Highs and Lows of An Interdepartmental MathBio Program

701 views

Published on

This talk describes the interdisciplinary undergraduate mathematical biology program at Truman State University, its history and development, and the minor degree it offers.

Published in: Education, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
701
On SlideShare
0
From Embeds
0
Number of Embeds
4
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • Thank the organizers (names)\n\n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • Through interdisciplinary experiences, bring mathematics majors to the point where they are capable of interacting with (collaborating with) professionals in the life sciences\n\n \n \nLikewise for biology majors.\n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • \n \n
  • Highs and Lows of An Interdepartmental MathBio Program

    1. 1. Highs and Lows of theInterdepartmental MathBio Program Jason Miller, Ph.D. Department of Mathematics SMB 2012
    2. 2. Outline SMB 2012
    3. 3. Outline• Truman’s Program (Development and Current State) SMB 2012
    4. 4. Outline• Truman’s Program (Development and Current State)• Successes SMB 2012
    5. 5. Outline• Truman’s Program (Development and Current State)• Successes• Failures ... Challenges SMB 2012
    6. 6. Outline• Truman’s Program (Development and Current State)• Successes• Failures ... Challenges• Lessons Learned & Conversation SMB 2012
    7. 7. Truman is...• ... public liberal arts & sciences• ... medium sized (≈6000 students, 320 faculty)• ... geographically isolated, rural• ... highly selective (ave. ACT of first-year student≥27)• ... lean, affordability Mission SMB 2012
    8. 8. Other Truman Factoids• T&P Scholarly expectation varies between departments • Biology: medium • Math & CS: (very) low• No formalized definition for faculty workload beyond ‘credit load’ or ‘contact hours’• Deep commitment to undergraduate research SMB 2012
    9. 9. Photo by w4nd3rl0st (InspiredinDesMoines) - http://flic.kr/p/aPw9Xe SMB 2012
    10. 10. Mathematical Biology Program SMB 2012
    11. 11. pre-2003 Biology Math (Silos not to scale) Photo by keeva999 - http://flic.kr/p/bXchED SMB 2012
    12. 12. SMB 2012
    13. 13. 2003 SMB 2012
    14. 14. 2003 2005 SMB 2012
    15. 15. 2003 2005 2010 SMB 2012
    16. 16. SMB 2012
    17. 17. SMB 2012
    18. 18. UBM Program SMB 2012
    19. 19. UBM Program• a small group of faculty from math, CS, and biology leveraged Truman strengths and Hopper’s Law of Retroaction: SMB 2012
    20. 20. 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.” SMB 2012
    21. 21. 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 SMB 2012
    22. 22. 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. SMB 2012
    23. 23. Research-focus SMB 2012
    24. 24. Research-focus• Multidisciplinary teams • two students, two faculty • students (resp. faculty) from each discipline SMB 2012
    25. 25. Research-focus• Multidisciplinary teams • two students, two faculty • students (resp. faculty) from each discipline• focus on a question arising from biologist’s lab, research programme SMB 2012
    26. 26. Research-focus• Multidisciplinary teams • two students, two faculty • students (resp. faculty) from each discipline• focus on a question arising from biologist’s lab, research programme• start 1 Jan to prepare & plan; execute during residential & coordinated Summer; complete arc in Fall, end by 31 Dec. SMB 2012
    27. 27. 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 SMB 2012
    28. 28. UBM AccomplishmentsFrom more than one ‘mathphobic’ biologyfaculty member, research mentor: “This program has changed the way I think about doing research.” SMB 2012
    29. 29. 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 SMB 2012
    30. 30. “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.” SMB 2012
    31. 31. “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. SMB 2012
    32. 32. SMB 2012
    33. 33. SMB 2012
    34. 34. SMB 2012
    35. 35. SMB 2012
    36. 36. SMB 2012
    37. 37. SMB 2012
    38. 38. SMB 2012
    39. 39. SMB 2012
