Preparing Undergraduates to Work at the Intersection of Biology and Mathematics

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  • Thank the organizers (names)\n\n
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  • END: an intersection of coincidences led a group of mathematical science faculty to reach out to biology faculty as a source of expertise in UR\n\nfeeding that interest: articles in professional society publications, Bio2010, and finally an NSF solicitation\n
  • END: an intersection of coincidences led a group of mathematical science faculty to reach out to biology faculty as a source of expertise in UR\n\nfeeding that interest: articles in professional society publications, Bio2010, and finally an NSF solicitation\n
  • END: an intersection of coincidences led a group of mathematical science faculty to reach out to biology faculty as a source of expertise in UR\n\nfeeding that interest: articles in professional society publications, Bio2010, and finally an NSF solicitation\n
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  • Spring of 2003\n\nI had been working with a colleague in Biology...\nBegan noticing calls going out in the professional societies...\n\nFloated the idea of a mathbio seminar...\n
  • Spring of 2003\n\nI had been working with a colleague in Biology...\nBegan noticing calls going out in the professional societies...\n\nFloated the idea of a mathbio seminar...\n
  • Spring of 2003\n\nI had been working with a colleague in Biology...\nBegan noticing calls going out in the professional societies...\n\nFloated the idea of a mathbio seminar...\n
  • Spring of 2003\n\nI had been working with a colleague in Biology...\nBegan noticing calls going out in the professional societies...\n\nFloated the idea of a mathbio seminar...\n
  • Spring of 2003\n\nI had been working with a colleague in Biology...\nBegan noticing calls going out in the professional societies...\n\nFloated the idea of a mathbio seminar...\n
  • Spring of 2003\n\nI had been working with a colleague in Biology...\nBegan noticing calls going out in the professional societies...\n\nFloated the idea of a mathbio seminar...\n
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  • Goal: to create infrastructure for a self-sustaining, research-based undergrad training program in mathematical biology\n+ elevate faculty scholarship \n
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  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
  • Overlaps of interest and project needs get students working togeth informally and spontenously. coding, phylogenies, statistical tests, LaTeX or some other software environment, Matlab\n\nThe wide variety of faculty and research projects led us to adopt a program management strategy that was hands-off in many ways; we communicated the program goals and expectations repeatedly, to the community and the teams, but beyond that we did little to mandate how faculty managed their teams.\nWe knew that meeting frequently was important. We knew that communication would be challenging, so we encouraged them to maintain line of communication and put more effort into that than they might think nece\n\nstudents identify with the community; get to know many faculty members from both departments\n
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  • Through interdisciplinary experiences, bring mathematics majors to the point where they are capable of interacting with (collaborating with) professionals in the life sciences\n\nLikewise for biology majors.\n
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  • Preparing Undergraduates to Work at the Intersection of Biology and Mathematics

    1. 1. Preparing Undergraduates to Work at the Intersection of Biology and Mathematics Jason Miller, Ph.D. - Department of Mathematics Timothy Walston, Ph.D. - Department of Biology Truman State University Available on http://www.slideshare.net/millerj870/ AAC&U 2012
    2. 2. Outline• Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    3. 3. The Institution AAC&U 2012
    4. 4. TrumanTruman is in rural Kirksville, Missouri AAC&U 2012
    5. 5. Truman AAC&U 2012
    6. 6. About Truman AAC&U 2012
