Work in Progress: Physiological Assessment of Learning in a Virtual Reality Clinical Immersion Environment

Christine E. King; Kit Roy Feeney; Quangminh Tang; Milan Das; Dalton Salvo

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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): Best of Works in Progress
Tagged Division: Biomedical Engineering Division (BED)
Tagged Topic: Diversity
Page Count: 14
DOI: 10.18260/1-2--44328
Permanent URL: https://peer.asee.org/44328
Download Count: 90

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Paper Authors

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Christine E. King University of California, Irvine

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Dr. Christine King is an Assistant Teaching Professor of Biomedical Engineering at UC Irvine. She received her BS and MS from Manhattan College in Mechanical Engineering and her PhD in Biomedical Engineering from UC Irvine, where she developed brain-computer interface systems for neurorehabilitation. She was a post-doctorate in the Wireless Health Institute at the University of California, Los Angeles, and a research manager in the Center for SMART Health, where she focused on wireless health monitoring for stroke and pediatric asthma. Her current research is on engineering education and women's health, specializing in pedagogy strategies to promote learning and innovation in design-build-test courses, including senior design, computer programming, and computer-aided-design courses, as well as pre-partum and partum medical devices.

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Abstract

Personalized learning is one of the 14 grand challenges for engineering in the 21st century identified by the National Academy of Engineering. Education is shifting from a one-size-fits-all approach to a personalized process in which learning is tailored to a student’s individual needs and learning abilities. In addition to the need for personalized education, the CHIPS and Science Act has listed relevant and experiential training as a strategic objective for US educational institutions. In biomedical engineering programs, this includes the need to perform clinical immersion, or learning from synergistic transactions between people and the environment within a healthcare setting. However, due to a lack of access to nearby medical centers, access for non-essential personnel enter hospitals, and increasing engineering class sizes, the ability for engineering students to shadow physicians has become difficult. To be able to allow students to perform clinical immersion without physically entering a hospital, the Department of Biomedical Engineering at the the University of California Irvine (UCI) has developed a virtual reality clinical immersion platform for student learning of unmet clinical needs and medical device design. This platform and the corresponding learning modules were piloted in Spring of 2022 as a junior-level unmet needs finding course, where students utilized the virtual reality clinical procedures to identify and screen unmet clinical needs using learning methods adopted from the Stanford BioDesign Process, and determine a proposed innovation for the problem that can be designed and validated in their senior capstone course the following year. A virtual reality platform was utilized over video recordings for the program, as prior research suggests that virtual reality for student learning can have a higher positive effect on knowledge transfer and self-efficacy than video recordings.

To assess whether knowledge transfer is occurring within the virtual reality clinical immersion platform, and further develop the efficacy of the virtual reality clinical immersion experiences, the authors are developing a phenomenological framework that has been previously utilized in other virtual reality research applications. To this end, the developed framework analyzes the attention to interactions between the users and the virtual environment they are immersed in. To test the framework, student volunteers enrolled in the Spring of 2023 offering of the unmet clinical needs finding course will complete questionnaires regarding their experience engaging with the virtual content before, during, and after taking the course alongside participating in one-on-one interviews (UCI IRB Exempt No. 904). To analyze their phenomenological responses to the virtual environments, the students will also perform the virtual reality experiences while their visual attention data is collected through eye tracking within a virtual reality headset (HP Omnicept Reverb G2). This information will be used to detect what and for how long the student is looking at in the environments. In addition, electroencephalogram (EEG) recordings (Neuroscan 19-Channel Quik-Cap, Biopac MP 160 Data Acquisition System) will be synchronized with the eye tracking information to assess whether there are neurological correlates of learning occurring within the environment using known EEG correlates of learning based on prior research findings. By comparing the physiological correlates of attention and learning against the course learning outcome assessments, such as a laboratory innovation notebook, the authors hope to be able to develop real-time interventions based on the individual user’s physiological patterns of learning to improve innovation and unmet clinical needs finding skills within virtual reality environments.

Citation
Format

King, C. E., & Feeney, K. R., & Tang, Q., & Das, M., & Salvo, D. (2023, June), Work in Progress: Physiological Assessment of Learning in a Virtual Reality Clinical Immersion Environment Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44328

TY  - CPAPER
AB  - Personalized learning is one of the 14 grand challenges for engineering in the 21st century identified by the National Academy of Engineering. Education is shifting from a one-size-fits-all approach to a personalized process in which learning is tailored to a student’s individual needs and learning abilities. In addition to the need for personalized education, the CHIPS and Science Act has listed relevant and experiential training as a strategic objective for US educational institutions. In biomedical engineering programs, this includes the need to perform clinical immersion, or learning from synergistic transactions between people and the environment within a healthcare setting. However, due to a lack of access to nearby medical centers, access for non-essential personnel enter hospitals, and increasing engineering class sizes, the ability for engineering students to shadow physicians has become difficult. To be able to allow students to perform clinical immersion without physically entering a hospital, the Department of Biomedical Engineering at the the University of California Irvine (UCI) has developed a virtual reality clinical immersion platform for student learning of unmet clinical needs and medical device design. This platform and the corresponding learning modules were piloted in Spring of 2022 as a junior-level unmet needs finding course, where students utilized the virtual reality clinical procedures to identify and screen unmet clinical needs using learning methods adopted from the Stanford BioDesign Process, and determine a proposed innovation for the problem that can be designed and validated in their senior capstone course the following year. A virtual reality platform was utilized over video recordings for the program, as prior research suggests that virtual reality for student learning can have a higher positive effect on knowledge transfer and self-efficacy than video recordings.


To assess whether knowledge transfer is occurring within the virtual reality clinical immersion platform, and further develop the efficacy of the virtual reality clinical immersion experiences, the authors are developing a phenomenological framework that has been previously utilized in other virtual reality research applications. To this end, the developed framework analyzes the attention to interactions between the users and the virtual environment they are immersed in. To test the framework, student volunteers enrolled in the Spring of 2023 offering of the unmet clinical needs finding course will complete questionnaires regarding their experience engaging with the virtual content before, during, and after taking the course alongside participating in one-on-one interviews (UCI IRB Exempt No. 904). To analyze their phenomenological responses to the virtual environments, the students will also perform the virtual reality experiences while their visual attention data is collected through eye tracking within a virtual reality headset (HP Omnicept Reverb G2). This information will be used to detect what and for how long the student is looking at in the environments. In addition, electroencephalogram (EEG) recordings (Neuroscan 19-Channel Quik-Cap, Biopac MP 160 Data Acquisition System) will be synchronized with the eye tracking information to assess whether there are neurological correlates of learning occurring within the environment using known EEG correlates of learning based on prior research findings. By comparing the physiological correlates of attention and learning against the course learning outcome assessments, such as a laboratory innovation notebook, the authors hope to be able to develop real-time interventions based on the individual user’s physiological patterns of learning to improve innovation and unmet clinical needs finding skills within virtual reality environments.

AU  - Christine E. King
AU  - Kit Roy Feeney
AU  - Quangminh Tang
AU  - Milan Das
AU  - Dalton Salvo
CY  - Baltimore , Maryland
DA  - 2023/06/25
PB  - ASEE Conferences
TI  - Work in Progress: Physiological Assessment of Learning in a Virtual Reality Clinical Immersion Environment
UR  - https://peer.asee.org/44328
DO  - 10.18260/1-2--44328
ER  -