> 7 ڽbjbjUU "7|7|l\\\8D "$ #"إT8h\40 #Jd#The tape-recorded telephone interview should take about a half hour. It will focus on the factors driving your collaboration with a mathematician (biologist), the background and skills you each bring, and the issues you encounter as a result of your different disciplinary orientations. I will also ask for your perspectives on the kind of preparation future researchers in your area will need and the implications this has for undergraduate education in biology (or math).
You are free to ask questions about any question I ask you, and you are under no obligation to answer any question asked of you. You are free to end the interview at any time.
All of your remarks will be kept confidential. In order to protect your privacy, your tape will be labeled with a code number and destroyed after it has been transcribed. Your name will never appear on the transcript. Any information that could identify you, your department, or anyone else will be altered in, or deleted from, the transcript. Any information that could be reconstructed to identify you or your department will be similarly altered or deleted.
Do you agree to be interviewed? If you agree to answer the questions, it means that you have read the information in Dr. Katkins initial communication and have had read to you by me what participation in the study entails and you would like to be a volunteer in this research study. You have also given your consent in a previous communication.
I: Can you tell me a little bit about the courses you teach that involve some collaboration or are at the intersection of biology and mathematics?
R: Certainly. There were two separate NSF funded projects. The first one focused on what the undergraduate curriculum might look like for undergraduates who are in some area of the life sciences, but the focus was on what the quantitative components of what the undergraduate life science curriculum should look like. And that led to the development of an entry-level Mathematics for the Life Sciences course that has been taught here for a little bit over ten years; it's been modified slightly from the initial versions; but it focuses on including real-world biological examples in the entry-level math course. It completely revises the common approach, which is a year-long calculus sequence, to now have essentially, a full semester, half-year of discrete mathematics followed by a relatively quick calculus that gets up to differential equations within one semester; and it includes the use of a variety of computational methodologies, meaning, in our case, different computer programs linked with biological examples and data. It also includes student lab reports and focuses on sort of a hypothesis formulation and testing approach to both the biological examples as well as mathematical examples. So that's one component.
I: Is it taught by one teacher or is it team taught, or?
R: This is a course that actually is maintained within the mathematics department. The majority of the sections have 20 to 30 students in them, has been taught over the last decade by a mixture of math-biology faculty. In this case, these are people, such as myself, which have a joint appointment in mathematics and biology, by instructors who are full-time instructors in the math department and by graduate students who are full-time graduate students in that department; and by graduate students in biology.
I: So, I mean, if I were an undergraduate and I was registered for this course, would I see just one teacher during the duration of the course, or would I see several teachers in and out of the room during the course?
R: It depends on the semester. This semester, for example I am teaching it as a lecture recitation sort of course, in which they will see me as a lecturer and then two graduate students. So they will see at least two different people. Most of the time it has been taught, it has been with a single instructor, though, for each section. And that instructor could have been a math faculty member; could have been a math instructor, meaning they're not a full-time tenure track faculty member; could have been a graduate student in math or biology; or it could have been a biology faculty. So it all depends on what hat you want the different people to play at one time. Now, that is the entry-level Math for the Life Sciences course. It is now the required sequence for biology undergraduates here, or they can take the yearlong science in engineering mathematics calculus course for science and engineering students. And, you know, about half of them take each, something like that. And, we encourage those with strong quantitative skills to take the calculus course that is designed for engineering students; that mainly has physical chemistry and engineering students in it, in part, because those courses lead naturally into the more advanced math courses and we dont want to constrain people. So, that is one project. Would you like me to tell you about the second one?
I: Okay, yes, absolutely.
