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Katelyn Mason*, Alyssa Taylor, Ph.D., Timothy E. Allen, Ph.D.*, Shayn Peirce-Cottler, Ph.D*.

Impact of Team and Advisor Demographics and Formulation on the Success of Biomedical Engineering Senior Design Projects. Katelyn Mason*, Alyssa Taylor, Ph.D., Timothy E. Allen, Ph.D.*, Shayn Peirce-Cottler, Ph.D*. U.Va. Dept. of Biomedical Engineering April 14, 2011

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Katelyn Mason*, Alyssa Taylor, Ph.D., Timothy E. Allen, Ph.D.*, Shayn Peirce-Cottler, Ph.D*.

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  1. Impact of Team and Advisor Demographics and Formulation on the Success of Biomedical Engineering Senior Design Projects Katelyn Mason*, Alyssa Taylor, Ph.D., Timothy E. Allen, Ph.D.*, Shayn Peirce-Cottler, Ph.D*. U.Va. Dept. of Biomedical Engineering April 14, 2011 Academic Symposium for the Inauguration of Teresa A. Sullivan Coursework Innovation: Reflective Teaching and Continuous Improvement

  2. Teams Advisors • Individual  4(+) members • Self-selected • 1  3(+) advisors/team • Faculty, clinicians, and industrial advisors Major Senior Design Experience • Required by ABET for BME undergraduate programs • U.Va.: Team-based, yearlong Capstone design course School of Engineering and Applied Science School of Medicine School of Nursing College of Arts and Sciences Industry

  3. Impact of Team and Advisor Demographics and Formulation on the Success of Capstone Projects • Motivation: What makes a successful Capstone team? • Aspects considered: • Success Metrics: Teams Advisors • Team size • Gender • GPA • Number • Degrees • Affiliation • Experience Grant Applied Grant Received Conference Paper Published Provisional Patent Award

  4. * n=24 n=28 n=39 n=44 n=33 35 48 74 65 61 Student # Y1 Y2 Y3 Y4 Y5 Grant Applied Conference Provisional Patent Grant Received Paper Published Award Y1 Y2 Y3 Y4 Y5 Analysis of Yearly Successes • Success Distributions Total # of Successes per Team Student’s t-test; avg. + SEM; *p = 0.03

  5. Advisor Selection: • Number of Advisors • Degrees * * * Total # of Successes per Team n = 114 n = 26 n = 29 n = 114 n = 48 n = 7 Uniform degrees Mixed degrees 1 2 3 (+) Individual Number of Advisors per Team Advisor Degrees per Team Student’s t-test; avg. + SEM; *p < 0.005 Student’s t-test; avg. + SEM; *p < 0.05

  6. * Advisor Selection: Advisor Affiliation School of Engineering and Applied Science School of Medicine School of Nursing College of Arts and Sciences Industry BME Clinician ENGR Researcher 3 * * * 2.5 2 Total # of Successes per Team 1.5 1 0.5 n = 70 n = 14 n = 9 n = 11 n = 3 n = 1 n = 18 n = 41 0 Nursing ENGR Arts/Sci Researcher Clinician BME Industry Combo Advisor Affiliation Student’s t-test; avg. + SEM; *p < 0.03

  7. 4 * 3.5 3 * 2.5 2 1.5 1 0.5 0 Advisor Selection: Advisor Affiliation School of Engineering and Applied Science School of Medicine School of Nursing College of Arts and Sciences Industry BME Clinician ENGR Researcher * † Total # of Successes per Team n= 5 n= 6 n= 13 BME ENGR Clinician Researcher Nursing Arts/Sci Industry BME/ Industry BME/ Researcher BME/ Clinician Advisor Affiliation Student’s t-test; avg. + SEM; *p < 0.03; †p = 0.001

  8. Team Formulation: • Number of Student Team Members * * Total # of Successes per Team n = 98 n = 40 n = 23 n = 8 1 2 3 4 (+) Number of Student Members per Team Student’s t-test; avg. + SEM; *p≤ 0.05

  9. Team Formulation: • Gender Total # of Successes per Team n = 21 n = 23 n = 27 M F M/F Gender of Student Team Members

  10. Team Formulation: • GPA: 3rd year Cumulative; classified as high or low (relative to average GPA of BME students of that year) 3 * 2.5 2 Total # of Successes per Team 1.5 1 n=16 n=18 n=36 n=63 n=35 0.5 0 High Low Mixed High Low Teams of 2(+) Individuals GPA of Student Team Members Student’s t-test; avg. + SEM; *p= 0.04

  11. Conclusions • Recommendations for Advisors: • 3(+) advisors/team • Mixed degrees • Interdisciplinary – mixed affiliations School of Engineering and Applied Science School of Medicine School of Nursing College of Arts and Sciences Industry BME Clinician ENGR Researcher • Recommendations for Students: • 3(+) students/team • M/F teams • Student with below avg. GPA  individual or w/mixed team • 2.8 GPA minimum for students wanting to work alone

  12. Future Work • Other factors (previous lab experience, career goals) • Analysis of individual success metrics • Additional metrics • Student preference surveys Grant Applied Grant Received Conference Paper Published Provisional Patent Award ???

  13. Team Formulation: • Feedback from Undergraduate Students Re: Number of Student Team Members Our Group Size Was Appropriate n=10 n=18 n=15 n=4 1 2 3 4(+) Number of Student Members per Team 5 = strongly agree, 1 = strongly disagree; avg. + SEM

  14. Team Formulation: • Feedback from Undergraduate Students Regarding Work Load Distribution I Did More Work Than the Other Members of My Team n=16 n=14 n=4 2 3 4 (+) Number of Student Members per Team 5 = strongly agree, 1 = strongly disagree; avg. + SEM

  15. Acknowledgments Kitter Bishop (BME, U.Va.) Katie Degen (BME, U.Va.)

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