TITLE: Workshop 1: Creating a Dialogue Between Science and CS
AUTHOR: Eugene Wallingford
DATE: November 15, 2007 8:34 PM
[A transcript of the
SECANT 2007 workshop:
Table of Contents]
The main session this morning was on creating a dialogue between
science and CS. There seems to be a consensus among scientists
and computer scientists alike that the typical introductory
computer science course is not what other science students need,
but what do they need? (Then again, many of us in CS
think that the typical introductory computer science course is
not what our computer science students need!)
a physics professor at North Carolina State, addressed the
question,"Why computation in physics?" He said that this was one
prong in an effort to admit to physics students "that the 20th
century happened". Apparently, this is not common enough in
physics. (Nor in
To be authentic to modern practice, even intro physics must show
theory, experiment, and computation. Physicists have to
build computational models, because many of their theories are
too complex or have no analytical solution, at least not a
What excited me most is that Sherwood sees computation as
a means for communicating the fundamental principles of
physics, even its reductionist nature. He gave as an
example the time evolution of Newtonian synthesis. The closed
form solution shows students the idea only at a global level.
With a computer simulation, students can see change happen over
time. Even more, it can be used to demonstrate that the theory
supports open-ended prediction of future behavior. Students
never really see this when playing with analytical equations.
In Sherwood's words, without computation, you lose the core of
He even argued that physics students should learn to program. Why?
More on science students and programming in a separate entry.
Useful links from his talk include
a part of the National Science Digital Library for educational
resources in physics and astronomy, and
dubbed by supporters as "3D Programming for Ordinary Mortals".
I must admit that the few demos and programs I saw today were
The second speaker was
a professor in earth and atmospheric sciences at Purdue. He
views himself as a modeler dependent on computing. In the last
year or so, he has collected 55 terabytes of data as a
part of his work. All of his experiments are numerical simulations.
He cannot control the conditions of the system he studies, so he
models the system and runs experiments on the model. He has no
Diffenbaugh claims that anyone who wants a career in his discipline
must be able to do computing -- as a consumer of tools,
builder of models. He goes farther, calling himself a black sheep
in his discipline for thinking that learning computing is critical
to the intellectual development of scientists and non-scientists
When most scientists talk of computation, they talk about a tool
-- their tool -- and why it should be learned. They do not talk
about principles of computing or the intellectual process one
practices when writing a program. This concerns Diffenbaugh,
who thinks that scientists must understand the principles of
computing on which they depend, and that non-scientists must
understand them, too, in order to under the work of scientists.
Of course, scientists are the only ones who fixate on their
computational tools to the detriment of discussing ideas. CS
faculty do it, too, when they discuss CS1 in terms of the
languages we teach. What's worse, though, is that some of us in
CS do talk about principles of computing and intellectual
process -- but only as the sheep's clothing that sneaks our
favorite languages and tools and programming ideas into the
The session did include some computer scientists.
of Princeton described an interdisciplinary "first course in
computer science for the next generation of scientists and
engineers". On his view, both computer science students and
students of science and engineering are shortchanged when they
do not study the other discipline. One of his colleagues
(Sedgewick?) argues that there should be a common core in math,
science, and computation for all science and engineering
students, including CS.
What do scientists want in such a course? Wayne and his
colleagues asked and found that they wanted the course to
cover simulation, data analysis, scientific method, and
transferrable programming skills (C, Perl, Matlab). That
list isn't too surprising, even the fourth item. That is
a demand that CS folks hear from other CS faculty and from
industry all the time.
course they have built
covers the scientific method and a modern programming model
built on top of Java. It is infused with scientific examples
throughout. This include not examples from the hard sciences,
such as sequence alignment, but also cool examples from CS,
such as Google's page rank scheme. In the course, they use
real data and so so experience the sensitivity to initial
conditions in the models they build. He showed examples from
financial engineering and political science, including the
construction of a red/blue map of the US by percentage of the
vote won by each candidate in each state. Data of this sort
is available at
National Atlas of the US,
a data source I've already added to my list.
The fourth talk of the session was on the developing emphasis
on modeling at Oberlin College, across all the sciences. I did
not take as many notes on this talk, but I did grab one last
link from the morning, to the
Oberlin Center for Computation and Modeling.
Occam -- a great acronym.
My main takeaway points from this session came from the talks
by the scientists, perhaps because I know relatively less about
what scientists think about and want from computer science. I
found the examples they offered fascinating and their perspectives
on computing to be surprisingly supportive. If these folks are
at all representative, the dialogue between science and CS is
ripe for development.
- So there are "no black boxes". He wants his students to
program all the physics in their simulations.
- So that they see common principles, in the form of recurring
- So that they can learn the relationship between the different
representations they use: equations, code, animation, ...