    7. 7. About Truman• Missouri’s only “highly selective” public liberal arts University; pride in high-quality teaching, small class size AAC&U 2012
    8. 8. 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 AAC&U 2012
    9. 9. 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 AAC&U 2012
    10. 10. 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 AAC&U 2012
    11. 11. About Truman AAC&U 2012
    12. 12. About Truman• about 25 biology faculty, 35 mathematics faculty (math+stats+CS) AAC&U 2012
    13. 13. About Truman• about 25 biology faculty, 35 mathematics faculty (math+stats+CS)• biology: research expected of faculty (with students); experienced mentors AAC&U 2012
    14. 14. 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 AAC&U 2012
    15. 15. 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 2012
    16. 16. Photo by w4nd3rl0st (InspiredinDesMoines) - http://flic.kr/p/aPw9Xe AAC&U 2012
    17. 17. pre-2003 Biology Math (Silos not to scale) Photo by keeva999 - http://flic.kr/p/bXchED AAC&U 2012
    18. 18. • Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    19. 19. The Genesis AAC&U 2012
    20. 20. Professional Societies AAC&U 2012
    21. 21. Professional Societies AAC&U 2012
    22. 22. Professional Societies AAC&U 2012
    23. 23. Professional Societies AAC&U 2012
    24. 24. Professional Societies AAC&U 2012
    25. 25. Professional Societies AAC&U 2012
    26. 26. Professional Societies AAC&U 2012
    27. 27. 2003 AAC&U 2012
    28. 28. 2003 AAC&U 2012
    29. 29. 2007 AAC&U 2012
    30. 30. R E P OR T T O T H E PR E SI DEN TENGAGE TO E XCEL: PRODUCI NG ONE M ILLION A DDI T IONA L COLLEGE GR A DUAT ES W I T H DEGR EES I N SCIENCE , T ECH NOLOGY, ENGI NEER I NG, A N D M AT HEM AT ICS Executive Office of the President President’s Council of Advisors on Science and Technology F E BRUA RY 2 01 2 AAC&U 2012
    31. 31. • Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    32. 32. The Program AAC&U 2012
    33. 33. Miller, Walston. Interdisciplinary Training in MathematicalBiology Through Team-based Undergraduate Research andCourses. CBE Life Sci Educ. 2010 Fall;9(3):284-9. AAC&U 2012
    34. 34. AAC&U 2012
    35. 35. Mathematical Biology Seminar (since 2003) AAC&U 2012
    36. 36. Mathematical Biology Seminar (since 2003)• Program fulcrum AAC&U 2012
    37. 37. Mathematical Biology Seminar (since 2003)• Program fulcrum• Biweekly meeting of faculty and undergraduates AAC&U 2012
    38. 38. Mathematical Biology Seminar (since 2003)• Program fulcrum• Biweekly meeting of faculty and undergraduates• Initially, a “Biology Fashion Show” AAC&U 2012
    39. 39. 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 AAC&U 2012
    40. 40. 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 AAC&U 2012
    41. 41. AAC&U 2012
    42. 42. Life Scientist (faculty) AAC&U 2012
    43. 43. Mathematical Life Scientist Scientist (faculty) (faculty) AAC&U 2012
    44. 44. Mathematical Life Scientist Scientist (faculty) (faculty)Mathematical Life Scientist Scientist (trainee) (trainee) AAC&U 2012
    45. 45. Mathematical Life Scientist Scientist (faculty) (faculty)Mathematical Life Scientist Scientist (trainee) (trainee) AAC&U 2012
    46. 46. Mathematical Life Scientist Scientist (faculty) (faculty)Mathematical Life Scientist Scientist (trainee) (trainee) AAC&U 2012
    47. 47. AAC&U 2012
    48. 48. Mathematical Life Scientist Scientist (faculty) (faculty)Mathematical Life Scientist Scientist (trainee) (trainee) AAC&U 2012
    49. 49. Mathematical Mathematical Life Scientist Life Scientist Scientist Scientist (faculty) (faculty) (faculty) (faculty)Mathematical Mathematical Life Scientist Life Scientist Scientist Scientist (trainee) (trainee) (trainee) (trainee)Mathematical Mathematical Life Scientist Life Scientist Scientist Scientist (faculty) (faculty) (faculty) (faculty)Mathematical Mathematical Life Scientist Life Scientist Scientist Scientist (trainee) (trainee) (trainee) (trainee) AAC&U 2012
    50. 50. AAC&U 2012
    51. 51. • selection occurs in the Fall, students start work in January (year-long) AAC&U 2012
    52. 52. • selection occurs in the Fall, students start work in January (year-long)• weekly meetings during the academic year AAC&U 2012
