨询小组进行评估。研究成果将通过学术出版物和会议报告分享。开发的学习材料将通过教师讲习班和化学教育交流网站传播。因此，该项目将促进了解本科生如何发展与解释涉及不同人口模式的图表相关的理解。此外，它有可能为STEM教育的协作学习活动的设计和实施提供信息，并传播从其他领域改编的方法，以便在基于学科的教育研究中得到更广泛的应用。该项目由EHR核心研究计划资助，该计划支持推进STEM学习和学习环境的基础研究，扩大STEM参与和STEM劳动力发展的工作。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。

A key learning outcome in undergraduate chemistry courses is the ability to understand and predict the behavior of atoms and molecules. The types, amounts, and other characteristics of atoms or molecules determine whether and how they interact. With support from NSF’s EHR Core Research (ECR) program, this project seeks to serve the national interest by examining the development of students’ ability to interpret and use graphical representations about atoms and molecules and their interactions. The research will involve two studies: (1) Analysis of individual student’s graphical reasoning and ideas about atoms and molecules, as the student progresses through a general chemistry course sequence; and (2) How students reason with and about graphs in a collaborative classroom environment. This research is expected to increase understanding about how students’ abilities to use graphs for making inferences change over time. This evidence about student learning can help education researchers and will better support development of students’ knowledge about key concepts in chemistry. Since all science, technology, engineering, and mathematics (STEM) fields involve graphical reasoning, the project findings may be applicable to other STEM fields. Thus, translation of research findings from this research into practice ultimately has the potential to improve teaching and learning in STEM courses and benefit society by increasing the number of students who are successful in these areas of study.This project will explore how students learn about varied population schema, the idea that there are a range of states for individual particles within a system at the particulate level, which has been hypothesized to be a threshold concept for chemistry learning. In addition, the team will study how students interpret and make inferences using graphical representations related to varied population schema. Despite the prevalence and importance of graphical models that relate to particulate-level systems, there are relatively few theory-based qualitative accounts of how general chemistry students interpret and make inferences from such models. Models that relate to particulate-level variability, such as distribution graphs and reaction coordinate diagrams, are particularly important. The research aims of the project are: (1) to describe the impact of a general chemistry course sequence on individual student’s conceptual structures pertaining to variability at the particulate level, including their ability to interpret and make inferences from graphical representations; and (2) to describe in-the-moment dynamics of students’ joint sense-making during a collaborative learning activity. To address aim 1, we will conduct a study with multiple semi-structured interviews regarding graphical models related to the varied population schema throughout the two-semester undergraduate general chemistry sequence. This will involve the use of eye-tracking technology to analyze features in representations that students attend to supplement their verbal explanations. Moreover, interviews will examine the ways in which students connect and use knowledge elements to make inferences about chemical properties such as diffusion, reaction rate, and equilibrium. For aim 2, the project team will investigate the discourse and dynamics of groups of students as they engage in a graphical-reasoning focused collaborative learning activity designed to emphasize the variability in a system. Analysis for both aims will be informed by coordination class theory and the microgenetic learning analysis approach. The success of the project will be assessed by an advisory panel comprised of disciplinary experts in chemistry and experts in educational research. Research findings will be shared via scholarly publications and conference presentations. Learning materials developed will be disseminated via faculty workshops and on the Chemical Education Xchange website. Thus, the project will advance knowledge of how undergraduate students develop understandings related to interpreting graphs that involve the varied population schema. In addition, it has potential to inform the design and implementation of collaborative learning activities for STEM education, and to propagate methodologies adapted from other fields for broader use in discipline-based education research. This project is funded by the EHR Core Research Program, which supports work that advances fundamental research on STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.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.