An Integrated Science Curriculum at Princeton

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00:00:15.20 Hello, I'm David Botstein.
00:00:17.18 I'm the director of the Lewis-Sigler Institute for Integrative Genomics
00:00:23.15 at Princeton whose beautiful building you see before you.
00:00:30.03 The Institute was founded with the dual mandate of doing teaching and research
00:00:37.03 at the interface of biology and the more quantitative sciences,
00:00:43.08 computer science, physics, and chemistry on the other.
00:00:49.12 And what I'm here to tell you about today is a curriculum that
00:00:53.29 we've developed with that idea in mind.
00:00:58.01 What we do is we allow freshmen who have an interest in becoming
00:01:05.04 professional scientists to choose between the standard way of becoming
00:01:11.01 a physics major or chemistry major or biology major, and
00:01:14.23 an integrated introductory course, which I'm going to tell you about,
00:01:19.27 where they spend the first two years learning all of these areas together
00:01:27.27 in an integrated way and, as you'll see, with a much higher quantitative emphasis
00:01:33.01 than you would have in anything but probably the physics curriculum.
00:01:39.18 So, the curriculum is aimed at students who are willing to do the math.
00:01:47.24 And it's really a matter of willing.
00:01:51.00 Most entering freshmen at Princeton have calculus credit from the Advanced Placement.
00:01:58.02 And we basically tell the students that if they want to do this they
00:02:02.00 need to have Calculus BC or the equivalent. It's not intended for every student.
00:02:07.23 The curriculum was designed from the very first not to replace anything.
00:02:12.18 We're not reforming things. We're giving students a choice, an alternative.
00:02:19.05 The curriculum integrates math, physics, and chemistry,
00:02:22.05 and computation all the way through.
00:02:24.05 It...we start at the most introductory level.
00:02:29.00 Other than calculus we don't expect them to have learned anything
00:02:32.22 except, you know, sort of standard high school stuff.
00:02:36.02 And we point this in the direction of a project based laboratory course,
00:02:42.21 which they typically take in the third year
00:02:45.10 if they want to continue in the general area of quantitative biology.
00:02:53.10 We have to emphasize that the outcome here is that the students end up
00:03:00.27 becoming physics majors or chemistry majors along with everybody else.
00:03:06.15 So the advanced stuff is not integrated or separate or whatever,
00:03:10.10 except to the degree that the student does that for him or herself.
00:03:15.28 OK, why are we doing this?
00:03:17.12 Well, the reason we're motivated to do this is
00:03:19.26 what I call the cultural gap, especially from the point of view of biologists.
00:03:25.03 The education of biologists has become much less quantitative in my lifetime.
00:03:29.13 Most colleges require minimal mathematics, no physics, or physics without calculus
00:03:36.07 (if you can believe that!) and no computation.
00:03:38.27 Quantitative preparation is limited to prerequisite courses,
00:03:42.26 which are not notable for their success,
00:03:46.03 largely because they try to teach a very heterogeneous group of students
00:03:50.10 and very large numbers of them and most U.S. biology Ph.D. students have only had one year of math.
00:04:02.15 It's become a real problem for biology
00:04:05.06 because the genome and the computer have completely changed the rules.
00:04:09.06 And the cultural gap has become so serious that it's sometimes hard for physicists and biologists
00:04:17.14 or statisticians and biologists to actually communicate effectively and work together.
00:04:24.11 And cross-training at the graduate and post-doctoral level has not been notably successful.
00:04:32.11 So that's why we wanted an integrated curriculum.
00:04:34.25 The first thing of how to do it is you have to get together
00:04:40.16 with your colleagues in physics and chemistry, biology and computer science,
00:04:47.03 and you have to decide what you want to teach.
00:04:48.28 And the first thing you realize is that the integrated curriculum can't be the sum of everything.
00:04:55.12 What we did was we studied every idea that is taught in the standard introductory courses,
00:05:01.09 and we put them into two piles: things that we all agreed across the divides of the disciplines,
00:05:07.10 all agreed are really fundamental, and a lot of things which we thought are really just traditional.
00:05:14.19 And we threw out the traditional, looked at how much we had to teach,
00:05:18.22 added in the things that are missing from even a traditional curriculum
00:05:23.26 and ensemble and made a program.
00:05:31.15 The other thing that we decided was that we were going to teach everything just once.
00:05:34.16 For example, teaching calculus in the guise of physics
