ArguMath: AI-Simulated Environment for Pre-Service Teacher Training in Orchestrating Classroom Mathematics Argumentation
Jiwon Chun, Yuling Zhuang, Armanto Sutedjo, Colin Xu, Rong Ren, Meng Xia

TL;DR
ArguMath is an AI-driven simulated classroom environment designed to help pre-service mathematics teachers practice and improve their skills in orchestrating classroom argumentation through realistic simulations and reflective tools.
Contribution
This paper introduces ArguMath, a novel AI-based environment that combines realistic student simulations, customization, and reflection to support teacher training in mathematical argumentation.
Findings
ArguMath shows promise in enhancing teachers' orchestration skills.
Participants found ArguMath useful for practicing theory-aligned questioning.
The system's design aligns with teachers' key requirements for simulation environments.
Abstract
Facilitating productive mathematical argumentation, especially asking rational questions, is essential yet remains challenging for pre-service mathematics teachers (PMTs), who often have limited opportunities to apply abstract theoretical knowledge in authentic practice. At the same time, recent advances in large language models (LLMs) have expanded the potential for simulating students in educational settings, enabling low-risk environments for instructional practice. To inform the design of a system that supports PMTs in orchestrating classroom argumentation, we conducted a formative study with eight experienced mathematics teachers to identify key design requirements, including personalization, realistic simulations, structured reflection, and ease of use. Building on these requirements, we developed ArguMath, an AI-simulated classroom environment that supports PMTs in practicing the…
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