R: So the second project was a follow-up to this, which came about because we realized that this was only one piece of the puzzle. The second piece of the puzzle was that students would continue to view mathematics as a subject somewhat isolated from biology, unless it was really incorporated within the biology courses that the students took. And, so we developed a second project, which was focused around incorporating additional quantitative methods within the General Biology sequence here. This was done in collaboration with myself and about three faculty members teaching General Biology on a regular basis. There are several components. We developed a set of about 50 modules that are all at high-school level mathematics that are designed to sort of piece-in to different parts of the General Biology course. We actually have two separate ones here, one that is focused on ecology and evolution, and the second one that is focused more on cell and molecular biology. So weve included modules for both of those, and this was, again, depending upon which faculty member is teaching the course, they utilize these in a variety of ways. Some people utilize them as, they basically include them as small pieces in lectures, but, I should mention, these are large lecture courses. They can have anywhere from 200 to 500 students with separate labs. So, they could incorporate these in lectures, they could use them as take-home assignments, they could use them as extra-credit assignments. They are all structured around the same format as having an underlining biological question, followed by a description of why that question is important, followed by a description of a mathematical approach, which usually means some set of equations to describe what the variables and how to measure those variables, followed by a data set that might be tabular or might be graphical, or might be both; followed by some analysis, meaning some understanding of what you understood from doing the mathematics that you did not understand before, followed by some references and additional questions. The additional questions are usually relatively brief, three or four questions that students can answer in a written format; if they would like they can use this either as an assignment, or as extra credit. These are, therefore, used in a variety of different ways by different instructors; we leave it up to them. And it varies from semester to semester, instructor to instructor. We also developed for the lab for that General Biology course an addendum to the lab manual that focuses on quantitative methods, particularly statistical ones for the lab.
I: I think we touched on this a little bit, but can you tell me how your courses got started? You know where did the idea originate, and whom did the idea come from?
R: So, lets start with the Mathematics for the Life Sciences course. There have been Mathematics for the Life Sciences courses hanging around the U.S. institutions since the early 70s or so. There was a spate of books produced in the early 70s that focused around these. Most of those courses have died out in the vast majority of institutions, in part, because, there are a number of reasons for that. One reason would be that the people who developed them moved on, retired, whatever, and are no longer available to teach it. A second one was it that the calculus reform movement came along and focused the interest in revising entry-level courses on taking modeling approaches and calculus and rethinking the calculus, moving away from sort of specific computation-oriented areas. The last decade or so, there has been a lot more push toward the realization that there are not enough quantitative approaches included in the undergraduate biology curriculum, and the rethinking of that curriculum was certainly in order. We have been teaching a Math for the Life Sciences course since before I came to UT, this was in 1979, and I realized by the late 80s that it was not doing what it needed to do. It was essentially a quickie calculus. I thought that were many, many other areas of mathematics that were used on a regular basis, and our students needed to have some exposure to them. That led to the NSF proposal that led to a set of workshops that led to the course founding. That is the Math for the Life Sciences sequence entry-level course. But we also have had, I did not mention this before, we had a regular follow up to that; that is a modeling in biology course that's taken by students who are generally more advanced, when they're juniors or seniors and sometimes taken by graduate students. The objective there is to get people more up to the research level in the sense that these projects and these applications for mathematics are somewhat more at an advanced level than we would do in an entry-level course. And a lot of this is on a conceptual basis, or using a variety of computer programs and software, so it is not heavily analytical, the way a math-biology course would be taught. I know a number of math-biology courses that we offer at the graduate level, but not at the undergraduate level. So that talks about them, sort of, the formal math components of this. The biology components of this varies because I initially submitted an NSF proposal that talked about looking throughout the entire biology curriculum and how to incorporate quantitative approaches throughout the curriculum in biology, and basically NSF cut the proposal back and we focused on General Biology. And, again, that was because there was consensus at some of these workshops that if we were going to do this, the majority of the focus should be right at the beginning. And that's what General Biology does, focuses right at the beginning of the undergraduate enterprise. Did I answer the question?
I: I think so. Can you tell me a little bit about the process of developing the courses?
