impact of team and advisor demographics and formulation on the success of biomedical engineering...
Post on 16-Dec-2015
219 Views
Preview:
TRANSCRIPT
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, 2011Academic Symposium for the Inauguration of Teresa A. Sullivan
Coursework Innovation: Reflective Teaching and Continuous Improvement
Major Senior Design Experience
Required by ABET for BME undergraduate programsU.Va.: Team-based, yearlong Capstone design course
TeamsIndividual 4(+) membersSelf-selected
Advisors1 3(+) advisors/teamFaculty, clinicians, and industrial advisors
School of Engineering and Applied
Science
School of Medicine
School of Nursing
College of Arts and Sciences
Industry
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
Team sizeGenderGPA
Advisors
NumberDegreesAffiliationExperience
Grant Applied
Provisional Patent
ConferenceGrant
ReceivedAward
PaperPublished
0
0.5
1
1.5
2
2.5
3
Analysis of Yearly Successes
Success Distributions
Y1 Y4Y2 Y3 Y5
Grant Applied
Provisional Patent
Conference
Grant Received
AwardPaper
Published
Y1 Y4Y2 Y3 Y5
*
n=24
n=39
n=44
n=28
n=33
Student # 35 48 6574 61 Student’s t-test; avg. + SEM; *p = 0.03To
tal #
of
Su
ccesses
per
Team
0
1
2
3
4
5
6
Advisor Selection:
Number of Advisors Degrees
Tota
l #
of
Su
ccesses
per
Team
n = 114
n = 48 n = 7
Number of Advisors per Team
1 2 3 (+)
**
Student’s t-test; avg. + SEM; *p < 0.005
0
0.5
1
1.5
2
2.5
3
n = 114
n = 26 n = 29
IndividualUniform degrees
Mixed degrees
*
Student’s t-test; avg. + SEM; *p < 0.05
Advisor Degrees per Team
0
0.5
1
1.5
2
2.5
3
Tota
l #
of
Su
ccesses
per
Team
Advisor Affiliation
BME ENGR Clinician
Researcher
Nursing Arts/Sci Industry Combo
n = 70 n = 14 n = 9 n = 11 n = 3 n = 1 n = 18 n = 41
* * **
Student’s t-test; avg. + SEM; *p < 0.03
Advisor Selection: Advisor AffiliationSchool of
Engineering and
Applied Science
School of Medicine
School of Nursing
College of Arts and Sciences
Industry
BME ENGR Clinician Researcher
Tota
l #
of
Su
ccesses
per
Team
Advisor AffiliationStudent’s t-test; avg. + SEM; *p < 0.03; †p = 0.001
Advisor Selection: Advisor AffiliationSchool of
Engineering and
Applied Science
School of Medicine
School of Nursing
College of Arts and Sciences
Industry
BME ENGR Clinician Researcher
0
0.5
1
1.5
2
2.5
3
3.5
4*
**
BME ENGR ClinicianResearcherNursing Arts/Sci Industry BME/Industry
BME/Researche
r
BME/Clinician
†
n=5
n=6
n=13
Team Formulation:
Number of Student Team Members
0
0.5
1
1.5
2
2.5
3
3.5
4
Tota
l #
of
Su
ccesses
per
Team
n = 98
n = 40
n = 8n = 23
Number of Student Members per Team
1 2 4 (+)
Student’s t-test; avg. + SEM; *p ≤ 0.05
*
3
*
Team Formulation:
Gender
0
0.5
1
1.5
2
2.5
3
Tota
l #
of
Su
ccesses
per
Team
Gender of Student Team Members
M F M/F
n = 21
n = 23
n = 27
Team Formulation:
GPA: 3rd year Cumulative; classified as high or low (relative to average GPA of BME students of that year)
0
0.5
1
1.5
2
2.5
3
Tota
l #
of
Su
ccesses
per
Team
GPA of Student Team Members
High
Low Mixed High
Low
Teams of 2(+) Individuals
*
n=16 n=18 n=36 n=63 n=35
Student’s t-test; avg. + SEM; *p = 0.04
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 ENGR Clinician 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
Future Work Other factors (previous lab experience, career goals)Analysis of individual success metricsAdditional metrics
Student preference surveys
Grant Applied
Provisional Patent
ConferenceGrant
ReceivedAward
PaperPublished
???
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Team Formulation:Feedback from Undergraduate Students Re: Number of Student Team Members
5 = strongly agree, 1 = strongly disagree; avg. + SEM
Ou
r G
rou
p S
ize
Was
Ap
pro
pri
ate
1 2 3 4(+)
Number of Student Members per Team
n=10 n=18 n=15 n=4
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Team Formulation:Feedback from Undergraduate Students Regarding Work Load Distribution
2 3 4 (+)
Number of Student Members per Team
5 = strongly agree, 1 = strongly disagree; avg. + SEM
I D
id M
ore
Wo
rk T
han
th
e O
ther
M
emb
ers
of
My
Team
n=16 n=14 n=4
top related