Ümit Aslan - Learning Sciences, Northwestern University

Abstract: Agent-based modeling provides a powerful computational infrastructure to construct dynamic representations of scientific phenomena that can augment analytical models in unique and meaningful ways. However, although it is used extensively in the field of complex systems and embraced by social scientists, only a handful of researchers in natural sciences incorporate agent-based modeling components into their theoretical investigations. In this talk, I will present findings from two of my prior studies on reconstructing existing theoretical models through agent-based modeling and I will argue that the tools and methods of Learning Sciences can help us cultivate productive ways of augmenting existing theoretical studies with agent-based components in a manner that is commensurate with scientists’ ways of thinking, which would in turn accelerate adoption of the complexity lens by more and more natural scientists.