R: Sure. So, both cases we actually had NSF funded workshops. The first one of these brought together a mixture of people who were mostly mathematicians, by training, but who are working in mathematical biology; across a lot of different areas of biology; not just my focused area, which is ecology, and a smattering of more data-oriented biologists, to discuss what they felt the limitations of the undergraduate quantitative curriculum for the student has been, and what would be an ideal curriculum. That workshop was held in 1982, I take it back, that was a decade earlier; 1992 and that led to a set of recommendations. Those recommendations guided this first project to rethink and redo the undergraduate math course, that's the entry-level course for life science students. That sort of guided that. It also suggested a follow-up workshop that incorporated more biologists. That was held in 1994 and recommendations from that led to us submitting a proposal that was funded to focus on the entry-level biology courses and more advanced biology courses, but that were not being included in the funding part of the proposal. Part of that, one of the strongest recommendations from the 1994 workshop was a production of what might be called a primer on quantitative biology designed to go along with General Biology. That is essentially what weve done with these about 50 modules, that we composed for the General Biology sequence. We keep thinking about, we, in this case, meaning myself and two graduate students, one of whom was trained as a math student who is now completing her PhD in ecology, the other one who was trained as an ecologist and is completing her PhD also in ecology. We are the authors of that primer on quantitative biology, the modules to go along with the teaching. It was also done in collaboration with several other faculty members who teach the General Biology course, whose names are Susan Riechert, Beth Mullin, and Otto Schwarz. Susan is in Ecology, Beth Mullin and Otto Schwarz are in the Botany department here, though Otto is now the Director of the Division of Biology.
I: Can you tell me about some of the obstacles and opportunities that you encountered in the process of developing the courses?
R: Sure, the usual obstacle to doing a mathematics course that is designed for a particular clientele, is that the math departments general unwillingness to offer specialized courses, because the argument is always, What happens? "Who do we get to teach them?" So there wasnt strong opposition from our math department because we actually have a very strong group here in mathematical biology. Its been around for several decades. But it is always a concern. It is a concern I hear regularly from math departments and other places saying, We could never offer this course because it focuses on biological examples and we dont have the faculty to teach it. There are several responses to that, that I can give them to you in a minute, if you are interested...
I: Sure
R: The other sort of obstacle is that they say, Well, how do we know we have enough students for this? In other words they say, Well, we dont want to offer something special for the biologists because then the chemists will want their own course, and the physicists will want their own course, etc., etc. And my comeback to this is that at virtually all major research institutions in the US, the larger ones, there are more biology undergraduates than there are chemistry, physics, mathematics, and sometimes, engineering lumped in, combined; so that the demand is certainly there on the life science front, particularly if you didnt focus this just on biology majors, but if you have an agriculture school, if it included them, if you included nursing students and other pre-health professions. So that argument does not really hold water in this case. As soon as you point out those numbers to them, they realize, Oh, yeah, there are a lot of students there. With regard to the concern about the lack of teachers who might be qualified to teach this, this is a perfect example of the situation in which you want the faculty teaching mathematics courses to be more focused on what it is that motivates their students. And what it is that motivates life sciences students is not mathematics; it's life sciences. And if you can relate the mathematics that you are doing to what motivates the students, you are much more likely to turn them on to why the mathematics is important. This is certainly a change of attitude that is needed. There is an alternative approach, and the alternative approach is one taken by people such as my friend and colleague Claudia Neuhauser. She is on the faculty, actually, she is a head of the Ecology and Evolution Department now at the University of Minnesota, and she wrote a book specifically for undergraduates, to teach them calculus, but with a biological tinge to it. But she wrote the book specifically so that it could be taught by math faculty who dont know any biology. And the difference is that it does not include as much biology as I think is appropriate; but Claudia and I disagree on that. There are other alternatives, too. Fred Adler has written another book that it is also appropriate for that level course, that has a lot more biology in it, but he is at the University of Utah, which also has a very strong mathematics and biology program. But, it has much more of a calculus tint to it than the more discrete math approach and statistical approaches that we include here, and I found that many math departments feel more comfortable with that, than with teaching a course that has a fairly heavy hit of biology in it. So, thats some of the obstacles from the math side of things. The obstacles initially from the biological side of things, about ten years ago were that, well our colleagues don't believe that mathematics is important. Okay, they just, they view this as a hurdle their students have to get over and then they can do real biology. And I think that has changed. It changed completely in the last decade, at least in the U.S.; so that now you pick up any issue of Science and any of my colleagues will acknowledge that if you look at the jobs, they're quantitative. There's computational biology, there's genomics. There are all these areas that require very, very good quantitative skills. And that is where the market is. They will not make that argument anymore. I was just talking with a colleague from France, who is one of their lead developers of mathematics and biology courses, Sandrine Charles and she is at Lyon and she was complaining about exactly this same problem. The biologists there dont feel that mathematics is useful, and that, they are perhaps a little bit behind, but I think it is the same kind of situation will change in France. And other European countries, I think, they are a little bit more akin to the U.S. in this regard. So, that was one of the major initial concerns that I think has disappeared, that virtually all biologists now agree that strong quantitative skills are important to be able to read the literature, and to be able to get to the point in doing thesis research. That doesnt mean they have those skills, and so another part of this battle is incorporating. Another way of dealing with this problem is how to incorporate more quantitative topics within the biology curriculum when the faculty themselves dont feel comfortable with those quantitative topics. And there, thats one of the reasons for having these sorts of modules that fit in that make it pretty easy to understand, admittedly, the mathematics is not very hard, but it is also an ideal situation for collaboration.
