Work in Progress:  Supplementing theoretical modeling with empirical data for improved design

Jennifer Bailey; Spencer Randolph Davis

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Conference: 2023 ASEE Annual Conference & Exposition
Location: Baltimore , Maryland
Publication Date: June 25, 2023
Start Date: June 25, 2023
End Date: June 28, 2023
Conference Session: First-Year Programs Division (FYP) - WIPS 1: Programs & Curricula
Tagged Division: First-Year Programs Division (FYP)
Page Count: 9
DOI: 10.18260/1-2--44135
Permanent URL: https://strategy.asee.org/44135
Download Count: 77

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Paper Authors

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Jennifer Bailey Rochester Institute of Technology (COE)

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Dr. Jennifer Bailey is a Principal Lecturer of Biomedical Engineering at Rochester Institute of Technology, where she has taught since January of 2014. She previously taught at the University of Illinois and the University of Southern Indiana after graduation. Her interests include first year design experiences, enhancing spatial reasoning skills, and creating a student-centered learning environment.

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Spencer Randolph Davis

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Abstract

This work in progress will describe the motivation, development, preliminary implementation, preliminary results, and planned full implementation and expected results of augmenting a theoretical modeling activity with empirical data as part of a semester long design project in a first year course.

The Biomedical Engineering curriculum begins with a one-credit Introduction to Biomedical Engineering course which is the only core engineering course during the students’ first semester. Since 2017 the course has focused on a semester long design project. Due to changes in constraints as a result of the pandemic, starting in 2020 the project has focused on theoretical modeling to aide in the design of a portable air filtration prototype instead of relying heavily on empirical data gathered in lab settings as in previous offerings. However, while the use of theoretical modeling has great learning outcomes, the students have been mentally overwhelmed by the activity and incapable of effectively applying the learned concepts into practice toward the design of their prototype. The goal is to fill the gap between learning and applying knowledge by providing experiences to help students understand and practice how to reconcile theoretical models with empirical data. The expected outcome is improvement of their final prototype due to use of theoretical modeling in the design process.

Theoretical modeling is new to many students including the skills of 1) extrapolating information from manufacturer’s websites to produce a graph, 2) producing the graph using tools such as Excel, 3) using the graph to determine the dependent variable from an independent variable, and 4) translating this information into an application used to make decisions in the design process. Being able to collect empirical data will support the learning process, specifically points 3 and 4, with a hands-on demonstration of the theoretical information. This experiential addition will also give physical meaning to the theoretical values in the graph and help the students who learn concepts better when connected to a physical experience instead of as mathematical representations.

This specific theoretical modeling activity is intended to help teams choose fans and filters for their filtration systems. A demonstration chamber was designed to allow for various filters to be tested at various fan speeds in order to confirm concepts from the theoretical modeling activity. Pressure and velocity are measured to validate relationships introduced by the theory and how varying fan speed or filter arrangement impacts these measurements. Assembly of the chamber took too long in the fall of 2022 so full implementation was not completed at this time. Preliminary evaluation of the demonstration chamber to compliment the theoretical fan and filter subsystem modeling activity will be gathered by the end of the fall 2022 semester.

For two offerings, the course has used theoretical models for students to learn the skill of how to make specific, data-driven design decisions. The next step has been for students to apply the concepts and relationships in order to size fan and filter subsystems for their project. Full implementation of the demonstration chamber is planned for the fall of 2023 when the collection of empirical data can be done concurrently to theoretical modeling. The final expectation is for this to result in better educated design decisions and more effective prototypes as students bridge the gap between learning and applying by using both empirical data and theoretical modeling.

Citation
Format

Bailey, J., & Davis, S. R. (2023, June), Work in Progress: Supplementing theoretical modeling with empirical data for improved design Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44135

TY  - CPAPER
AB  - This work in progress will describe the motivation, development, preliminary implementation, preliminary results, and planned full implementation and expected results of augmenting a theoretical modeling activity with empirical data as part of a semester long design project in a first year course.

The Biomedical Engineering curriculum begins with a one-credit Introduction to Biomedical Engineering course which is the only core engineering course during the students’ first semester. Since 2017 the course has focused on a semester long design project. Due to changes in constraints as a result of the pandemic, starting in 2020 the project has focused on theoretical modeling to aide in the design of a portable air filtration prototype instead of relying heavily on empirical data gathered in lab settings as in previous offerings. However, while the use of theoretical modeling has great learning outcomes, the students have been mentally overwhelmed by the activity and incapable of effectively applying the learned concepts into practice toward the design of their prototype. The goal is to fill the gap between learning and applying knowledge by providing experiences to help students understand and practice how to reconcile theoretical models with empirical data. The expected outcome is improvement of their final prototype due to use of theoretical modeling in the design process.

Theoretical modeling is new to many students including the skills of 1) extrapolating information from manufacturer’s websites to produce a graph, 2) producing the graph using tools such as Excel, 3) using the graph to determine the dependent variable from an independent variable, and 4) translating this information into an application used to make decisions in the design process. Being able to collect empirical data will support the learning process, specifically points 3 and 4, with a hands-on demonstration of the theoretical information. This experiential addition will also give physical meaning to the theoretical values in the graph and help the students who learn concepts better when connected to a physical experience instead of as mathematical representations.

This specific theoretical modeling activity is intended to help teams choose fans and filters for their filtration systems. A demonstration chamber was designed to allow for various filters to be tested at various fan speeds in order to confirm concepts from the theoretical modeling activity. Pressure and velocity are measured to validate relationships introduced by the theory and how varying fan speed or filter arrangement impacts these measurements. Assembly of the chamber took too long in the fall of 2022 so full implementation was not completed at this time. Preliminary evaluation of the demonstration chamber to compliment the theoretical fan and filter subsystem modeling activity will be gathered by the end of the fall 2022 semester.

For two offerings, the course has used theoretical models for students to learn the skill of how to make specific, data-driven design decisions. The next step has been for students to apply the concepts and relationships in order to size fan and filter subsystems for their project. Full implementation of the demonstration chamber is planned for the fall of 2023 when the collection of empirical data can be done concurrently to theoretical modeling. The final expectation is for this to result in better educated design decisions and more effective prototypes as students bridge the gap between learning and applying by using both empirical data and theoretical modeling.
AU  - Jennifer Bailey
AU  - Spencer Randolph Davis
CY  - Baltimore , Maryland
DA  - 2023/06/25
PB  - ASEE Conferences
TI  - Work in Progress:  Supplementing theoretical modeling with empirical data for improved design
UR  - https://strategy.asee.org/44135
DO  - 10.18260/1-2--44135
ER  -