Making sense of models: How teachers use agent‐based modeling to advance mechanistic reasoning
Author(s)Hsiao, Ling; Lee, Irene; Klopfer, Eric
MetadataShow full item record
Computer modeling promotes mechanistic reasoning when learners build and analyze models of complex systems to explore causal mechanisms and use models to generate patterns. StarLogo Nova (SLN), an agent‐based modeling (ABM) environment, enables novice programmers to model a system's individual components and investigate its emergent, collective behavior. Through case analysis of teachers using SLN, we demonstrate how ABM advances thinking about mechanisms generating phenomenon. Teachers who used simulation combined with the decoding of SLN models utilized mechanistic reasoning to make sense of how and why complex phenomenon emerged.
DepartmentMassachusetts Institute of Technology. Department of Comparative Media Studies
British Journal of Educational Technology
Ling, Hsiao et al. "Making sense of models: How teachers use agent‐based modeling to advance mechanistic reasoning." British Journal of Educational Technology 50, 5 (July 2019): 2203-2216 © 2019 British Educational Research Association
Author's final manuscript