Abstract for: Mental Models of Dynamical Systems: Taking Stock and Looking Ahead
This paper deals with the representation of the structure of mental models of dynamical systems (MMDS). Systems are dynamical if its present output depends on past input. Available research about mental models has most often accounted only for aspects which have the capability to form a static mental model—i.e., simple variables, common links, and their polarity. The properties which translate such models into dynamical mental model are feedback loops and delays. Not many mental model studies have accounted for them up to now. The contribution of this paper is twofold: First, we elaborate the structural content of a MMDS—the conceptual structure. And second, we use this conceptual structure to enrich the seminal definition of a MMDS. Based on a current overview of research about MMDS, we lay out paths for further research.