Unsilencing Critical Conversations in Social-Studies Teacher Education using Agent-based Modeling

In this article, we argue that when complex sociopolitical issues such as ethnocentrism and racial segregation are represented as complex, emergent systems using agent-based computational models (in short agent-based models or ABMs), discourse about these representations can disrupt social studies teacher candidates' dispositions of teaching social studies without engaging in critical conversations about race and power. Our study extends the literature on agent-based computing to the domain of social studies education, and demonstrates how preservice teachers' participation in agent-based modeling activities can help them adopt a more critical stance toward designing learning activities for their future classrooms.