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

使用应用数学工具对数学课堂话语进行大规模分析

• 批准号: 2218770
• 负责人: Jessica Bishop
• 金额: $ 35.11万
• 依托单位: Texas State University - San Marcos
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218770&HistoricalAwards=false
• 关键词: Toward; Analyses; Mathematics; Classroom; Discourse

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.

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与学，从而为国家利益服务。该项目将重点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中学数学课堂的视频数据。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和建立学生对数学的理解。此外，它将研究定量工具如何帮助研究人员系统地分析课堂话语，并有可能发展到更大规模的研究项目。与中期职业发展计划的意图一致，该项目使研究者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。本研究项目将使用统计话语分析和社会网络分析的定量工具来分析数学课堂话语。三个研究目标指导这项工作。首先是扩展可用于研究数学课堂话语的方法论工具，并确定这些工具的功效、效率和可扩展性。其次，利用统计语篇分析的工具，在多个时间尺度上对数学课堂语篇进行时间分析，以了解对学生思维和数学权威的反应性语篇结构的变异性。第三，也是最后，是探索社会网络分析的可行性，通过数学课堂话语来表示社会和智力关系，作为特定课堂中社区的指标。主要数据是来自11个中等年级教室145节数学课的现有数据集的视频记录和文本。拟议项目的很大一部分将从统计和社会网络分析中确定和应用适当的方法工具来解决研究目标。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，使用社会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中的可变性很重要。该项目由美国国家科学基金会EHR STEM教育研究核心研究能力建设项目（ECR: BCSER）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。