Programming As a Part of a Science Education?

An anonymous reader writes "I'm a fairly new physics professor at a well-ranked undergraduate university. When I arrived, I was surprised to discover there were no computer programming requirements for our majors. This has led to a series of fairly animated faculty curriculum conversations, driven by the question: to what extent should computer programming be a part of an undergraduate science education (in particular, physics)? This is a surprising line of questioning to me because in my career (dominated by research), I've never seriously even questioned the need. If you are a physics major, you learn to program. The exact language isn't so important as is flow control, file handling, basic methods/technique, basic resource management, and troubleshooting. The methods learned in any language can then be ported over to just about any numerical or scientific computational problem. Read on for the rest of the reader's questions and his experiences dealing with faculty who have their own ideas. The reader continues, "I'm discovering the faculty are somewhat divided on the topic. There is even a bizarre camp that actually acknowledges the need for computer programming, but turns my 'any language' argument on its head to advocate the students do 'scientific programming' using Excel because it is 'easy,' ubiquitous, and students are familiar with it. They argue Excel is 'surprisingly powerful' with flow control and allows you to focus on the science rather than syntax. I must admit that when I hear such arguments I cannot have a rational discussion and my blood nearly boils. In principle, as a spreadsheet with simple flow control in combination with visual basic capabilities, Excel can do many things at the cartoon level we care about scientifically. But I'm not interested in giving students toys rather than tools. As a scientist raised on a heavy diet of open source software and computational physics, I'll hang my head in shame if our majors start proudly putting Excel down on their resumes. However, in the scientific spirit, perhaps I'm missing something. So I ask Slashdot, to what extent do you feel computer programming should be a part of an undergraduate science education? As a follow-up, if computing is important, what languages and software would best serve the student? If there are physics majors out there, what computing/programming requirements does your department have? My university is in the US, but how is this handled in other parts of the world?"

Comments

CMU

[allanw]

The introductory physics classes at Carnegie Mellon use VPython to run some simulations. It's pretty simple to use and intuitive. The textbook makes use of it too.

Re:CMU

[cashman73]

I'm currently working in the computational biology department at the school across the street from CMU,... A lot of people don't think of "programming" and "biology" in the same sentence, and most biology programs are the last science programs that would even think of requiring programming as a prerequisite for graduation. However, once you get into the more specific structural and molecular biology fields, you almost can't escape programming. Almost on a daily basis, I use perl. Most of our software is probably coded in C or C++, and some of the older software is coded in Fortran, though that's not as common anymore. Some people in our department have been doing some stuff with Python, too, though I personally haven't. There's also quite a few genomic and database applications where SQL will come in handy for the database work, and an increasing amount of computational biology projects are coming online with web interfaces, so PHP could be useful.

Re:CMU

[somersault]

Yep - one of the engineers at our company used to work for Rolls Royce in the 70s, and at some point was a professor at Aberdeen University. He used to use FORTRAN, possibly some other languages too, but basically at the moment he does most things in excel (I think he likes Matlab too but the stuff I've seen him do mostly involves Excel). It seems to be pretty powerful, and good for easily graphing results from large datasets, etc. I've been doing work converting a couple of the engineer's hydraulic simulation spreadsheets over to Delphi (so that people other than the engineers can use the calculations, and can't see or change what's going on behind the scenes, since these spreadsheets are simulating what the tools we build can do, and they don't want our competitors getting too much information). I can definitely see the attraction of doing calculations on large datasets the Excel way - or rather, the 'spreadsheet' way, since Excel isn't the only spreadsheet system, just the most common..

Perl, probably Python now

[Average]

Back in undergrad, I helped my AtmoSci Masters' roommate out with several projects. At least in his case, the problems involved a lot of comma or space separated text files and mostly just limited data manipulation. Students had all been taught FORTRAN, weakly, and most classmates were trying to do it in FORTRAN. Several times, we created 20 line not-terribly-obfuscated Perl programs that worked much better than pages of FORTRAN for the task at hand.

Probably Python would be the 'cooler' kit these days. But, my former roommate, now with the National Weather Service, says it's all command-line Perl scripts there and working with me to learn Perl was one of the best things he got in college.

"Other parts of the world"

[DancesWithBlowTorch]

My university is in the US, but how is this handled in other parts of the world?"

I studied physics in Heidelberg, Germany. During the first half of my first year (about 6 years ago), we had introductory courses in C (they liked to call it C++, but it really was glorified C). In the second half of the first year, there was a "technical informatics" (read: Hardware design) course, which involved every student designing a little 16bit chip which could decipher the DCF long-wave time signal. That part used mostly C, but had some bits were we had to gnaw through Assembler.

That was my formal introduction to computing. Later on in my course, I mostly used MatLab, and occasionally C. Sometimes I had to reverse-engineer old Fortran code. I wrote my Master's thesis in MatLab (even though it was a rather computationally expensive application. In scientific applications, the time saved during design time often easily makes up for the loss in computational efficiency).

Since I started my PhD, I've tried a lot of different languages, from MatLab to Java, C# Python and, recently, F#. Even though I was brought up with OSS (my laptop runs Debian next to Windows), I have come to value the rapid development capabilities of .NET (I know, it sounds crazy. Please try it out before you flame. Visual Studio is certainly the best (maybe the only good) piece of software Microsoft ever made). But I'm a theoretician, so my focus is on being able to rapidly change my code to incorporate new ideas. Experimentalists, who mostly just want to control their machinery, need to know more about Fortran, C, and on the high-level side, LabView and MatLab

I think my point is: It's probably a good idea to start with powerful low-level languages like C first, but don't overdo it. It's good if your students know about the existence of Assembler and Fortran, but the important point is that they lose their fear of computers. Nowadays, teenagers grow up with computers, but they never get to see behind the web 2.0 surface. Our generation grew up with text editors and batch files. They grow up with facebook. So it's important to give them a look behind the curtains. Let them feel the power of being able to control memory adresses. Once they have lost their fear of pointers, they can move on to use high-level languages that safe loads of design time, while being able to descend down into the architecture when it really counts.

Re:"Other parts of the world"

[LihTox]

A word of warning about Mathematica, Matlab, Maple, etc: they're great when you're a student, but should you find yourself between jobs (e.g. teaching part-time while applying for tenure-track positions) for very long, you may be cut off and you won't know what to do. (Speaking from experience here.) This might not matter to an experimentalist who can't do research outside of a lab anyway, but for a theorist like myself it has been crucial that I be able to use open-source software (and therefore know how to do numerical integration, gradient searches, etc) so that I can maintain a research program, keep publishing, and not drop off the map professionally.

Re:"Other parts of the world"

[Bud]

There's an OSS Matlab clone called GNU Octave, see http://www.octave.org/. It's mostly compatible with Matlab. I've been using it for handling larger datasets or maths-heavy stuff. Works fine. --Bud

Numerical methods requires programming

[davros-too]

Every physics graduate should have a grounding in numerical methods. This requires some programming, but the critical point is that the numerical methods drives programming not the other way around.

Every physics graduate should have the ability to find and use Numerical Recipes by Abramowitz and Stegun. Doesn't matter if they're using the C version, Fortran or whatever. This means you need to teach some programming, but more importantly the skills to understand the recipes.