Moving a Team-Based Freshmen Biomedical Engineering and Design Course Online

Haase, Eileen

doi:10.1007/s43683-020-00005-0

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…The course has been previously well described and its objectives are listed in Table 1. 9 However, computational methods in BME were notably missing from the first-year course. It is critical that BME students understand both the potential and limitations of using computational methods to identify and analyze health inequities.…”

Section: Challenge Statementmentioning

confidence: 99%

“…For the module, we employed a ''flipped'' classroom to best aid students in their learning, which had been previously used in other modules of this course. 9 Research has found that a flipped classroom can enhance equity among university students by allowing students time to digest content and review resources in a non-stressful environment. 1,2 Indeed, BME students learn most effectively from collaboration and teamwork with their classmates, relying on their peers to achieve success in course objectives.…”

Section: Novel Initiativementioning

confidence: 99%

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Development and Implementation of a Health Equity-Focused Python and Machine Learning Module in an Introductory BME Course

Storm

Zhang

Haase

2022

Biomed Eng Education

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Our first year biomedical engineering course exposes students to multiple engineering and design techniques within an overarching theme of understanding health inequity. Currently, the semester-long curriculum excludes computational methods such as Python programming and Machine Learning, which are usually not introduced until more advanced BME courses in the student's third and fourth year. This paper details the development and student feedback of a 2-week computational module in a team-based course focused on health inequity. Google Colaboratory was used to host the modules and provide a coding environment for students. The end-of-semester survey indicated that 53% of students (N=127) agreed they gained a basic understanding of Python and were comfortable with the programming language and that 72% of students agreed that the module helped them understand the potential of Machine Learning to aid in analyzing health data and identifying health inequities. Student feedback indicated strong interest in spending additional time on a more in-depth project. Nonetheless, we were able to provide students experience with Python programming and Machine Learning. Further, there was a statistically significant increase (34% to 88%, pvalue < 0.001) in students who ''agreed'' or ''strongly agreed'' that ''I can define and ideate solutions for issues in health inequity.'' This module enables first year students to use Python and Machine Learning to analyze health inequities and prepares them to apply computational methods in future courses. We have included links to all of the Python and Machine Learning guides, assignments, coding, and answer keys for educators to implement this module.

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Section: Challenge Statementmentioning

confidence: 99%

Section: Novel Initiativementioning

confidence: 99%

Development and Implementation of a Health Equity-Focused Python and Machine Learning Module in an Introductory BME Course

Storm

Zhang

Haase

2022

Biomed Eng Education

Self Cite

View full text Add to dashboard Cite

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“…The redesign included considering the course in the larger context of the curriculum and, in particular, the current first-year experience. Although the redesign was planned prior to the COVID-19 pandemic, additional considerations were made to transition the course to the virtual environment, especially considering that effective online teaching requires additional skills and pedagogy compared to in-person teaching [7,8].…”

Section: Introductionmentioning

confidence: 99%

Teaching the First-Year, Hands-On Engineering Design Experience Online

Simson,

Lawless,

Lee

et al.

2021 ASEE Virtual Annual Conference Content Access Proceedings

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Her research focuses on using heterogeneous catalysis in applications like emissions control and alternative energy technologies. Amanda received her Ph.D. from Columbia University's Department of Earth and Environmental Engineering. After her PhD she worked on developing hydrogen production technologies for Watt Fuel Cell in Port Washington, NY. Dr. Simson is dedicated to improving educational opportunities for students in STEM. Prior to her PhD studies she taught middle school for three years. She has developed several programs for students including a series of math competitions for NYC middle school students and a chemistry card game called Valence. Dr. Martin S. Lawless, The Cooper UnionMartin Lawless earned his Ph.D. in Acoustics in 2018 from the Pennsylvania State University where he investigated the brain's auditory and reward responses to room acoustics. At the Cooper Union, he continues studying sound perception, including 1) the generation of head-related transfer functions with machine-learning techniques, 2) musical therapeutic inventions for motor recovery after stroke, and 3) active noise control using an external microphone array.

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Interactive remote electrical safety laboratory module in biomedical engineering education

Haj-Hosseini,

Jonasson,

Stridsman

et al. 2024

Educ Inf Technol

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To enable interactive remote education on electrical safety in biomedical engineering, a real-life problem-based laboratory module is proposed, implemented and evaluated. The laboratory module was implemented in a freestanding distance course in hospital safety for three consecutive years and was based on electrical safety for medical devices, where standard equipment existing in most hospitals could be used. The course participants were from a total of 42 geographical locations in or near Sweden. To allow a high level of interaction, especially among peer students, a graphical digital platform (Gather Town) was used. The digital platform was additionally used in two group work sessions. The experience of the participants in terms of usefulness and satisfaction was rated on a range of [-2, 2] using a van der Laan 5-point Likert-based acceptance scale questionnaire. The laboratory module overall was scored 4.1/5 by the participants (n = 29) in the final course assessments. The evaluation of the digital platform alone showed that in the first usage instance, the participants (n = 21) found the platform to be useful (0.54 ± 0.67) and satisfactory (0.37 ± 0.60). The participants’ experience of the digital platform improved when comparing two identical group work assignments so that ratings of usefulness and satisfaction were 1.11 ± 0.59 and 1 ± 0.71, respectively, after they had used it in the second group work session (n = 38). This study provides an instance of an interactive remote electrical safety laboratory module that is envisioned to contribute to further implementations of sustainable education in biomedical engineering.

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Moving a Team-Based Freshmen Biomedical Engineering and Design Course Online

Cited by 4 publications

References 8 publications

Development and Implementation of a Health Equity-Focused Python and Machine Learning Module in an Introductory BME Course

Development and Implementation of a Health Equity-Focused Python and Machine Learning Module in an Introductory BME Course

Teaching the First-Year, Hands-On Engineering Design Experience Online

Interactive remote electrical safety laboratory module in biomedical engineering education

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