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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?"
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.
While a lot of computational physics requires speed, I find myself on a daily basis needing to write simple programs to collect, filter, transform and plot data. I have found no better language for writing these quickie tools in than Python.
Once they know Python, then they can pick up C++ or Java as context requires it. And if they never have to deal with really huge amounts of computation, then Python + Scipy might get them by for most everything. (And if not, Python has bindings for everything, practically.)
Physics requires number crunching. It's that simple. It's not much use learning differential equations if you're incapable of solving anything useful. Any physics or engineering major should learn at least basic numerical methods and how to implement them. For me, we did it with C, nothing fancy. As far as using Excel for scientific computing, some of my classmates tried to pull this in a heat transfer class. It's a joke, it'll work for something really simple, but it's no good for any serious work.
I'm not suggesting that all physics students must learn C++ and Matlab, but they should be taught a grown-up computer language so that they at least understand the concept of C++ objects, or how to begin solving the problem of communicating with a machine via a Matlab environment.
My examples are very specific, but you get the idea. Physicists need to be aware of certain computer programming concepts (which cannot be gleaned from experience with spreadsheets) otherwise they will fall flat on their face when faced with a real research environment.
The specific language is not very important, but physics tends to be dominated by C/C++ and Fortran, so these would definitely be a good place to start.
Even BASIC is better than Excel.....
All of the libraries and programs of interest are in C and FORTRAN. C++ is interesting and used but the other two still dominate. If you had to chose between the two for teaching people to program, take C. For utility, the two are about equal.
It depends on what you feel they MUST learn.
Certainly Excel can be a powerful, and useful, tool in data analysis. But I agree, I would never call it programming.
For simulation, however, I would expect you need something a bit more powerful. Perhaps you can teach all the students how to use Excel to analyze experimental data, and design a separate course for simulation design, which would, in turn, use a far more featured language/toolset.
The big danger with trying to teach a "real" language is that you spend the whole semester teaching students with no aptitude for the work the basics of structured programming and they still won't have time for the numerical analysis that is important to them as scientists. Structured programming is as natural as breathing to a geek, but it would be a bit more of a struggle to somebody without the right mindset. I don't see any way of forcing two required semesters of programming on every student. Just not room in the schedule for it.
However, keep in mind that the purpose of college is not to get those students employed, it is to teach them to think. Your brighter students are going to figure out that as a practical skill, most of them will need to know how to program, and would possibly sign up for "Programming for Theoretical Science Majors" as an elective The not-so-bright students... well... they will struggle in the real world, just as they always have.
SirWired
learning to program in excel / vba DOES do what you CLAIM to want (flow control, file handling, basic methods / techniques, troubleshooting), so why is your blood boiling? preconceived notions? and yes, excel IS surprisingly powerful (those who don't think so aren't leveraging its capabilities). someone who can PROGRAM in excel / vba (versus just manipulate a spreadsheet) will be perfectly capable of programming in perl / python / fortran with very little additional work if the need arises.
(i'm an aerospace engineer, and for work, i program in c, fortran, java, vb, and yes, excel / vba,depending on the need)
http://aps.arxiv.org/abs/0803.1838
DNA in your Linux: DNALinux
Bottom line: IMHO no special effort to add programming to a physics curriculum should be necessary. However, there are obviously classes where programming is essential to the physics content and for those you would horribly disserve your students by candy-coating the computational aspects.
Require programming as a pre-requisite where the class requires it, and if that means that none of the reasonable degree tracks are possible without it then you have your answer.
Lacking <sarcasm> tags,
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.
A solid understanding of the nature of floating point numbers wouldn't hurt either. For example, something like David Goldberg's What Every Computer Scientist Should Know About Floating-Point Arithmetic.
As to the language not being important, I don't know that that's entirely true. Each language offers a choice of types and some sets of choices are more instructive than others. I personally think Lisp or Scheme are good teaching candidates because they offer arbitrary precision integers and rational numbers in addition to basic floating point number types so that it's easy to see side-by-side the trade-offs being made between correctness on one hand and space/speed on the other hand that go along with choices in this regard.
Plus, if you go the Scheme route, you get teaching materials focusing on good abstraction like Sussman and Wisdom's Structure and Interpretation of Classical Mechanics , the proper companion to Abelson and Sussman's popular CS text Structure and Interpretation of Computer Programs !
Kent M Pitman
Philosopher, Technologist, Writer
The GSL is mostly C. It's useful for students to take a numerical methods class and recreate the basics and to understand the limitations. Once they know, they can use libraries like GSL to get real work done.
Excel is not only a joke for real problems, it's a real problem to grade.
...one might expect, given the ubiquity of computers, that everyone (not just science majors) have some basic understanding of programming, even if it's just -- err --- BASIC.
I'll go even further and suggest that this isn't appropriate for college, but would fit nicely into 6th and 7th grade algebra.
What good reason is there that would make Matlab insufficient for a physics major? What amount of programming does a physicist do on a given day at the job?
