Toward Analyses of Mathematics Classroom Discourse at Scale Using Tools from Applied Mathematics
Effective Years: 2023-2025
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.