I: What about opportunities that you encountered while developing the courses? We talked about the obstacles Were you done with the obstacles?
R: Right, yes, so while this was going on, there was this whole change in attitude towards mathematics going on because of all the growth of genomics and computational biology. That presents tremendous opportunities and these opportunities have been sort of pointed out by reports, such as the BIO2010 report, and a variety of other sort of groups have been formed both within the NSF, the National Science Foundation funded and NIH and Hughes (Howard Hughes Medical Institute) funded. Many of these groups have realized that with future incorporation of a more interdisciplinary approach to biology, by which I dont just mean mathematics, but appropriate training and skill development, and conceptual development in key physical and chemical sciences components, are really important; and along with that, the ability to talk to each other, and developing a language so that undergraduates at least can have some kind of coherent conversation with people with somewhat different skill sets. To me, that is the essence of appropriate undergraduate interdisciplinary training. Its not necessarily being able to have all of those skills yourself, but rather having the conceptual foundation upon which you can have an intelligent conversation with someone with a different skill set.
I: You indicated that the courses were developed with NSF funds, were there funds from any other funder?
R: Internal UT, University of Tennessee support for these. Now there is another whole separate set of courses that we developed with NIH funding that I havent talked about, and, in part, that's because those are designed as short courses that are designed for advanced undergraduates, graduate students, and post-docs in the life sciences. And weve offered about 7 or 8 of those things within the last several years. So there has been NIH support for those; but they are not sort of standard undergraduate courses, or so I can't talk very much about it.
I: To the extent that these courses are team-taught. Can you tell me about the different roles and responsibilities of people who teach those courses?
R: Sure. The ones that I've talked about are not team-taught in the sense, the mathematics courses; if you can view it as a team it would be a faculty member and several graduate students. And the graduate students are essentially there to do labs and sort of help session kind of things. And I wouldnt say that those are really team-taught. The General Biology courses sometimes are team-taught and sometimes they are not. By team-taught, that means that they are taught by two or three faculty members, and some of those faculty members will use these more quantitative modules, others will not, and it is basically up to them how they want to do it. I make them available. We encourage them to talk to us, and to talk to other faculty whove taught the courses that way; but is not really an inter-disciplinary team-taught course, although I do get a question every now and then from someone in the faculty teaching the course.
I: When it is taught by two or three faculty as you mentioned, do they all come from the same discipline or do they come in from different disciplines?
R: Because of the way the General Biology is set up, one of the sessions is basically cell and molecular, and the other one is ecology and evolution; so, but if its ecology and evolution, yes, there are two people from ecology and evolution, and when it is cell and molecular, it is two people, they might have very different sort of focus in their own research, but they're both from the same department, yes.
I: I think what were are looking for here are issues that arise when you have people from distinctively different disciplines like math and biology teaching the same course as opposed to different fields within the
R: We have not team-taught these like that unless you split me in half, because part of me is in ecology and part of me is in mathematics. And I dont know if I have internal conflicts or not.
I: Again, we are looking at issues when there is collaboration across major disciplines, and what happens when those disciplines come together.
R: I dont think that applies to these particular courses taught here. I can give you other undergraduate examples, if you want here.
I: Sure.
R: For example, we currently have a brand new undergraduate research initiative, funded by the NSF through research funding, that involves two of us who are mathematically trained and two of us who are biologically trained in the sense of one's a field biologist and one is a real lab-biologist; so we have a mixture. We have about seven undergraduates involved in this, three of them from that, three of them from biology. And we sit around the table once a week and basically try to develop the same language so that the math students and faculty understand the biology faculty. We read through papers and we take different points of views, things like that; but I would say the majority of the difficulty is communication in terms of conceptual communication of whats really going on, for example, in the papers we read.
