Concerning physics simulations: There is a long history going back over 30 years of physicists writing simulations of physical phenomena for students to play with. I claim that mostly this by itself has had little pedagogical value. The Ph.D. physicist learned a lot from the simulation, but the introductory student didn't have the background to ask or address interesting questions using the tool. One exception to this gloomy assessment is the situation where the instructor assigns carefully articulated tasks for students to work on using the simulation as a tool. It is attractive to imagine that just sitting the student down in front of a wonderful simulation will lead to learning, but in most cases it doesn't. I also want to draw people's attention to the fact that there already exists a widely used general simulation package, called "Interactive Physics." Using a graphical interface, an instructor can set up something as complicated as a tumbling tower of blocks, and instrument the simulation with graphs and meters to display velocity, energy, etc. There is a player that students can use to run these instructor-prepared simulations. There is a third-party cooperative effort to share setups. So all of this already exists. Many physics teachers have gone beyond the gee-whiz to incorporate this tool into their teaching in a sensible and thoughtful way. An important distinction can be made between simulations and visualizations. A simulation is always somewhat suspect, because it necessarily leaves out some aspects of the real world. This is why many instructors appropriately reject replacing lab experiences with simulations. Visualizations normally are not subject to this problem. For example, my colleague Ruth Chabay has produced QuickTime movies showing electric and magnetic fields in three-dimensional space. We use these movies as lecture-demonstration tools to help students visualize the 3D aspects of fields. There is no issue here of inadequacy of the model, because the movies don't simulate physical processes; rather they teach about the vector representation used by physicists to reason about fields. You can see or download these movies at http://cil.andrew.cmu.edu/emi.html A rather different use of Python that interests our group is to have students write their own computer models from scratch, rather than merely manipulating parameters in someone else's computer model. Currently in our modern mechanics curriculum (and to a lesser extent in our electricity and magnetism curriculum) we have students write programs in our cT programming language, with no black boxes. Many of the programs that the students write are numerical integrations of Newton's second law. Here is the guts of a typical student-written program for integrating the equations of motion for a planet going around a stationary star (initial conditions would be set by the student's program before entering this loop): while 1: r = sqrt(x**2+y**2) F = G*M*m/r**2 Fx = F*x/r Fy = F*y/r px = px+Fx*dt py = py+Fy*dt x = x+(px/m)*dt y = y+(py/m)*dt plot a disk at x,y This is the simplest possible, crude integration algorithm. We have students progressively cut the step size dt until the behavior doesn't change. Today's computers are fast enough that this is adequate for our purposes: we don't have to teach fancy Runge-Kutta techniques. In merely two 50-minute periods we teach the students a subset of cT adequate for writing these and related programs, and they immediately get a spacecraft to the Moon, followed by orbits, spring-mass motion, etc., all with 2D graphical output in the form of visualizing the actual motion as well as graphs of energy, etc. We can't afford to spend more than two periods teaching the language, because this is a physics course, not a programming or computer science course. A sizable minority of our freshman college science students have never written a computer program before, and many of the others have never written a program with graphics output. The goal, largely met, is to teach students the value of computer modeling, and to fix clearly in their minds the fundamental nature of the "Newtonian synthesis" -- that knowledge of positions and momenta at this moment let you predict new positions and momenta a moment dt into the future, and iterate. This view of Newtonian mechanics does not come across in the traditional mechanics curriculum, which is dominated by known motions (blocks sliding down inclines) from which something about the forces is inferred, so that open-ended prediction of motion into the future plays a minor role. We have glimpsed the possibilities of teaching Python rather than cT in those two 50-minute periods, with the possibility of students getting 3D output for free! Python, like cT, has a simple surface syntax, without lots of extra semicolons, braces, etc., and with meaningful indentation. As an existence proof we have written Python programs that look sufficiently similar to the cT programs that our students have successfully written that we can be confident that brief instruction would be sufficient to get them into computer modeling right away. Python offers us three important things that we can't get from cT as it stands, and we don't feel that cT is an adequate base to get there from here. The first is 3D graphics. Dave Scherer, a computer science sophomore at Carnegie Mellon, is developing an engine that lives as a separate thread from the student's Python program and continually (many times a second) updates a picture of the current positions of objects whose positions the student is calculating (he uses OpenGL as the underlying engine). The effect is that the student would write a purely