Two approaches to teaching computation physics

skills by the time they complete their studies. However, the depth and range of skills needed varies considerably—even in a single discipline such as physics. Moreover, the interests , backgrounds, and abilities of students taking physics courses vary widely, whereas the number of teachers with scientific computing skills is often limited. Providing appropriate courses for such diverse student groups is thus a challenge. Computational physics provides exciting new teaching opportunities that can complement traditional methods of teaching in the lecture theater or experimental laboratory. Students usually realize that computing skills enhance their job prospects after graduation, and the hardware and software available for teaching such courses is relatively inexpensive and easy to maintain. I have taught computational physics courses at Trinity College Dublin (TCD) for approximately 10 years, initially through a theoretical physics degree class in which final-year students must solve a problem in nine weeks by using computational methods. More recently, I have directed a degree course in computational physics that started in 1997. The computational parts of the syllabus are mainly taught together with a computational chemistry degree program. Two important factors led to the course's introduction: a skills initiative by the Irish Higher Education Authority and a need to increase the level of training of potential postgraduate students for work in computational science. (The IHEA aims to increase the number of graduates from Irish universities with skills in information technology and provides extra funding for two additional staff members and equipment.) This article describes two approaches to teaching computational physics to these and other student groups. Two important uses of computing in an undergraduate physics syllabus are to teach students to combine their knowledge of mathematics with an understanding of its meaning in physical problems and to teach the emerging discipline known as computational physics. Numerical methods, programming, and the use of applications are obvious topics that should be part of any syllabus for a computational science or engineering degree course. However, not all student groups in any discipline need, or have the time, to take the full computational syllabus. Moreover, there is no single syllabus in computing suitable for all groups of physics students. Physics students usually learn mathematics and physics topics requiring mathematics in different years. Generally, they learn mathematics first, but when they're taught courses requiring an understanding of that mathematics in physics in later classes, they frequently have difficulty connecting the two. An …