    40. 40. ‘Convergent’ teamwork is going to be a definingcharacteristic of 21st century science andmathematics. SMB 2012
    41. 41. ‘Convergent’ teamwork is going to be a definingcharacteristic of 21st century science andmathematics. It can’t be taught through a series of lectures. SMB 2012
    42. 42. ‘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. SMB 2012
    43. 43. ‘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. SMB 2012
    44. 44. ‘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’ SMB 2012
    45. 45. ‘Convergence’ can be taught... SMB 2012
    46. 46. ‘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’ SMB 2012
    47. 47. ‘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: SMB 2012
    48. 48. ‘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 SMB 2012
    49. 49. ‘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 SMB 2012
    50. 50. ‘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 SMB 2012
    51. 51. ‘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 SMB 2012
    52. 52. ‘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 SMB 2012
    53. 53. 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 SMB 2012
    54. 54. Competency-based Minor SMB 2012
    55. 55. Competency-based Minor SMB 2012
    56. 56. Data Competency-based Minor ModelingComputational StatisticsInterdisciplinary Research SMB 2012
    57. 57. Data Competency-based Minor ModelingComputational • Demonstrate proficiencies in each category (though research, courses) StatisticsInterdisciplinary Research SMB 2012
    58. 58. 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 SMB 2012
    59. 59. 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 SMB 2012
    60. 60. 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 SMB 2012
    61. 61. 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 SMB 2012
    62. 62. Nota Bene• The 15+ credit minor only adds 2-ish courses to a student’s major• At conferences... “I wish we could do that...”• Getting it through governance... [ovation] SMB 2012
    63. 63. Challenges SMB 2012
    64. 64. SMB 2012
    65. 65. SMB 2012
    66. 66. SMB 2012
    67. 67. SMB 2012
    68. 68. 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 SMB 2012
    69. 69. Funding Reality1998 2015 From Tuition From State How to sustain a program in this environment? SMB 2012
    70. 70. Funding Reality• Show program’s cost-benefit lean ‘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) SMB 2012
    71. 71. Minor Production• MathBio Minor: competency based (requires planning, paperwork, and approval)• Cognitive Science Minor: course-based SMB 2012
    72. 72. Minor Production Cognitive Science MathBio543210 2009 2010 2011 2012 SMB 2012
    73. 73. Minor Production Cognitive Science MathBio Env Studies12 9 6 3 0 2009 2010 2011 2012 SMB 2012
    74. 74. Minor Production Cognitive Science MathBio Mathematics201612 8 4 0 2009 2010 2011 2012 SMB 2012
    75. 75. Minor Production Cognitive Science MathBio Mathematics Biology100 80 60 40 20 0 2009 2010 2011 2012 SMB 2012
    76. 76. Minor Production Cognitive Science MathBio543210 2009 2010 2011 2012 SMB 2012
    77. 77. Minor Production Cognitive Science MathBio543210 2009 2010 2011 2012 ‘Cost’ of the minor exceed ‘benefit’. SMB 2012
    78. 78. Program Dashboard• Applications to the summer research program are low• Enrollment in interdisciplinary courses is low-ish• Our Intro to MathBio course was not team- taught last semester SMB 2012
    79. 79. 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• Bringing math & bio together prepares you to bring other disciplines into the game SMB 2012
    80. 80. Lessons Learned SMB 2012
    81. 81. Lessons Learned SMB 2012
    82. 82. Lessons Learned SMB 2012
    83. 83. http://www.vonnegutgroup.net SMB 2012
    84. 84. Funding Opportunities• The UBM program has been archived• Alternative pathways: • STEM Talent Expansion Program (STEP) in DUE • rumor: Experiences in Education (NSF- wide) • rumor: ‘why-der’ (phonetic) in DUE• NIH mechanisms (???) JMM New Orleans 9 January 2011
    85. 85. SMB 2012
    86. 86. 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. SMB 2012

    ×