I: Okay, so these are some of the difficulties because of your different disciplinary orientations. What about benefits that you derive from your different disciplinary orientations?
R: Oh, boy. The whole area of mathematical biology has benefited tremendously because its let to new mathematics that wouldn't be there without interesting and fascinating biological problems, and it has led to phenomenal understanding of biological systems that would not have occurred without basically quantification and taking alternative mathematical structures, looking at alternative mathematical structures for the biological questions of interest. So the whole field of mathematical biology is in part because it benefits both disciplines.
I: In what ways, if any, has developing and teaching these courses affected your research?
R: To me, research and teaching is one enterprise. I dont view them as separate enterprises. So here is an example. One of my research areas deals with space, spatial problems; we deal with big problems across large landscapes, South Florida Everglades restoration, and small problems that are basically the remediation of sites that have been, which has been pollutants and toxins dumped on, and I regularly talk about those examples in my entry level math courses; because they are current problems and I use relatively simple computer implementation of the same sort of things that we try to do, in a more complicated way, to explain whats going on in the entry-level courses. So, to me it's all one enterprise.
I: Are there similar courses in your department to the ones we have been talking about that integrate mathematics and biology?
R: Yeah, well, these courses are, there are whole variety of upper division seminars that, I mean, graduate seminars that use mathematical approaches in biology. We teach a whole series of them actually.
I: But not at the undergraduate level?
R: No, these are pretty much graduate level. The undergraduate course that I mentioned, that we have this course on essentially modeling in biology. We also have one that is sort of more of statistical approaches in biology, and that is also, that follow on to this.
I: And those are undergraduate?
R: Yes, those are undergraduate, but there are not taught real regularly. Frankly, what we do is encourage our undergraduates to take a more standard statistics for science course, if they can fit in the two semesters that it requires to take it. And those that are going on into research, I always encourage them to do that.
I: How, if at all, do your courses fit within your departments curricular reform efforts?
R: So, now I have to put on a different departmental hat. So, the math department does not really care about curricula reform for anybody except their own majors, at least in the 25 years that I have been here. I've never heard a discussion about curricular reform from anybody except for their own majors, unless there was a college out there saying, We need something different for our students; which has occurred regularly from the engineers. But the biologists, because we have this fine group of mathematical biologists here, the math department has left it up to us to structure the undergraduate curriculum for the life science students. This institution has not had any sort of major undergraduate curriculum review of mathematics as a whole, meaning mathematics, statistics, and computer science, all of the quantitative kinds of things. They probably should be. On the biology front, the stuff that we have done in terms of the Mathematics for the Life Sciences course has basically been picked up as a requirement by the biology division for its undergraduates. So, here, undergraduates in biology are not within my Department of Ecology and Evolutionary Biology or the other departments. They get a degree in biology and they can concentrate, if they want to, in one area or another; but they are actually students within divisions, which includes four different departments. And, with regard to the curriculum for the division, for the undergraduate biology components, weve also had impact, not just on a General Biology courses, but, faculty members use our modules and use some of our examples from using a variety of computer packages in the upper division courses, too. But, we have not emphasized the upper division as much as we focused on the General Biology sequence.
I: How did your colleagues in each of your departments feel about your courses?
R: Well, youll have to ask them. Basically we are left a lot to do what we want. But thank you for the way that you say that. There's not much sort of second-guessing. We are one of the worlds premier groups in mathematical biology, so, these people trust us to do whats right.
I: I think the question is more, you know, how your colleagues in your department feel about the courses you are teaching? Are they supportive, not supportive?
R: Well, here is a good example. Most of the, in terms my time, fits in Ecology and Evolutionary Biology. I am spending most of my teaching time this year teaching courses in the math department, formally, even though it's a course that's designed for biology students. All the brownie points for this course goes to the math department; but the biology division, meaning the division director and my department head in ecology and evolution, feel that this is so important for the undergraduates in biology that I should be spending my time teaching it, even though none of the brownie points worked for, flow back to them. So, that is an indication of how strongly people feel about the importance of this course.