If a physics major wants to learn more about programming than is required to compute complex formulas in Matlab then they should probably minor or double major in Comp Sci.
I majored in Math and the only programming I did as part of my degree was in Matlab. And that was in applied classes. I was taught just enough Matlab to do the assignments.
C/Java courses would have been a waste of time. A physics major's time is best spent learning how to use existing tools rather than wasting time learning low level languages so they can reinvent Matlab functionality.
Work Safe Porn
I am a experimental physics postdoc. Nearly everybody i know uses Matlab/Octave (theoreticians Mathematica). For simple (not heavy number crunching), matlab/octave is the de-facto way to exchange numerical programs. You get without much trouble results and a plot within a few minutes. And your students will learn what vectorization is, if they use matlab long enough. (if you can write you operation in a vectorized form, you can also do heavy number crunching). The documentation of matlab is excellent, and there are a lot of toolboxes which actually solve detail work (they have their price). You can use instrument control and DAQ toolboxes to control experiments directly. The matlab support is responsive and not arrogant at all (reporting bug is more a "thank you, we'll look at it" experience instead of a "what the fuck are you doing to trigger this bug? dont do it."). One big problem about matlab is that it spoils the programming style a little bit, but after all, these are physicists. The ones who can not program when they enter university will never learn it fully.
But scientists are going to need to do increasing amounts of computer use as computers pervade and inform the sciences, and that means doing their own programming, including writing real programs and writing scripts to bash input or output data for other programs. So they not only need to learn some syntax, and some scripting languages, they need to learn basic data structures, efficiency issues, debugging, and one of the most important lessons from my CS100 days - "Never trust input" "Ever" . That means they need at least two semesters of programming.
As scientists, even if they don't ever end up doing much more programming than feeding input to other packages and interpreting the output, they need to be able to do it in ways that will run in finite amounts of time and produce correct output - and learning not to trust input is as basic as learning not to connect the 110volt power to a 5 volt device or use fire near flammable liquids.
Bill Stewart
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Lacking <sarcasm> tags,
I assume that Physics majors at your university are required to take some level of math classes.
Excel is not sufficient instruction in programming any more than Algebra is sufficient instruction in math. So if someone suggests that all students need to learn is Excel, you may ask why the students are required to take more advanced math classes.
paintball
I once had a friend who built an instantiation of LIFE in Excel. Using macros and stored VB code in each cell, he was able to have every cell look up the context of every other adjoining cell during each generation, and the cells would turn on and off accordingly.
I'm not saying it can't be done in Excel. I'm saying just because you're versed in Excel, doesn't mean it's an expedient, or even appropriate tool for managing complex data structures, critical physical concepts, or large multidimensional problem sets.
For straight forward engineering and archtectual applications, it might well prove to be an excellent resource. It just seems a little like going next door via the polar route to try ways of making problems fit an inappropriate tool, vs finding an optimal tool in the first place and having it available for problems requiring greater flexibility, and less application related operational overhead.
Of course, when what you have is a hammer...
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
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.
I know this is going to confirm every bad stereotype the
Maybe next semester I'll do a research colloquium on SQL and basic database construction.
There's a perfect xkcd for my sig but I'm too lazy to look it up. sudo someone go find it.
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.
In theory, there's no difference between theory and practice; in practice there is.
I know Matlab has really low (or no) cost for educational use, but could you guys please switch over to GNU Octave (matlab clone) or SciLab/SciCos (similar but different & has a Simulink equivalent)? That way, after school people can keep using low cost tools in industry. My department spends a ton of money for those tools simply because the people who make decisions don't know about good/cheap alternatives. And guess where these guys learned Matlab. Yep - back in school.
Back in 1974-78, all students in the University of Illinois' College of Engineering were required to take at least a semester of introductory programming. That included the Physics majors because the Physics department was under the aegis of the College of Engineering (unlike Chemistry, Biology, etc.). That this particular science was placed in the engineering school always seemed like a really weird, but good placement.
That is all.
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Just like they say "Don't give a programmer a soldering iron", giving physicists something like C is probably giving them more than they need for most number crunching.
Engineering is the art of compromise.
If I mod you up, it doesn't necessarily mean I agree with what you've said, sorry.
Something like Pascal or Python would probably have been better for learning programming, but Fortran was/is the language for science and engineering.
I'm very glad I wasn't introduced to something as inconsistent and inelegant as VB(A) so early in the learning process. It's much harder to unlearn than it is to extend your knowledge.
"I've got more toys than Teruhisa Kitahara."
The first book I read on computers when I was 7 or 8 was sort of kids guide to the ZX Spectrum. I can't remember the name of it but it was a great book featuring the character "Speccy" and spent basically the first 4 pages explaining that nothing you could do would break speccy and not to be afraid to play around and do anything you liked which is probably the best advice you can give anyway trying to find there way around computers.
Of course Speccy was wrong and met a premature end when switching him on and yanking out his joystick at the same time caused him to smoke and shortly afterwards to die.