preparing undergraduates to work at the intersection of biology and mathematics
TRANSCRIPT
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Preparing Undergraduates to Work at the Intersection of Biology and Mathematics
Jason Miller, Ph.D. - Department of MathematicsTimothy Walston, Ph.D. - Department of Biology
Truman State University
Available on http://www.slideshare.net/millerj870/
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Outline• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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The Institution
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Truman
Truman is in rural Kirksville, Missouri
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Truman
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About Truman
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About Truman• Missouri’s only “highly selective” public
liberal arts University; pride in high-quality teaching, small class size
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About Truman• Missouri’s only “highly selective” public
liberal arts University; pride in high-quality teaching, small class size
• ~6000 undergraduates, ~300 faculty, 150 Masters students
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About Truman• Missouri’s only “highly selective” public
liberal arts University; pride in high-quality teaching, small class size
• ~6000 undergraduates, ~300 faculty, 150 Masters students
• Institutional commitment to Undergraduate Research and to Interdisciplinary teaching
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About Truman• Missouri’s only “highly selective” public
liberal arts University; pride in high-quality teaching, small class size
• ~6000 undergraduates, ~300 faculty, 150 Masters students
• Institutional commitment to Undergraduate Research and to Interdisciplinary teaching
• EX: all students must take a Junior Interdisciplinary Seminar
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About Truman
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About Truman
• about 25 biology faculty, 35 mathematics faculty (math+stats+CS)
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About Truman
• about 25 biology faculty, 35 mathematics faculty (math+stats+CS)
• biology: research expected of faculty (with students); experienced mentors
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About Truman
• about 25 biology faculty, 35 mathematics faculty (math+stats+CS)
• biology: research expected of faculty (with students); experienced mentors
• mathematics: teaching focus, little or no support for research activity; 10 new faculty between 1998-2000
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Other Truman Factoids
• T&P research expectation varies between departments
• Biology: medium• Math & CS: low
• No formalized definition for faculty workload beyond ‘credit load’ or ‘contact hours’
AAC&U 2012Photo by w4nd3rl0st (InspiredinDesMoines) - http://flic.kr/p/aPw9Xe
AAC&U 2012Photo by keeva999 - http://flic.kr/p/bXchED
pre-2003
Biol
ogy
Mat
h
(Silos not to scale)
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• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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The Genesis
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Professional Societies
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Professional Societies
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Professional Societies
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Professional Societies
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Professional Societies
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Professional Societies
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Professional Societies
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2003
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2003
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2007
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F E B R UA R Y 2 0 1 2
Executive O!ce of the PresidentPresident’s Council of Advisors
on Science and Technology
R EPORT TO THE PR ESIDENTENGAGE TO EXCEL: PRODUCING ONE MILLION
ADDITIONAL COLLEGE GR ADUATES W ITH DEGREES IN SCIENCE, TECHNOLOGY, ENGINEER ING, AND MATHEMATICS
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• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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The Program
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Miller, Walston. Interdisciplinary Training in Mathematical Biology Through Team-based Undergraduate Research and Courses. CBE Life Sci Educ. 2010 Fall;9(3):284-9.
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Mathematical Biology Seminar (since 2003)
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Mathematical Biology Seminar (since 2003)
• Program fulcrum
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Mathematical Biology Seminar (since 2003)
• Program fulcrum
• Biweekly meeting of faculty and undergraduates
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Mathematical Biology Seminar (since 2003)
• Program fulcrum
• Biweekly meeting of faculty and undergraduates
• Initially, a “Biology Fashion Show”
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Mathematical Biology Seminar (since 2003)
• Program fulcrum
• Biweekly meeting of faculty and undergraduates
• Initially, a “Biology Fashion Show”
• Engineered several cross-disciplinary, research hook-ups
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Mathematical Biology Seminar (since 2003)
• Program fulcrum
• Biweekly meeting of faculty and undergraduates
• Initially, a “Biology Fashion Show”
• Engineered several cross-disciplinary, research hook-ups
• Pairings provided us with a foundation for NSF UBM grant proposals
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Life Scientist (faculty)
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Mathematical Scientist (faculty)
Life Scientist (faculty)
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Mathematical Scientist (faculty)
Life Scientist (faculty)
Life Scientist (trainee)
Mathematical Scientist (trainee)
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Mathematical Scientist (faculty)
Life Scientist (faculty)
Life Scientist (trainee)
Mathematical Scientist (trainee)
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Mathematical Scientist (faculty)
Life Scientist (faculty)
Life Scientist (trainee)
Mathematical Scientist (trainee)
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Mathematical Scientist (faculty)
Life Scientist (faculty)
Life Scientist (trainee)
Mathematical Scientist (trainee)
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Mathematical Scientist (faculty)
Life Scientist (faculty)
Life Scientist (trainee)
Mathematical Scientist (trainee)
Mathematical Scientist (faculty)
Life Scientist (faculty)
Life Scientist (trainee)
Mathematical Scientist (trainee)
Mathematical Scientist (faculty)
Life Scientist (faculty)
Life Scientist (trainee)
Mathematical Scientist (trainee)
Mathematical Scientist (faculty)
Life Scientist (faculty)
Life Scientist (trainee)
Mathematical Scientist (trainee)
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• selection occurs in the Fall, students start work in January (year-long)
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• selection occurs in the Fall, students start work in January (year-long)
• weekly meetings during the academic year
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• selection occurs in the Fall, students start work in January (year-long)
• weekly meetings during the academic year
• Intense 10-week summer research program
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Community
Summer
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Community
Summer
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Community
Summer
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Community
Summer
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Community
Summer
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Community
Summer
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Community
Summer
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Summer
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Residence Hall
Small Group Meetings + MentorsWeekly Discussions/Workshops
Meals
Social EventsMathBio Seminar
Summer
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Residence Hall
Small Group Meetings + MentorsWeekly Discussions/Workshops
Meals
Social EventsMathBio Seminar
Summer
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Automatic Annotation of Maize Genome
Collaboration between Truman, IA State, Cornell, Cold Spring Harbor.
