Surprisingly Stochastic: Learning and Application of Emergent Behavior Using Interactive Simulations of Nano-Mechanical Biological Systems

Paul EganCarnegie Mellon University
Christian SchunnUniversity of Pittsburgh
Jonathan CaganCarnegie Mellon University
Phillip LeDucCarnegie Mellon University

Abstract

Emergence is pervasive in complex systems, and often produces surprising phenomenon that are challenging to understand and apply, especially regarding inter-level causalities. Here, we study engineering undergraduates’ capacity to understand and solve design problems concerning inter-level causalities in nanomechanical biological systems. We developed a GUI with an agent-based molecular simulation that calculates performance and renders animations in real-time as users adjust design inputs. We randomly assigned undergraduate engineering students to learning groups with support of animated simulations or charts. Both groups improved on pre/post design problems. On assessments of understanding inter-level causality, only the animation group demonstrated an understanding. Both groups were then presented contrasting animations of continuous and intermittent systems, resulting in about half of participants in each group demonstrating an understanding of inter-level causal behaviors. Study findings demonstrate the difficulty in understanding inter-level causal relationships, the helpfulness of software tools, and that greater learning may improve design performance.

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Surprisingly Stochastic: Learning and Application of Emergent Behavior Using Interactive Simulations of Nano-Mechanical Biological Systems (754 KB)



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