computational program, with no graphics statements, and for free get an animated 3d display. And also for free, the graphics window lets you move the mouse to view the scene from any position. The second thing Python offers is object orientation. The student creates objects such as sun = sphere() and earth = sphere() and then computes their motions. This doesn't necessarily lead into teaching the student to create classes, but it takes some first steps in the student's education about OOP, because the student thinks about the display objects as objects, for which we have some evidence that this is advantageous. In contrast, in cT an animation is produced by erasing a disk here and plotting a disk there, and the disk is just pixels on the screen, not an object that cT remembers anything about. Students are sometimes puzzled that they can't change a position merely by changing x and y, or that a ball plows through a wall on the screen because those pixels aren't being considered by anyone. The third thing Python offers is the possibility of writing vector operations as single statements rather than as two (or three) separate statements. We probably wouldn't start students this way, but at some point during the course it may be appropriate to have them write something like earth.position = earth.position + (earth.momentum/m)*dt rather than writing earth.x = earth.x + (earth.px/m)*dt earth.y = earth.y + (earth.py/m)*dt earth.z = earth.z + (earth.pz/m)*dt The possible value in this is that it is a powerful idea to think of vectors as single entities, not merely as two (or three) separate quantities. OUR GROUP In alphabetic order, let me introduce our Carnegie Mellon group. We think we can make a real contribution to one aspect of CP4E, that of enabling students in a physics course to write their own 3D graphics programs. We are studying a variety of issues that must be addressed to make Python plus 3D viable for science students who have not programmed before. These issues include making more robust and easy to use an integrated development environment and the installation procedure, as well as the purely 3D issues. We realize that if we address these problems we may serve wider needs than our own, but we find it useful to take a very narrow focus (the novice-programmer physics students) in order to make progress. I should mention for completeness that our focus is rather different from that of Randy Pausch at Carnegie Mellon. In Pausch's course on creating virtual worlds, students use Python to control 3D models. Our focus is rather on physics students writing simulations in the context of 3D scientific visualization. David Andersen <dma+@andrew.cmu.edu> System designer in CIL (Center for Innovation in Learning). Wrote much of the system software for the PLATO computer-based education system at the University of Illinois in the 70's and 80's, including major contributions to the TUTOR authoring language. Initiator of the MicroTutor language (1977). For the last ten years has been further developing and maintaining the cT programming language (which is a granddaughter of TUTOR and a daughter of MicroTutor). Extensive cross-platform experience, including Windows, Macintosh, and Unix/Linux. Ruth Chabay <rchabay+@andrew.cmu.edu> Ph.D. physical chemist, senior research scientist in CIL and Department of Physics. Contributed to the PLATO system software in the 70's. Has written award-winning and commercial educational software in chemistry and physics, including 3D visualizations of electric and magnetic fields, and of the ball-and-spring model of a solid. Co-author with Bruce Sherwood of a new textbook for introductory university physics incorporating computer modeling. Devised a very rapid introduction of computer modeling for physics students. Regularly teaches physics courses at Carnegie Mellon in which computing plays a major role. Ari Heitner <aheitner@andrew.cmu.edu> Ian Peters <itp@gnu.org> David R Scherer <dscherer@andrew.cmu.edu> Ari, Ian, and Dave are sophomores at Carnegie Mellon. Ari and Dave are majoring in computer science, and Ian is a double major in physics and computer science. They all come from the excellent Thomas Jefferson High School in Alexandria VA. Dave Scherer is the person who introduced Python to us and proposed building a novice 3D graphics computing environment on top of Python. Dave and Ari were members of the TJ team that built "Fire and Darkness," a 3D computer game that won the national prize last year at the First Independent Games Festival. All three of the students were in our physics course last year and had experience with student computer modeling of physical phenomena. Dave is rapidly developing a module that runs in parallel to Python, updating the screen with often enough to give smooth 3D animations, with user mouse actions enabling change of point of view of the scene. His module talks to OpenGL. Programs using Dave's module don't make explicit graphics calls but simply update screen positions of objects such as spheres and curves. Bruce Sherwood <bas@andrew.cmu.edu> Ph.D. physicist, a principal research scientist in CIL and professor in the Department of Physics. Contributed to the PLATO system software in the 70's, including in particular contributions to the TUTOR and MicroTutor languages. Has written award-winning and commercial educational software in physics. Initiated the development of the cT programming language. Has written book and on-line software documentation. Co-author with Ruth Chabay of a new textbook for introductory university physics incorporating computer modeling. Regularly teaches physics courses at Carnegie Mellon in which computing plays a major role.