I: I guess you almost pretty much answered the next question, which is how supportive are your chairs of this course?
R: Thats the biology end of it. The math, well we have a new, the previous math head basically left us alone; although I dont think he ever understood what the course was about. To him it was a math course and it shouldn't necessarily have any biology in it. Anyone in the math department should be able to teach it. And I constantly had to battle with him about that, in fact, that it was not a math course, that it intimately involved biology in order to make it successful. So, there were some battles within the math department about this, over the last decade or so, but that head is now gone.
I: Have you received any internal, or external recognition for your courses?
R: Oh, yeah!
I: Can you tell me about it!
R: Well, to start out with, I mean, NSF wouldnt fund this stuff if there werent external recognition for its importance. The Math for Life Sciences course is listed in the BIO2010 report as a case study, what should be done, one approach to what should be done. And I think I got some award from NSF as an Innovator of Undergraduate Education or something like that.
I: How popular are your courses with the students?
R: The students dont have much choice. They are required to take it. If they are going to be biology majors they have to take General Biology, unless they have an AP. Relatively few of the students take AP biology to get out of it. This is different now in the math end of things; there are many more students coming in with AP credit in some areas of mathematics, including statistics than they used to be. And for some of them, they actually get out of the entry-level requirements. I still encourage them to take the first semester of this course, because it covers topics they dont see in their undergraduate , in their high school curriculum.
I: Which of the two courses are we talking about?
R: That is the discrete mathematics one, the portion that is called Math 151 and 152. The first semester is basically discrete approaches in applications to biology, and the second one is continuous, essentially calculus and applications to biology. And, most students will not have seen, most, even if they had a full year-long calculus sequence in high school, they may not have not seen topics within the 151 discrete approaches. They know, I will be honest with you; they know that this course, through the grapevine, is harder than the standard kinds of engineering calculus course. Harder, because it covers more conceptual territory than the calculus course does, much more. Harder, because we do expect a lot from them, and harder because we include real biological examples, so if you look at the student responses, to that kind of questionnaire, they'll all say, This course was really hard. But I certainly believe in setting standards and demanding that students live up to those standards. And at least the comments that I get back from students is, Ive never done, Ive never had funding to do a sort of formal good survey of students several years after this course. Its one that's been on my list of things to try to get funding for. It's just fallen by the wayside. So I dont have good formal assessment of the Mathematics for the Life Sciences course. It's all informal; and they come back to me and say, You know, this made it a lot easier to understand what was going on when we saw these population genetics in my general genetics course. Those kinds of comments.
I: Are there any prerequisites for either of the courses?
R: Yeah, the Mathematics for the Life Sciences course has as a prerequisite the sort of standard entry-level requirements in quantitative skills that is geared for all science students, meaning, anybody who is going to major in biology has to have two years of high school algebra and a pre-calculus course and a geometry course. Its the same sort of entry requirements. The General Biology course does not have any biology prerequisites; in other words it is not required of the students to have high school biology, but the vast majority of them have had it.
I: Let's take the Mathematics for Life Sciences course first. What types of students typically take this course, in terms of majors, minors, where are they coming from?
R: The vast majority of the majors are biology majors. The vast majority of those are pre-med. I have 85 students in the course this semester and approximately 80% of them are pre-meds. The rest are a smattering of other biology majors with interests in other areas, and a few students from Wildlife Forestry and Fisheries, which is on our Ag campus here, a few from Plant and Soil Science, which is another Ag campus department, and a smattering of nursing students.
I: Are you getting any math or computer sciences majors in that class?
R: No, they should not take this sequence. This is a Math for the Life Sciences sequence; its a terminal sequence, in that it is designed to end after two semesters, without leading to more advanced mathematics courses, except for the courses that have been designed specifically as follow ups to it, which in this case would be, particularly the Modeling for Biology course. But, we certainly dont want, we dont want those students here; they have to take the standard sciences and math calculus courses.
I: And the career plans for most of these students are?
R: They all want to be doctor, M.D.
I: Its mainly health science students?
R: It is mainly health sciences. Again, there is probably 20 percent that are in other areas of life sciences. Remember, these are entering students, this is what they think that they want to
I: Sure
R: But a very small fraction wind up going to med school.
I: And are some of these student planning to go to grad school, or?
