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关键学习成果是理解和预测原子和分子的行为的能力。原子或分子的类型、数量和其他特性决定它们是否相互作用以及如何相互作用。在NSF的EHR核心研究(ECR)计划的支持下，该项目寻求通过检查学生解释和使用关于原子和分子及其相互作用的图形表示的能力的发展来服务于国家利益。这项研究将涉及两项研究：(1)随着学生在一般化学课程中的进步，对个人的图形推理和对原子和分子的想法的分析；(2)学生如何在协作的课堂环境中使用和使用图形进行推理。这项研究有望增加对学生使用图表进行推理的能力如何随着时间的推移而变化的理解。这些关于学生学习的证据可以帮助教育研究人员，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，因此该项目的发现可能适用于其他STEM领域。因此，将这项研究的研究成果转化为实践，最终有可能改善STEM课程的教和学，并通过增加在这些研究领域取得成功的学生数量来造福社会。本项目将探索学生如何了解不同的群体模式，即在颗粒物水平上系统内单个粒子存在一系列状态的想法，这被假设为化学学习的一个门槛概念。此外，该团队将研究学生如何使用与不同人口图式相关的图形表示来解释和做出推理。尽管与颗粒物水平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此类模型并从中做出推断的基于理论的定性描述相对较少。与颗粒物水平变异性有关的模型，如分布图和反应坐标图，尤其重要。该项目的研究目标是：(1)描述一般化学课程顺序对个体学生在颗粒水平上与变异性有关的概念结构的影响，包括他们解释和从图形表示进行推理的能力；(2)描述学生在合作学习活动中联合意义形成的瞬间动态。为了解决目标1，我们将在两个学期的本科普通化学序列中进行一项关于与不同种群图式相关的图形模型的多个半结构化访谈的研究。这将涉及到使用眼球跟踪技术来分析学生参与的陈述中的特征，以补充他们的口头解释。此外，面试将考察学生如何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。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基因学习分析方法进行。该项目的成功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演示文稿分享。编写的学习材料将通过教员研讨会和化学教育交流网站进行传播。因此，该项目将促进本科生对涉及不同总体模式的图表的解释相关理解的了解。此外，它还有可能为STEM教育的合作学习活动的设计和实施提供信息，并宣传从其他领域改编的方法，以便在以学科为基础的教育研究中更广泛地使用。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、扩大对STEM的参与以及STEM劳动力发展的工作。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.