Toward Analyses of Mathematics Classroom Discourse at Scale Using Tools from Applied Mathematics

该项目旨在通过使用分析工具来更好地了解课堂话语如何影响数学的教学和学习，从而为国家利益服务。该项目将关注课堂话语的两个方面：教师如何回应学生的思考，以及教师和学生如何谈论数学权威。该项目将使用定量方法分析来自中年级数学教室的视频数据。研究结果将促进知识和理解教师和学生如何在数学课堂上使用话语来创建社区并建立学生对数学的理解。此外，它还将研究定量工具如何帮助研究人员系统地分析课堂话语，并有可能发展为更大规模的研究项目。与中期职业发展计划的意图一致，该项目使研究人员和合作伙伴能够实质性地推进他们的研究计划和职业轨迹。本研究将运用统计语篇分析和社会网络分析的定量工具对数学课堂语篇进行分析。三个研究目标指导这项工作。首先是扩大可用于研究数学课堂话语的方法工具，并确定这些工具的功效，效率和可扩展性。第二个是进行时间分析的数学课堂话语在多个时间尺度上使用统计话语分析的工具，以了解学生的思维和数学权威的反应性话语结构的变化。第三，也是最后，是探索社会网络分析的可行性，代表社会和智力关系作为一个指标，在一个给定的课堂通过数学课堂话语的社区。主要数据是来自现存数据集的视频记录和成绩单，该数据集由11个中年级教室的145节数学课组成。拟议项目的很大一部分将是从统计和社会网络分析中确定和应用适当的方法工具，以实现研究目标。提出的分析方法包括将序列分析和时间序列方法纳入对数线性模型，使用卡方值来比较不同时间间隔内编码类别的某些组合的相对频率，计算语言学，使用社交网络分析开发课堂社区的网络模型，以及探索课堂网络的属性（例如，密度、节点中心性等）以及网络及其属性如何随时间变化。研究结果将完善和扩展用于研究课堂话语的分析工具，并提供有关话语结构的知识，这些结构对学习及其在课堂上的变化很重要。该项目由NSF的EHR Core Research Building Capacity in STEM Education Research（ECR：BCSER）项目提供支持，该项目旨在培养研究人员开展高质量STEM教育研究的能力。该奖项反映了NSF的法定使命，通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national interest by using analytic tools to better understand how classroom discourse affects the teaching and learning of mathematics. The project will focus on two aspects of classroom discourse: how teachers respond to student thinking, and how teachers and students talk about mathematical authority. The project will use quantitative methods to analyze video data from middle-grades mathematics classrooms. Results will advance knowledge and understanding how teachers and students use discourse in mathematics classrooms to create community and build student understanding in mathematics. Additionally, it will investigate how quantitative tools may help researchers systematically analyze classroom discourse with potential to grow to larger-scale research projects. Consistent with the Mid-Career Advancement Program's intent, this project enables the investigator and collaborative partners to substantively advance their research programs and career trajectories. This research project will use the quantitative tools of statistical discourse analysis and social network analysis to analyze mathematics classroom discourse. Three research aims guide this work. First is to expand the methodological tools available to study mathematics classroom discourse and determine the efficacy, efficiency, and scalability of those tools. Second is to conduct temporal analyses of mathematics classroom discourse at multiple timescales using tools from statistical discourse analysis to understand variability in the discursive constructs of responsiveness to student thinking and mathematical authority. Third, and finally, is to explore the viability of social network analysis to represent social and intellectual relationships as an indicator of community in a given classroom via mathematics classroom discourse. The primary data is video recordings and transcripts from an extant data set comprised of 145 mathematics lessons across 11 middle-grades classrooms. A large part of the proposed project will be identifying and applying appropriate methodological tools from statistics and social network analysis to address the research aims. Proposed analytic methods include incorporating sequential analyses and time series methods into log linear models, using chi-square values to compare the relative frequency of certain combinations of coding categories across varying time intervals, computational linguistics, developing network models of classroom community using social network analysis, and exploring properties of classroom networks (e.g., density, node centrality, etc.) and how networks and their properties change over time. Research findings will refine and expand analytic tools used to study classroom discourse and provide knowledge about the discursive constructs that matter for learning and their variability within classrooms. The project is supported by NSF's EHR Core Research Building Capacity in STEM Education Research (ECR: BCSER) program, which is designed to build investigators’ capacity to carry out high-quality STEM education research.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.