R: Some are, how many end up doing that, again, they are entering students, they dont necessarily know exactly what they want to do; and sometimes they'll come in and decide, "I really think I want to be a chemistry major, or something else. This is actually one of the objectives to this course, that the mathematicians always make reference, I forgot to mention early on. And that is that, here is a course for terminal sequence for science students, what happens if one of these students wants to be a math major? They have to go back and repeat the calculus? And I say, No. We have been teaching this course for a decade, there have been no cases of anyone is coming to me after having sat through this thing saying, I want to be a math major. They know, pretty much in advance whether they want to be a life science major or not, or at least have some idea they're interested in some area of sciences, not mathematics or computer sciences.
I: And what about your General Biology course, in terms of the mix of students in there?
R: Well this is taken by us to be anyone, could be humanities students, although most of the humanities are students who need a science course take the non-majors General Biology sequence. So the one that I was talking about, I probably didn't make clear, it is designed as a course for majors, but majors also include science students from chemistry, physics, engineers who are interested in, for example, bio-medical engineering, will take it; as well as all of the students in the Ag campus.
I: Since these are introductory courses, I am not sure how applicable the next question is, but let me ask it any way. How adequate are students backgrounds in biology, math and computer science for these courses?
R: It is relevant that they have a strong background, because students come into these courses, both the biology and the mathematics course having, supposedly, been exposed to essentially four years of high school mathematics, and, frankly, many of them dont understand anything about the basic applications of those to some area outside, on some sort of given problem on which they are given an equation and asked to solve. So, their background, and this is not just true of biology students, it's true of physics and chemistry students. All faculty will tell you that students dont have an adequate conceptual basis for solving real world problems using mathematics. They might have the skills once something was formulated in a really mathematical way to figure out how to solve it, but getting to that formulation is something that theyve not been trained yet to do generally, speaking in generality of the average student. Of course there are some who are very well trained. The thing that the life science faculty have told me again and again, and continue to tell me, that they would like their students to get out of these entry-level courses, both the Biology and the Math for Life Sciences course, is the ability to read, construct, and understand graphs. And that is the first thing we focus on in the Math for the Life Sciences course, and is something we focus on in a fair amount in the modules we've constructed for the General Biology sequence.
I: Okay, we have talked a little bit about graduate students. Do they have a role in both of your courses?
R: Yes, actually graduate students have been the primary teachers for the Math for the Life Sciences course. They have been sort of TAs, or currently I use them as TAs. These beginning graduate students who have essentially one course in biology, and aside from that, their undergraduate training is completely in mathematics, so they dont have much of a framework for understanding the biological components, but we work with them on that and we provide them with a variety of materials and so on.
I: So, these are graduate students in mathematics?
R: These are graduate students in mathematics. Now, there are exceptions. For example, one of the students who taught this course last year, is doing her PhD here in Ecology, but most of her training was actually in mathematics, but she was trained by one of the premier Latin American teachers in mathematical biology. So she knew a lot of biology and she was admitted to graduate school for the PhD program in Ecology, even though she didnt have much formal biological training. And she was the ideal person to teach this course. She had a foot in both camps. She is an interdisciplinary scientist. And although she was a graduate student, she was probably much better for teaching this course than a full professor of mathematics who knew nothing about biology and had no interest in learning it.
I: Do they need any special training to assist on this, or teach this course, mathematics?
R: So, I am talking now about the math course for the life sciences course.
I: Do graduate students need special training?
R: Yea, they cant, this was my argument with the department head over the last ten years, is that you cant get any old graduate student and throw them in. They will just fail, the students will know, they will just fail, because they dont know anything about the biology. So you have to have students who actually have some kind of conceptual background in biology, at least conceptual and, hopefully, more than conceptual, in order to be good at teaching this course.
I: So you are basically selecting students who have that background, or you provide the training?
R: No, we select students who have that background and then, when necessary we couple it with materials that we provide, or they come and ask us questions, How do I motivate this? or Can you give some examples of this? and I pull out my collections of books and give examples and things like that. But the majority of students that we've had teaching that course, who were math background people, were people who sat through a yearlong graduate course that we teach in mathematical ecology. So they at least had some framework in this.
I: Okay, about the role of graduate students in your General Biology course?
