TITLE: Workshop 3: Computational Thinking in Physics AUTHOR: Eugene Wallingford DATE: October 31, 2008 10:26 AM DESC: ----- BODY:

[A transcript of the SECANT 2008 workshop: Table of Contents]

As much as computation is now changing biology, it has already changed physics. Last year's workshop had a full complement of physicists and astronomers. In their minds, it is already clear that physicists must program -- even students learning intro physics. The question is, what problems do they face in bringing more computation to physics education? This panel session shared some physicists' experience in the trenches. Bruce Sherwood, the panel chair, set the stage: We used to be able to describe physics as theory, experiment, and the interplay between the two. This is no longer true, and it hasn't been for a while. Physics is now theory, experiment, simulation, and the interplay among the three! Yet this truth is not reflected in the undergraduate physics curriculum -- even at so-called "respectable schools". Rubin Landau described a systemic approach, a Computational Physics major he designed and implemented at Oregon State. He was motivated by what he saw as a turning inward of physics, efforts to cover all of the history of physics in the undergrad curriculum, with a focus on mathematics from the 19th century, and not looking outward to how physics is done today. (This CS educator felt immediate empathy for Landau's plight.) He noted his own embarrassment: computational physicists at major physics conferences who refuse to discuss their algorithms or the verification of their programs. This is simply not part of the culture of physics. Students learn by doing, so projects are key to this Computational Physics curriculum. Students use a "compiled language", which is Landau's way to distinguish programming in a CS-style language from Mathematica and Maple. For him, the key is to separate the program from engine; students need to see the program as an idea. Two languages is better, as that gives students a chance to generalize the issues at play in using computation for modeling. The OSU experience is that the political issues in changing the curriculum are much tougher to solve than the academic issues: the need for budget, the resistance of senior faculty, the reluctance of junior faculty to risk tenure, and so on. Landau closed by saying that, for physics-minded students, using computation in physics and then taking a CS course seems to work best. He likened this to the use of Feynman diagrams in grad school: students learn to calculate with them, and then learn the field theory behind them the next year. His undergrads have several "A-ha!" moments throughout CS1. I suspect that this approach would work for a lot of CS students, too, if we can get them to use computation. Media computation is one avenue I've seen work with some. Next up was Robert Swendsen, from Carnegie-Mellon. In the old days, physicists wrote programs because they did not know how to solve a problem analytically. Now, they compute to solve problems that no one knows how to solve analytically. (Mental note: It also lets them ask new questions.) The common problem many of us face: we tend to teach the course we took -- something of a recursion problem. (Mental note: Where is the base case? Aristotle, I suppose.) Swendsen identified a few other challenges. Students are used to looking at equations, though if they don't get as much from them as we do, but they have no experience looking at and reasoning about data. They struggle even with low-level issues such as accuracy in terms of the number of significant digits. Further, many students do not think that computational physics is "real" physics. To them, physics == equations. This is a cultural expectation across the sciences, a product of the few centuries of practice. Nor is it limited to students; people out in the world think of science as equations. Perhaps they pick this notion up in their high-school courses, or even in their college courses. I think that faculty in and out of the sciences share this misperception as well. The one exception is probably biology, which may account for part of its popularity as a major -- no math! no equations! I couldn't help but think of Bernard Chazelle's efforts to popularize the notion that the algorithm is the idiom of modern science. Listening to Swendsen, I also had an overriding sense of deja vu, back to when CS faculty across the country were trying to introduce OO thinking into the first-year CS curriculum. Curriculum change must share some essential commonalities due to human nature. Physicist Mark Haugan focused on a particular problem he sees: a lack of continuity across courses in the physics curriculum with respect to computation. Students may use computation in one course and then see no follow-through in their next courses. In his mind, students need to learn that computation is a medium for expressing ideas -- a theme regular readers of this blog will recognize. Mathematical equations are one medium, and programs are another. I think the key is that we need to discuss and work with problems where computation matters -- think Astrachan's Law -- problems for which the lack of computation would limit our ability to understand and solve the problem. This, too, echoes the OO experience in computer science education. We still face the issue that other courses and other professors will do things in a more traditional way. This is another theme common to both SECANT workshops: we need to help students feel so empowered by computation that they use it unbidden in their future courses. The Q-n-A session contained a wonderful thread on the idea of physics as a liberal art. One person reported a comment made by a student who had taken a computational physics course and then read a newspaper article on climate modeling:
Wow. Now I know what that means.
I can think of no higher "student learning outcome" we in computer science can have for our general education and introductory programming courses: Wow. Now I know what that means. There are many educated people who don't what "computer model" means. They don't understand what is reported in the news. There are many educated people reporting the news who don't understand the news they are reporting. That's not right. -----