Complex systems are challenging to design, particularly because of multi-level organizations that lead to non-obvious relationships among design components. One aspect of that challenge is how to effectively present complex information to the user for systems with multiple levels of organization. Two contrasting design graphical user interfaces (GUIs) were developed to aid multi-level biosystem design: a GUI with feedback via performance charts that emphasized learning of parametric relationships, and a GUI with feedback via agent-based animations that emphasized learning of inter-level causalities. The effectiveness of these interfaces is compared through assessing the design proficiency of human users for optimization design tasks. Results from user interactions with the interfaces demonstrated that users with both interfaces improved on pre-/post-learning design tasks, and users that demonstrated an understanding of inter-level causal relationships had greater improvement. However, only users with the animations interface tended to learn inter-level causal relationships. All users were then presented contrasting animations of systems with opposing emergent system behaviors, resulting in many more participants demonstrating an understanding of inter-level causal behaviors. These findings reveal the usefulness of interactive software tools for supporting engineers in overcoming challenges of complex systems design. Particularly, that successful design of complex systems requires unique reasoning skills that are informed by knowing how system components relate across levels, and specialized interfaces with animations provide information necessary for the learning these relationships.

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