EduMirror: Modeling Educational Social Dynamics with Value-driven Multi-agent Simulation

摘要

Uncovering the causal mechanisms of educational social dynamics is critical for designing effective pedagogical policies. However, traditional methods face a fundamental dilemma. vational studies often lack causal power, while controlled experiments are ethically prohibitive. While LLM-powered multi-agent simulations offer a scalable in silico alternative, current approaches often fail to support rigorous experimentation due to shallow psychological grounding and unquantifiable interactions. To address this, we introduce EduMirror, a multi-agent simulator for the scientific study of educational social dynamics. EduMirror employs a value-driven cognitive architecture for agents that grounds agent behaviors in social value and intrinsic motivation, coupled with a dual-track measurement protocol that utilizes LLMs to quantify both overt actions and latent psychological states. We validate the realism and usability of our platform through case studies on school bullying and group cooperation. The results show that EduMirror generates realistic social phenomena aligned with established theories and measurable by empirical criteria. These properties enable structured in-silico educational research. Results demonstrate that EduMirror generates dynamics aligned with established theories, providing a robust tool for hypothesis testing in educational science.