    53. 53. • selection occurs in the Fall, students start work in January (year-long)• weekly meetings during the academic year• Intense 10-week summer research program AAC&U 2012
    54. 54. Summer Community AAC&U 2012
    55. 55. Summer Community AAC&U 2012
    56. 56. Summer Community AAC&U 2012
    57. 57. Summer Community AAC&U 2012
    58. 58. Summer Community AAC&U 2012
    59. 59. Summer Community AAC&U 2012
    60. 60. Summer Community AAC&U 2012
    61. 61. Summer AAC&U 2012
    62. 62. Summer Residence Hall Meals Small Group Meetings + Mentors Weekly Discussions/Workshops Social Events MathBio Seminar AAC&U 2012
    63. 63. Summer Residence Hall Meals Small Group Meetings + Mentors Weekly Discussions/Workshops Social Events MathBio Seminar AAC&U 2012
    64. 64. Automatic Annotation of Maize Genome Collaboration between Truman, IA State, Cornell, Cold Spring Harbor. AAC&U 2012
    65. 65. Automatic Annotation of Maize Genome Collaboration between Truman, IA State, Cornell, Cold Spring Harbor. AAC&U 2012
    66. 66. Geometric Modeling of C.elegan’s 4-cell stage AAC&U 2012
    67. 67. Graph Theoretic Modeling of Vascular Networks Collaboration between Truman and AT Still University of Health Sciences. AAC&U 2012
    68. 68. Modeling Dispersion of Extinct Saccate Pollen Collaboration between Truman and the College of New Jersey. AAC&U 2012
    69. 69. Identifying Volant Bats via Echolocation with Lynn Robbins, MSU Biology AAC&U 2012
    70. 70. Habitat Suitability modeling for the Missouri Bladderpod Collaboration between Truman and the US Fish and Wildlife Service. AAC&U 2012
    71. 71. Statistical Modeling of Abundance of Beetle Populations AAC&U 2012
    72. 72. Models of Tick Respiration and Physiology AAC&U 2012
    73. 73. • Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    74. 74. The Outcomes AAC&U 2012
    75. 75. 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 AAC&U 2012
    76. 76. UBM AccomplishmentsFrom more than one ‘mathphobic’ biologyfaculty member, research mentor: “This program has changed the way I think about doing research.” AAC&U 2012
    77. 77. UBM AccomplishmentsFrom more than one ‘mathphobic’ biologyfaculty member, research mentor: “This program has changed the way I think about doing research.”If it’s changing the way they think in the lab,then it’s changing the way they talk withstudents about mathematics AAC&U 2012
    78. 78. “We are not trying to turn mathematicsmajors into biology majors, nor are wetrying to turn biology majors intomathematics majors.Rather, we are trying to bring both togetherat the intersection of the life andmathematical sciences to train them to workacross disciplinary boundaries.” AAC&U 2012
    79. 79. “We are not trying to turn mathematicsmajors into biology majors, nor are wetrying to turn biology majors intomathematics majors.Rather, we are trying to bring both togetherat the intersection of the life andmathematical sciences to train them to workacross disciplinary boundaries.” We work to bridge an epistemological gap between the mathematical and life sciences. AAC&U 2012
    80. 80. AAC&U 2012
    81. 81. 2003 AAC&U 2012
    82. 82. 2003 2005 AAC&U 2012
    83. 83. 2003 2005 2010 AAC&U 2012
    84. 84. AAC&U 2012
    85. 85. AAC&U 2012
    86. 86. UBM Program AAC&U 2012
    87. 87. UBM Program• a small group of faculty from math, CS, and biology leveraged Truman strengths and Hopper’s Law of Retroaction: AAC&U 2012
    88. 88. 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.” AAC&U 2012
    89. 89. 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 AAC&U 2012
    90. 90. 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. AAC&U 2012
    91. 91. • Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    92. 92. The Minor AAC&U 2012
    93. 93. 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 AAC&U 2012
    94. 94. Competency-based Minor AAC&U 2012
    95. 95. Competency-based Minor AAC&U 2012
    96. 96. Data Competency-based Minor ModelingComputational StatisticsInterdisciplinary Research AAC&U 2012
    97. 97. Data Competency-based Minor ModelingComputational • Demonstrate proficiencies in each category (though research, courses) StatisticsInterdisciplinary Research AAC&U 2012
