Senior Honors Projects, 2010-2019

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Date of Graduation


Document Type


Degree Name

Bachelor of Science (BS)


Department of Engineering


Robert L. Nagel

Justin Henriques

Julie Linsey


The ability to understand complexity and think holistically about systems is an increasingly important part of engineering design. This is embodied in the concept of systems thinking, a concept studied primarily in the fields of systems dynamics and systems engineering. Systems thinking ability is built off mental models, a loosely-defined construct people form to make predictions about their surroundings. Methods to evaluate systems thinking and underlying mental models rely primarily on self-evaluative methods such as questionnaires, or detailed simulations of systems or processes; however these methods fail to directly capture students’ design tendencies. This work presents a visual instrument used to elicit and evaluate students’ mental models of two simple systems, a hair dryer and a car radiator. This instrument is used to evaluate the changes in students’ mental models after learning functional modeling, a systems abstraction method utilized in several engineering disciplines including engineering design. Two phases of analysis are presented. In the first phase of analysis, it is established that students had a significantly better understanding of the hair dryer than the car radiator system, based on the number of critical components students included in their responses; in this first phase, a component-based scoring strategy is presented. The second phase of analysis presents a scoring method based on Module Heuristics, a method for decomposing and categorizing flows and groups of functions within a functional model of a system. Module Heuristics are used to show the analogous functional flows between the hair dryer and car radiator. The scoring method is then used to investigate changes in students’ mental models resulting from learning functional modeling.



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