00:05:37.21 and teaching calculus again in the guise of chemical reaction rates
00:05:41.23 and then teaching calculus again as a mathematical thing didn't make sense to us.
00:05:46.15 And we believed very much in the "just in time" principle.
00:05:50.20 We don't believe in "Learn this now, it's good for you later."
00:05:56.16 The professional scientist has to be a lifetime learner and most of that learning
00:06:02.10 is going to be when you realize that you need it and not preparation years in advance.
00:06:09.10 And we of course have organized this course in such a way that the students can
00:06:14.12 actually migrate into other tracks with out a great deal of difficulty
00:06:20.05 so that the introductory requirements are met.
00:06:24.27 This required, as you may imagine, a certain amount of negotiation.
00:06:27.27 But because we started out as a collaboration, it worked out.
00:06:33.12 OK, how do we distinguish the fundamental from the traditional?
00:06:37.17 Well, we don't teach a lot of history.
00:06:41.25 We don't teach things that people already know.
00:06:44.05 For example: How do we know DNA is the genetic material?
00:06:47.27 Well, in 1943 there was a very famous experiment by Avery, MacLeod and McCarty.
00:06:53.12 But there are two reasons why we don't teach about that.
00:06:56.05 One is, the students already believe that DNA is the genetic material.
00:06:59.20 They watch CSI, and they watch Law and Order, and they're not in doubt about this.
00:07:05.20 We don't have to convince them.
00:07:07.12 And the experiment that Avery did is completely obsolete. You wouldn't do it that way today.
00:07:12.29 On the other hand, we do teach the method of Luria-Delbruck for measuring
00:07:17.06 mutation rates because if you want to know for sure what a mutation rate is today
00:07:21.13 you still have to do it the way they did it in 1943.
00:07:24.19 So that's a good example of fundamental versus traditional.
00:07:30.02 How do we measure Avogadro's number?
00:07:32.25 OK, well we have many choices. There are many ways to do this.
00:07:36.07 And we chose one which has the most resonance in all the different fields as you'll see.
00:07:41.27 How do we find the right distribution in statistical significance?
00:07:46.07 A perennial problem and the standard way of teaching it is really very bad in our opinion,
00:07:52.22 but what we do is we teach the students first how to do a simulation
00:07:56.09 and get an approximation from a computer and only then worrying about
00:08:01.04 what a closed form expression or what the distribution might actually look at.
00:08:09.29 And so the answers to one, two, and three are:
00:08:12.12 We would do it by sequencing today. We would do it by Brownian motion
00:08:16.26 (we teach them Brownian motion) and by simulation.
00:08:21.09 OK, so what did we actually do?
00:08:23.01 Year one we have a double credit course. It's half of the students' time;
00:08:26.23 five hours of lecture a week, a lab...a computer lab and section.
00:08:31.07 And it's equivalent of four one semester courses in the Ivy League.
00:08:35.17 And in year two it's two regular courses.
00:08:40.11 The faculty is sort of...you know...Noah's Ark of people in different fields.
00:08:47.05 And the asterisks are people who are members of the National Academy.
00:08:52.03 So this is not a bunch of post-docs doing this.
00:08:56.06 OK, we have a laboratory section and we have Lewis-Sigler Fellows
00:09:02.00 who teach in the laboratory and we have an opportunity
00:09:10.01 to take a project laboratory for those who want to continue in quantitative biology.
00:09:16.05 So the integrated approach is...this is what we do:
00:09:19.22 beginning freshman year they come in and we start to teach them about things
00:09:25.16 from the point of view of the mathematics used to describe them.
00:09:28.28 So linear models, differential equations, probabilistic models, fields, quantum world and so on
00:09:35.11 as you can see on the slide. I'll give you just one example.
00:09:38.25 When we get to the dynamical models of differential equations
00:09:42.07 what happens is that Bill will take them through the whole...
00:09:49.21 derivation of Newton's Laws, which is of course
00:09:53.07 what calculus and differential equations were invented for,
00:09:57.11 and then the chemists will go through chemical reaction rates.
00:10:01.29 It turns out the be the same mathematics.
00:10:04.16 And then typically I will teach about DNA re-association kinetics,
00:10:09.01 which is again the same mathematics. And so by the end of that time
00:10:12.15 everybody gets the idea that this particular subset of mathematical things is worth knowing.
00:10:20.10 We have problems sets.
00:10:22.09 They're very demanding and they use both analytic and computer methods.
00:10:28.04 We have a laboratory in which we teach basic principles with the technology of today.
