SUMMARY

The engineering design process involves the representation of knowledge about a system and the communication of that knowledge in order to achieve worthwhile solutions to a problem. Functional modeling provides a framework for system representation that structures system knowledge into a flow-based diagram used for abstraction and communication. Informed by cognitive psychology literature, elicitation of mental models gives insight into the knowledge an engineer or designer has about a system holistically beyond a functional understanding alone. Further, different approaches to the prototyping process likely affect an engineer’s or designer’s mental model of a given system, therefore affecting design outcome. This research first focuses on measuring functional decomposition as a strategy by refining a functional modeling scoring rubric that can be used as an instructional tool or an evaluation metric for design research. With this established, a second study was designed to investigate whether or not functional modeling instruction provides a framework that enhances understanding of engineering systems. A mental model elicitation instrument was developed to investigate the effects of functional decomposition on systems understanding. This second study compared engineering and non-engineering undergraduates' mental models of common systems and yielded improved mental model representation after a functional modeling intervention and product teardown activity. This also revealed that technological literacy can be increased for non-STEM majors using this method. A third study involving graduate engineering students helped validate the mental model elicitation method and confirmed that a functional modeling intervention increased the completeness of students’ mental model representations, which was attributed to a stronger framework for system communication. Finally, this research investigates how different strategies during the prototyping process affects design success as the fourth and final study. Results show that a parallel prototyping strategy yields better design success, improved engineering design self-efficacy, and a broader exploration of the solution space than an iterative prototyping strategy. Taken as a whole, this work showcases different design strategies that improve the engineering design process by increasing systems understanding and facilitate the development of innovative engineering solutions.