Designing for discovery learning of complexity principles of congestion by driving together in the TrafficJams simulation

We propose and evaluate a framework supporting collaborative discovery learning of complex systems. The framework blends five design principles: (1) individual action: amidst (2) social interactions; challenged with (3) multiple tasks; set in a (4) a constrained interactive learning environment that draws attention to (5) highlighted target relations. The framework addresses a persistent tension in discovery-based pedagogy between offering students the freedom to initiate, experiment, and explore and providing them with tailored experiences with many instances of particular relations underlying the target conceptual structure. The framework was realized with TrafficJams, a participatory simulation in which students drive together. A class of high-school students worked with TrafficJams over 2.5 h. The teacher's role was to orchestrate the activity but there was no explicit instruction of the traffic and complexity principles. The students completed preand post-test questionnaires and their activities were observed and logged. In terms of driving in the simulation, the students learned to drive in ways that reduced congestion in traffic by decreasing lane and speed changes, and keeping their speed down. Even though there was no explicit teaching, half of the students learned that car speed distribution alone can generate traffic jams with no additional causes; and, keeping a safe following distance from the next driver increases everyone's speed. Our study suggests that the learning environment partially met both the overarching design goal of constrained discovery and the specific content goal of systems reasoning.