00:10:41.03 The whole idea here is to take things, some of which are very old like Brownian motion and Luria-Delbruck,
00:10:48.17 but still to teach them by today's technology
00:10:52.00 and the...of course the data then get used in computer science stuff.
00:10:56.28 I think I neglected to say that of course from the very beginning they are...
00:11:02.10 the first thing that they do is learn how to program in Java and MatLab.
00:11:08.09 Here is the measurement experiment. It's the falling ball viscometer.
00:11:13.13 There you see a student dropping it in and doing it by hand.
00:11:16.26 And then the partner is there with the stop watch.
00:11:20.18 And then that turns into a thing on the monitor over here.
00:11:26.05 And then they measure on the monitor, and by the end of the day
00:11:29.01 they have migrated from the 17th century where this was subject to
00:11:34.01 you know, how fast can you push the button, how good is the stop watch,
00:11:37.06 and so forth and so on, and now what's the parallax, to taking pictures with a camera
00:11:44.06 and then doing the calculations with the computer.
00:11:48.14 They...this is the Brownian motion experiment. As you can see the data are very good.
00:11:54.10 This is student data.
00:11:57.06 And the second year we get less physical and chemistry
00:12:02.17 and we have more chemistry and biology, but it's still the same philosophy.
00:12:08.00 We have substitutes for genetics and biochemistry prerequisites
00:12:13.15 and it includes...we are relentlessly quantitative. We teach all kinds of quantitative things.
00:12:19.09 So the principles and practices are:
00:12:21.20 Focus on the important ideas and do them well.
00:12:24.16 Teach every idea from the viewpoint of the technology of today.
00:12:29.14 And never go out of the way to teach from history and never go for coverage.
00:12:36.13 What we want is skill and not coverage and breadth.
00:12:41.14 The students are enrolled by self-selection.
00:12:45.15 If you want to do this at home you have to have a very realistic description
00:12:49.10 of the content and level so the students don't do the wrong thing.
00:12:53.04 We provide lots of problem sets and help sessions,
00:12:55.24 and in fact we encourage the students to discuss the problems among themselves,
00:13:00.02 and they hand in their understanding at the end of all of that.
00:13:05.12 And we have been evolving the program because if it doesn't work, we change it.
00:13:11.09 So, what are the outcomes?
00:13:13.08 Well, when we came to Princeton it was a big issue that fewer and fewer students
00:13:19.14 were wanting to go to graduate school to become scientists.
00:13:23.07 And we appear to be reversing that trend.
00:13:26.21 We've had 41 who've finished the freshman course.
00:13:29.11 The majority have gotten a certificate, and as you see from the list
00:13:35.14 they have gotten into, and then they are in, the
00:13:39.11 leading graduate schools that are interested in quantitative biology and genomics.
00:13:46.01 And statistics continue to be good.
00:13:50.24 And that's it.
00:13:52.28 Except to say that this is a picture of the pioneer class.
00:13:56.28 The first class that took the program and this is... they had a double course.
00:14:02.07 The exams were really challenging.
00:14:05.25 The problem sets were really hard, but their morale, however, was so good that
00:14:10.20 what you see here...this photograph was taken about five minutes after the end of the final examination,
00:14:17.11 and they had had nothing better to do during finals week than to design a T-shirt
00:14:24.06 and organize it so that they're all wearing it to the final.
00:14:28.06 So we think that one of the maybe most important take home lessons is
00:14:34.25 that maybe the standard program and prerequisites far from being too challenging
00:14:41.25 is not challenging enough intellectually.
00:14:44.15 That there's lots of competition, but the competition is for grades,
00:14:47.20 and what we have done is try to substitute competition for understanding.
00:14:52.20 Thank you very much for your attention.

This Talk

Speaker: David Botstein

Audience:

Educators of H. School / Intro Undergrad
Educators of Adv. Undergrad / Grad
Educators

Recorded: April 2011

Talk Overview

Dr. Botstein explains why and how he and a group of faculty from Princeton University designed and implemented an undergraduate introductory science curriculum that integrates biology, physics, chemistry and computer science courses and emphasizes quantitative research.

Speaker Bio

David Botstein

David Botstein has been the Director of the Lewis-Sigler Institute for Integrative Genomics at Princeton University since 2003. (For more information on this institute and its unique program, see Botstein’s talk. Prior to this, Botstein was a professor at the Massachusetts Institute of Technology and Stanford University. He also worked in the biotechnology industry as… Continue Reading