The value of multiple representations for learning about complex systems

Multiple external representations are a well-researched strategy for understanding phenomena, however, they have yet to be empirically tested with respect to learning about complex systems, and specifically environmental education or learning from models. System dynamics models and agent-based models are tools used to represent complex systems. System dynamics models provide a top-down aggregated representation of a system with an emphasis on understanding time delays and feedback. Agent-based models provide a bottom-up representation, using animation, allowing system-level concepts to emerge from the interaction between individuals. Their joint use is becoming more common among scientists researching complex systems. This experimental study provides empirical evidence for the advantage of using multiple models with Year 9 and 10 students (novices in the use of either model type) to learn about a complex socio-environmental system.