    98. 98. Data Competency-based Minor ModelingComputational • Demonstrate proficiencies in each category (though research, courses) Statistics • Earn 15+ credits doing so (must take Intro to MathBio course)Interdisciplinary Research AAC&U 2012
    99. 99. Data Competency-based Minor ModelingComputational • Demonstrate proficiencies in each category (though research, courses) Statistics • Earn 15+ credits doing so (must take Intro to MathBio course)Interdisciplinary • Attend MathBio Seminar Research AAC&U 2012
    100. 100. Data Competency-based Minor Modeling • competencies straddle disciplinary boundariesComputational • create learning plan • use experiences (incl. courses) to Statistics show competencies • faculty oversight committeeInterdisciplinary approves plan, notifies Registrar Research when completed AAC&U 2012
    101. 101. Other Courses• Any that makes a connection between the areas. Some example: • Math Modeling • Developmental • Ecology Biology • ODEs • (Electron) Microscopy • Genetics of • Plant/Animal Animal and Plant Improvement Breeding AAC&U 2012
    102. 102. • Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    103. 103. The Broader Vision AAC&U 2012
    104. 104. AAC&U 2012
    105. 105. AAC&U 2012
    106. 106. AAC&U 2012
    107. 107. AAC&U 2012
    108. 108. AAC&U 2012
    109. 109. AAC&U 2012
    110. 110. AAC&U 2012
    111. 111. AAC&U 2012
    112. 112. ‘Convergent’ teamwork is going to be a definingcharacteristic of 21st century science andmathematics. AAC&U 2012
    113. 113. ‘Convergent’ teamwork is going to be a definingcharacteristic of 21st century science andmathematics. It can’t be taught through a series of lectures. AAC&U 2012
    114. 114. ‘Convergent’ teamwork is going to be a definingcharacteristic of 21st century science andmathematics. It can’t be taught through a series of lectures. It can’t be taught from a textbook or by reading a journal paper. AAC&U 2012
    115. 115. ‘Convergent’ teamwork is going to be a definingcharacteristic of 21st century science andmathematics. 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. AAC&U 2012
    116. 116. ‘Convergent’ teamwork is going to be a definingcharacteristic of 21st century science andmathematics. 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 andprepare them to learn to be ‘convergent’ AAC&U 2012
    117. 117. ‘Convergence’ can be taught... AAC&U 2012
    118. 118. ‘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’ AAC&U 2012
    119. 119. ‘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
    120. 120. ‘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
    121. 121. ‘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 AAC&U 2012
    122. 122. ‘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
    123. 123. ‘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 AAC&U 2012
    124. 124. ‘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 AAC&U 2012
    125. 125. • Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    126. 126. The Challenges AAC&U 2012
    127. 127. AAC&U 2012
    128. 128. AAC&U 2012
    129. 129. 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 AAC&U 2012
    130. 130. Funding Reality1998 2015 From Tuition From State How to sustain a program in this environment? AAC&U 2012
    131. 131. Funding Reality• 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) AAC&U 2012
    132. 132. 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 AAC&U 2012
    133. 133. • Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    134. 134. The Lessons AAC&U 2012
    135. 135. 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 AAC&U 2012
    136. 136. Lessons Learned AAC&U 2012
    137. 137. Lessons Learned AAC&U 2012
    138. 138. Lessons Learned AAC&U 2012
    139. 139. • Institution• Genesis, Program, Outcomes• Minor• Broader Vision• Challenges• Lessons AAC&U 2012
    140. 140. AAC&U 2012
    141. 141. millerj@truman.eduThis material is based upon work supported by the National Science Foundation under NSFUBM #0337769, #0436348, and #0926737. Any opinions, findings, and conclusions orrecommendations expressed in this material are those of the author(s) and do not necessarilyreflect the views of the National Science Foundation. AAC&U 2012

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