R: Okay, so, they are mainly there to do labs, basically, so its not, its really quite different from the graduate student role in the Mathematics for the Life Sciences course. General Biology is taught as a big lecture with lab sections.
I: So does their role involve any integration in mathematics or is it just focusing on the lab?
R: Well, the lab is one of the places in which there is quantitative skill requirements needed, so this is one reason why we constructed this supplement to the lab manual that focuses on the statistical quantitative methods that are appropriate for the labs within that collection, sort of standard labs; so they need to be familiar with that, but I think that the quantitative skills that our entering graduate students in Life Sciences, in Ecology, I cant speak for Cell and Molecular Biology, but in Ecology the quantitative skills that they have are far superior to what they were even ten years ago. Virtually all of them have had a fair amount of statistical background, not all, but most of them have had some introduction to mathematical modeling; and many know how to use some computer software, like the standard statistical analysis software, SAS, J&P, and a fair number come in knowing how to use the mathematical packages, like the Matlab and Mathematica.
I: But they dont get special training introduced with your course, or do they?
R: For the General Biology?
I: Yeah...
R: The General Biology has their own little training program for them in terms of the labs, but it is not special for the quantitative stuff.
I: Okay. We are getting near the end now. What lessons have you learned about developing a course that integrates biology and mathematics that you would like to share with others?
R: So, I actually wrote a whole thing on this that deals with not just life science, but in general how to develop quantitative interdisciplinary curriculums. I call it the CPA approach. CPA stands for Constraints, Prioritize, and Aid, in which I look at this process as, first of all understanding what the constraints are, and here I am speaking from the perspective of a quantitative department, it could be Computer Science or Mathematics or Statistics, which is attempting to aid or assist colleagues in another discipline with incorporating more quantitative approaches. My focus, of course, has been on life sciences, but I think it applies to others as well, particularly social sciences, things that are not inherently quantitative like chemistry and physics. So constraints, meaning, first of all, understanding what the constraints are on your colleagues, in terms of how much time you can expect their students to commit to the kinds of courses that you are talking about. P stands for prioritize, meaning that you need to work with your colleagues in other disciplines, to prioritize and say, What are the key conceptual approaches that you can really expect the students to get? and that also requires a lot of backward and forward; and then A is for Aid, that means assist your colleagues in incorporating these quantitative concepts and ideas in their own courses and dont just funnel it off to a course.
I: Any other lessons that you've learned that you'd like to share with others?
R: Well, start small. Whenever I am approached by people at other institutions, this is often young faculty members who say, I have been hired in this place, I am in a biology department, or I am in the math department, and I want to do something. How do I start?" And my assumption has always been to start small, you start with what you might call teaching circles, find one or two collaborators who have some similar ideas to you and do course development based around them. And it might just be a simple seminar course to start with, dont try to go whole hog and do the whole curriculum.
I: What factors would you say have been critical to the success of your courses?
R: NSF support, one. Number two, a great group of colleagues here who are inherently interdisciplinary and realize the importance of quantitative approaches in a field that was, frankly, not very quantitative up until relatively recently. So support from colleagues. Support from the NSF. And the support of the infrastructure, in terms of providing access to technology that we found useful in these.
I: What advice would you give to others planning to develop, or teach a similar course, or courses?
R: First of all, sit down and talk to a lot of people who are involved in setting the curricula for the students of concern to you. I mean if this is life sciences and you are in a math department that means going around and having lunch with a lots of life scientists; and bouncing ideas off them and see what their ideas are. Getting their ideas about what it is that is important to them; and reading the literature, reading BIO2010, reading other approaches to incorporate quantitative or other ideas within the education of your students. There is a large literature out there, and there is a lot that you dont have to reinvent. Theres a lot of material that has been supported by NSF, you dont have to think it all up yourself - and NIH, too.
I: Is there anything else you would like to tell me about your courses?
R: Its been a lot of fun! Yeah, it is an awful lot more fun to do things that the students enjoy, and they might not enjoy every piece of it, but it's a lot more fun, and I get a lot of enjoyment about bringing in the most recent papers published in Science and Nature and showing them, Here is something we are talking about today; which, frankly, I dont think most of my colleagues who teach standard straight calculus would ever do.
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