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Validation of a Mental Model Elicitation Instrument through Deployment of Control Groups in an Undergraduate Engineering Program

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Conference

2020 ASEE Virtual Annual Conference Content Access

Location

Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

Design Methodologies 1

Tagged Division

Design in Engineering Education

Tagged Topic

Diversity

Page Count

16

DOI

10.18260/1-2--35481

Permanent URL

https://peer.asee.org/35481

Download Count

145

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Paper Authors

biography

Alexander R. Murphy Georgia Institute of Technology

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Alexander R. Murphy is a graduate student at the Georgia Institute of Technology and is pursuing a Ph.D. in mechanical engineering. He was born and raised in Tampa Florida, where he received a B.S. in mechanical engineering with a minor in creative writing from the University of South Florida. He is proud to have received a NSF GRFP fellowship this past spring of 2018. Currently, he is interested in exploring students' and professionals' mental models and how they change during the design process. Specifically, he is investigating the connections between functional decomposition, systems thinking, and mental model representation. His research interests also include investigation into prototyping strategies for engineering design. After completing his graduate degree, Alexander wants to become academic faculty and start a small business as a design consultant.

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Henry David Banks James Madison University

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Henry Banks is an undergraduate engineering student at James Madison University. He has been conducting design research as an undergraduate research assistant since 2017 and is currently working towards his honors thesis.

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Matt Robert Bohm Florida Polytechnic University Orcid 16x16 orcid.org/0000-0002-9598-633X

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Matt Bohm is an Associate Professor of Mechanical Engineering at Florida Polytechnic University (Florida Poly). He joined the University in 2016 after spending 6-years as an Assistant Professor of Mechanical Engineering at the University of Louisville (UofL). Bohm’s research examines the intersection of 3 distinct areas, engineering design, engineering education, and big data. Currently, Bohm has an active NSF grant under the Division of Undergraduate Education to examine the effects of systems modeling paradigms with respect to design outcomes and systems thinking and understanding. While at UofL, Bohm was primarily responsible for overseeing the Mechanical Engineering Department’s capstone design program. Prior to his position at UofL, Bohm was a visiting researcher at Oregon State University (OSU) after completing his PhD at the Missouri University of Science and Technology (S&T) in 2009. While at S&T, Bohm was also a Lecturer for the Department of Interdisciplinary Engineering and was responsible for coordinating and teaching design and mechanics related courses.

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Robert L. Nagel James Madison University

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Dr. Robert Nagel is an Associate Professor in the Department of Engineering at James Madison University. Dr. Nagel joined James Madison University after completing his Ph.D. in mechanical engineering at Oregon State University. Nagel teaches and performs research related to engineering design. Specifically, through research, Nagel explores how design interventions commonly used to teach design influence student learning.

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Julie S. Linsey Georgia Institute of Technology

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Dr. Julie S. Linsey is an Associate Professor in the George W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technological. Dr. Linsey received her Ph.D. in Mechanical Engineering at The University of Texas. Her research area is design cognition including systematic methods and tools for innovative design with a particular focus on concept generation and design-by-analogy. Her research seeks to understand designers’ cognitive processes with the goal of creating better tools and approaches to enhance engineering design. She has authored over 150 technical publications including over forty journal papers, and ten book chapters.

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Abstract

Mental models of engineering systems contain information about the components, connections, inputs/outputs, and function of a system. It is difficult to study mental models because any mental model elicitation method inherently only provides a representation of the mental model and not a realization of the mental model itself. In order to measure engineering students’ systems understanding, a mental model instrument with accompanying scoring rubrics have been developed and deployed in undergraduate and graduate engineering classrooms in previous work. The research presented in this paper explores validation of this mental model elicitation approach through two control groups involving the collection of pre- and post- mental model data without intervention, whereas previous research included a functional modeling intervention. Results from the control groups are discussed and compared to previous results that had an intervention to show whether or not learning effects take place. In addition, this work considers the addition of an explanatory example showing exactly how to complete the given tasks, where one control group is given the example and the other is not. Results show whether or not the example should be provided in future deployments of the mental model instrument and provides insight into how an included example might have affected past results and how it could affect future results. This work serves as a first step towards validation of this new mental model elicitation method, is in contribution to ongoing research on mental models of engineering systems, and will inform future research that utilizes this approach. As we continue to explore how students learn about engineering, it is important that educators and researchers have a way to reliably measure student understanding of various engineering systems while they complete their undergraduate and graduate degree programs.

Murphy, A. R., & Banks, H. D., & Bohm, M. R., & Nagel, R. L., & Linsey, J. S. (2020, June), Validation of a Mental Model Elicitation Instrument through Deployment of Control Groups in an Undergraduate Engineering Program Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35481

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