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Automatic Annotation of Maize Genome
Collaboration between Truman, IA State, Cornell, Cold Spring Harbor.
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Geometric Modeling of C.elegan’s 4-cell stage
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Graph Theoretic Modeling of Vascular Networks
Collaboration between Truman and AT Still University of Health Sciences.
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Modeling Dispersion of Extinct Saccate Pollen
Collaboration between Truman and the College of New Jersey.
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Identifying Volant Bats via Echolocation
with Lynn Robbins, MSU Biology
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Habitat Suitability modeling for the Missouri Bladderpod
Collaboration between Truman and the US Fish and Wildlife Service.
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Statistical Modeling of Abundance of Beetle Populations
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Models of Tick Respiration and Physiology
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• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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The Outcomes
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UBM Accomplishments• about 60 student participants
• 20+ faculty participants
• 80%+ students to graduate school
• 10%+ students to industry
• 20 papers in peer-reviewed scientific journals
• scores of presentations at regional, national, and international meetings
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UBM Accomplishments
“This program has changed the way I think about doing research.”
From more than one ‘mathphobic’ biology faculty member, research mentor:
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UBM Accomplishments
“This program has changed the way I think about doing research.”
From more than one ‘mathphobic’ biology faculty member, research mentor:
If it’s changing the way they think in the lab, then it’s changing the way they talk with students about mathematics
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“We are not trying to turn mathematics majors into biology majors, nor are we trying to turn biology majors into mathematics majors.
Rather, we are trying to bring both together at the intersection of the life and mathematical sciences to train them to work across disciplinary boundaries.”
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“We are not trying to turn mathematics majors into biology majors, nor are we trying to turn biology majors into mathematics majors.
Rather, we are trying to bring both together at the intersection of the life and mathematical sciences to train them to work across disciplinary boundaries.”
We work to bridge an epistemological gap between the mathematical and life sciences.
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2003
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2003 2005
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2003 2005
2010
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UBM Program
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UBM Program
• a small group of faculty from math, CS, and biology leveraged Truman strengths and Hopper’s Law of Retroaction:
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UBM Program
• a small group of faculty from math, CS, and biology leveraged Truman strengths and Hopper’s Law of Retroaction:
“It is easier to seek forgiveness than permission.”
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UBM Program
• a small group of faculty from math, CS, and biology leveraged Truman strengths and Hopper’s Law of Retroaction:
“It is easier to seek forgiveness than permission.”
• NSF UBM grants in 2003, 2004, and 2009
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UBM Program
• a small group of faculty from math, CS, and biology leveraged Truman strengths and Hopper’s Law of Retroaction:
“It is easier to seek forgiveness than permission.”
• NSF UBM grants in 2003, 2004, and 2009
• Established research-focused interdisciplinary training program in mathbio.
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• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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The Minor
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We Wanted More...• impact a bigger group of students
• institutionalize the changes in culture, activity
• courses
• Bioinformatics• Introduction to Mathematical Biology• Biostatistics/Biometry• Introduction to Computational Science*• (new, 2012) Calculus & Mathematical Methods for
the Life Sciences
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Competency-based Minor
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Competency-based Minor
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Data
Modeling
Computational
Statistics
Interdisciplinary Research
Competency-based Minor
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Data
Modeling
Computational
Statistics
Interdisciplinary Research
Competency-based Minor
• Demonstrate proficiencies in each category (though research, courses)
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Data
Modeling
Computational
Statistics
Interdisciplinary Research
Competency-based Minor
• Demonstrate proficiencies in each category (though research, courses)
• Earn 15+ credits doing so (must take Intro to MathBio course)
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Data
Modeling
Computational
Statistics
Interdisciplinary Research
Competency-based Minor
• Demonstrate proficiencies in each category (though research, courses)
• Earn 15+ credits doing so (must take Intro to MathBio course)
• Attend MathBio Seminar
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Data
Modeling
Computational
Statistics
Interdisciplinary Research
Competency-based Minor
• competencies straddle disciplinary boundaries
• create learning plan
• use experiences (incl. courses) to show competencies
• faculty oversight committee approves plan, notifies Registrar when completed
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Other Courses
• Math Modeling
• Ecology
• ODEs
• Genetics of Animal and Plant Improvement
• Developmental Biology
• (Electron) Microscopy
• Plant/Animal Breeding
• Any that makes a connection between the areas. Some example:
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• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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The Broader Vision
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‘Convergent’ teamwork is going to be a defining characteristic of 21st century science and mathematics.
