Board 24: Work in Progress: Teaching Cardiovascular Physiology with Computational Modeling - Insight from a New, Team-Taught Course in Biomedical Engineering

Mitchel Jonathan Colebank; Naomi Chesler

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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: Biomedical Engineering Division (BED) Poster Session
Tagged Division: Biomedical Engineering Division (BED)
Page Count: 4
DOI: 10.18260/1-2--42682
Permanent URL: https://strategy.asee.org/42682
Download Count: 101

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Paper Authors

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Mitchel Jonathan Colebank University of California, Irvine

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Dr. Colebank is a postdoctoral fellow in the Biomedical Engineering department at the University of California, Irvine. He is a member of Naomi Chesler's lab as part of the Edwards Lifesciences Foundation Cardiovascular Innovation and Research Center (CIRC). He received his undergraduate degree in Mathematical Sciences from Clemson University and his Ph.D. in Biomathematics from North Carolina State University. Dr. Colebank's research thrusts are in computational biology, cardiovascular function, and multiscale physiological phenomena.

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Naomi Chesler

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Abstract

Student exposure to computational modeling and simulation varies with biomedical engineering (BME) departments and institutions. Though computational science can be an entire thrust within BME research, it is also an effective educational tool for students to explore principles of core BME courses. Other engineering disciplines such as electrical or mechanical engineering regularly use computation and programming in the classroom. BME departments use these tools in varied capacities, yet most BME subdisciplines require either an understanding of quantitative relationships derived from theory or an ability to interpret and analyze quantitative data. The key biological mechanisms in cardiovascular physiology (e.g., the Frank-Starling mechanisms or Poiseuille flow) are not intuitive but can be better understood in the classroom using computational modeling and simulation. Hence, we developed an elective BME course on cardiovascular physiology that combines standard lecture-style theory presentations with computational, in-silico experiments.

The course has been offered to undergraduate and graduate students in the spring and fall 2022 quarters and is team-taught between a tenured professor and postdoctoral researcher. The class concepts follow a textbook designed for graduate and medical students that briefly summarizes key principles of cardiovascular physiology, including sarcomere function, pressure-volume loop analysis, and pulse-wave propagation. Classes were held twice a week and were split into theory lectures and in-person coding sessions. Student progress and understanding was assessed by weekly online reading quizzes and computational homework problems. Reading content was complemented by lecture style classes. In-class coding sessions provided an active learning framework for exploring topics using mathematical models developed in MATLAB. A final assessment at the end of the quarter included a review of a journal article related to cardiovascular physiology and either (a) replication of article results using computational modeling or (b) innovation on article results using the models covered in class.

The use of in-class coding and active learning style sessions not only exposed students to in-silico modeling, but also provided an “input-output” approach to understanding how physiological changes can affect measured outputs or cardiovascular indices. Our study will report anonymous pre- and post-reflections from students on the class content, their assessment on the use of in-class coding, and overall opinions of class structure. We will report which concepts were most difficult to understand from either theoretical or computational perspectives as expressed by student surveys. In summary, this work-in-progress study will provide insight into how in-silico, mechanistic computer models can promote student understanding of complex cardiovascular principles.

Citation
Format

Colebank, M. J., & Chesler, N. (2023, June), Board 24: Work in Progress: Teaching Cardiovascular Physiology with Computational Modeling - Insight from a New, Team-Taught Course in Biomedical Engineering Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--42682

TY  - CPAPER
AB  - Student exposure to computational modeling and simulation varies with biomedical engineering (BME) departments and institutions. Though computational science can be an entire thrust within BME research, it is also an effective educational tool for students to explore principles of core BME courses. Other engineering disciplines such as electrical or mechanical engineering regularly use computation and programming in the classroom. BME departments use these tools in varied capacities, yet most BME subdisciplines require either an understanding of quantitative relationships derived from theory or an ability to interpret and analyze quantitative data. The key biological mechanisms in cardiovascular physiology (e.g., the Frank-Starling mechanisms or Poiseuille flow) are not intuitive but can be better understood in the classroom using computational modeling and simulation. Hence, we developed an elective BME course on cardiovascular physiology that combines standard lecture-style theory presentations with computational, in-silico experiments. 

The course has been offered to undergraduate and graduate students in the spring and fall 2022 quarters and is team-taught between a tenured professor and postdoctoral researcher. The class concepts follow a textbook designed for graduate and medical students that briefly summarizes key principles of cardiovascular physiology, including sarcomere function, pressure-volume loop analysis, and pulse-wave propagation. Classes were held twice a week and were split into theory lectures and in-person coding sessions. Student progress and understanding was assessed by weekly online reading quizzes and computational homework problems. Reading content was complemented by lecture style classes. In-class coding sessions provided an active learning framework for exploring topics using mathematical models developed in MATLAB. A final assessment at the end of the quarter included a review of a journal article related to cardiovascular physiology and either (a) replication of article results using computational modeling or (b) innovation on article results using the models covered in class. 

The use of in-class coding and active learning style sessions not only exposed students to in-silico modeling, but also provided an “input-output” approach to understanding how physiological changes can affect measured outputs or cardiovascular indices. Our study will report anonymous pre- and post-reflections from students on the class content, their assessment on the use of in-class coding, and overall opinions of class structure. We will report which concepts were most difficult to understand from either theoretical or computational perspectives as expressed by student surveys. In summary, this work-in-progress study will provide insight into how in-silico, mechanistic computer models can promote student understanding of complex cardiovascular principles.

AU  - Mitchel Jonathan Colebank
AU  - Naomi Chesler
CY  - Baltimore , Maryland
DA  - 2023/06/25
PB  - ASEE Conferences
TI  - Board 24: Work in Progress: Teaching Cardiovascular Physiology with Computational Modeling - Insight from a New, Team-Taught Course in Biomedical Engineering
UR  - https://strategy.asee.org/42682
DO  - 10.18260/1-2--42682
ER  -