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‘Convergent’ teamwork is going to be a defining characteristic of 21st century science and mathematics.
It can’t be taught through a series of lectures.
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‘Convergent’ teamwork is going to be a defining characteristic of 21st century science and mathematics.
It can’t be taught through a series of lectures.
It can’t be taught from a textbook or by reading a journal paper.
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‘Convergent’ teamwork is going to be a defining characteristic of 21st century science and mathematics.
It can’t be taught through a series of lectures.
It can’t be taught from a textbook or by reading a journal paper.
It can’t be taught in a course for a (single) major.
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‘Convergent’ teamwork is going to be a defining characteristic of 21st century science and mathematics.
It can’t be taught through a series of lectures.
It can’t be taught from a textbook or by reading a journal paper.
It can’t be taught in a course for a (single) major.
The above activities can motivate students and prepare them to learn to be ‘convergent’
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‘Convergence’ can be taught...
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‘Convergence’ can be taught...• Our experience provides strong evidence that
proper hands-on undergraduate research (or research-like) projects can train undergraduates to be ‘convergent’
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‘Convergence’ can be taught...• Our experience provides strong evidence that
proper hands-on undergraduate research (or research-like) projects can train undergraduates to be ‘convergent’
• Essential characteristics:
AAC&U 2012
‘Convergence’ can be taught...• Our experience provides strong evidence that
proper hands-on undergraduate research (or research-like) projects can train undergraduates to be ‘convergent’
• Essential characteristics:
• it’s a real research project to the mentors
AAC&U 2012
‘Convergence’ can be taught...• Our experience provides strong evidence that
proper hands-on undergraduate research (or research-like) projects can train undergraduates to be ‘convergent’
• Essential characteristics:
• it’s a real research project to the mentors
• mentors from different disciplines
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‘Convergence’ can be taught...• Our experience provides strong evidence that
proper hands-on undergraduate research (or research-like) projects can train undergraduates to be ‘convergent’
• Essential characteristics:
• it’s a real research project to the mentors
• mentors from different disciplines
• undergraduates from different disciplines
AAC&U 2012
‘Convergence’ can be taught...• Our experience provides strong evidence that
proper hands-on undergraduate research (or research-like) projects can train undergraduates to be ‘convergent’
• Essential characteristics:
• it’s a real research project to the mentors
• mentors from different disciplines
• undergraduates from different disciplines
• long-term immersion
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‘Convergence’ can be taught...• Our experience provides strong evidence that
proper hands-on undergraduate research (or research-like) projects can train undergraduates to be ‘convergent’
• Essential characteristics:
• it’s a real research project to the mentors
• mentors from different disciplines
• undergraduates from different disciplines
• long-term immersion
• students have sense of significant ownership
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• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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The Challenges
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Our program is costly• research program: • ≈$40k per team• time and effort to recruit• not easily sustainable
• minor: faculty time • oversight• recruiting, mentoring students
• courses• departmental zero-sum, silo mentality• team-teaching is seen as frivolous
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Funding Reality
1998 2015
From Tuition From State
How to sustain a program in this environment?
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• Show program’s cost-benefit leans toward ‘benefit’ (e.g., credit generation, revenue)
• Show your program’s outcomes align with University’s strategic plan
• Track student successes (e.g., subsequence grades, post-graduation experiences) and share
• Cultivate faculty buy-in (individual, group, departmental, and school)
Funding Reality
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Program Dashboard
• Applications to the summer research program are low
• Enrollment in interdisciplinary courses and minor is low-ish
• Our Intro to MathBio course was not team-taught last semester
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• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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The Lessons
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Lessons Learned• Starting a new interdepartmental program
requires guts and a theme that you (or your team) can carry
• Sustaining a interdepartmental program requires strong leadership and administrative champion(s)
• Grant money opens a door, but membership requires faculty buy-in
• This model for bringing disciplines together could work for any pair of disciplines
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Lessons Learned
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Lessons Learned
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Lessons Learned
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• Institution
• Genesis, Program, Outcomes
• Minor
• Broader Vision
• Challenges
• Lessons
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This material is based upon work supported by the National Science Foundation under NSF UBM #0337769, #0436348, and #0926737. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.