Computation in Classical Mechanics

AIP Conference Proceedings, 2012

Students taking introductory physics are rarely exposed to computational modeling. In a one-semester large lecture introductory calculus-based mechanics course at Georgia Tech, students learned to solve physics problems using the VPython programming environment. During the term 1357 students in this course solved a suite of fourteen computational modeling homework questions delivered using an online commercial course management system. Their proficiency with computational modeling was evaluated in a proctored environment using a novel central force problem. The majority of students (60.4%) successfully completed the evaluation. Analysis of erroneous student-submitted programs indicated that a small set of student errors explained why most programs failed. We discuss the design and implementation of the computational modeling homework and evaluation, the results from the evaluation and the implications for instruction in computational modeling in introductory STEM courses.

Graduate Texts in Physics publishes core learning/teaching material for graduate-and advanced-level undergraduate courses on topics of current and emerging fields within physics, both pure and applied. These textbooks serve students at the MS-or PhD-level and their instructors as comprehensive sources of principles, definitions, derivations, experiments and applications (as relevant) for their mastery and teaching, respectively. International in scope and relevance, the textbooks correspond to course syllabi sufficiently to serve as required reading. Their didactic style, comprehensiveness and coverage of fundamental material also make them suitable as introductions or references for scientists entering, or requiring timely knowledge of, a research field.

Computing in Science and Engineering, 2006

Austin Peay State University's Department of Physics and Astronomy has reinvigorated its physics program by adding a required computational methods class and small computational components to classes across its curriculum. A front-to-back problem management approach has required a change in the way the department assesses students' performance

The multidisciplinary study of computer science in science education over the past quarter of a century has led to the articulation of important new conceptual perspectives and methodologies that are of value both to researchers in these fields as well as to teachers and students. This article describes progress and changes in developing and implementing of education materials in computational physics education; particularly at University of Delhi. This explains the time series analysis of computational interest of students for a three-year undergraduate degree program leading to a Bachelor's and two year postgraduate degree program leading to a Master's degree in Physics. Finally, some remarks are made about implementation issues and scope of computational physics study at present.

A national survey of physics faculty was conducted to investigate the prevalence and nature of computational instruction in physics courses across the United States. 1246 faculty from 357 unique institutions responded to the survey. The results suggest that more faculty have some form of computational teaching experience than a decade ago, but it appears that this experience does not necessarily translate to computational instruction in undergraduate students' formal course work. Further, we find that formal programs in computational physics are absent from most departments. A majority of faculty do report using computation on homework and in projects, but few report using computation with interactive engagement methods in the classroom or on exams. Specific factors that underlie these results are the subject of future work, but we do find that there is a variation on the reported experience with computation and the highest degree that students can earn at the surveyed institutions.

Physics Today, 1998

American Journal of Physics, 1993

Since 1983, the Maryland University Project in Physics and Educational Technology (M.U.P.P.E.T.) has been investigating the implication of including student programming in an introductory physics course for physics majors. Many significant changes can result. One can rearrange some content to be more physically appropriate, include more realistic problems, and introduce some contemporary topics. We also find that one can begin training the student in professional research-related skills at an earlier stage than is traditional. We learned that the inclusion of carefully considered computer content requires an increased emphasis on qualitative and analytic thinking. ________________________________________________________________________________________________________________ Redish and Wilson 2 Student Programming in the Introductory Course A. Problems with the traditional physics curriculum The physics curriculum as presently taught was developed over thirty years ago. 2 Although that change was a significant advance at the time, the curriculum has failed to develop since then. This might not be a problem if physics were a static field. It is not. In the past thirty years we have seen an explosion of new understanding and power in a variety of subfields of physics ranging in scale from the substructure of the proton to the clustering of galaxies. There have even been major breakthroughs in fields long thought to be understood. Current developments in Newtonian mechanics are evolving into a theory of non-linear systems and chaotic behavior that may produce profound changes in the way we think about physics.

The Physics Teacher, 2019

Computers have revolutionized physics and engineering because they have made it easy to analyze differential equation models of physical processes. This paper describes a high school or introductory university course in scientific programming that introduces the computer revolution into the physics curriculum at the beginning. The laws of physics are written as differential equations, and differential equations are the point of connection between the real world and the mathematical world. Yet because differential equations are difficult or impossible to solve analytically they are given short shrift in the educational system. At the (nearby to me) Univ. of South Florida, physics majors do not study differential equations until their third year at the university ! Differential equations are used descriptively to write laws of physics and to model physical processes, and analytically, that is, a process can be analyzed by solving the differential equations. This course introduces the descriptive use of differential equations at the beginning of the physics curriculum, starting in high school. In the first one-hour lecture, Euler’s method is presented and used to compute a solution to the analytically unsolvable two-body problem. In the remainder of the course a variety of physical systems are modeled and analyzed to demonstrate the remarkable power and wide range of applicability of the method.

Arxiv preprint arXiv:0904.3960, 2009

The paper describes two general problems encountered in computational assignments at the in-troductory level. First, novice students often treat computer code as almost magic incantations, and like novices in many fields, have trouble creating new algorithms or ...

Computers in Physics, 1998

Applying computer technology is simply finding the right wrench to pound in the correct screw. -Anonymous I n this article we describe the Web-enhanced computa- tional-physics course and textbook we developed in the Physics Department at Oregon State University. The goal of our efforts is to provide an improved medium for teaching physics and for incorporating some basics of high-performance computing into university curricula. The improvement comes by using the computer as a tool for amplifying the student's cognitive and reasoning abilities, and by using the World Wide Web to provide what is otherwise too difficult to provide. The course is aimed at upper-division undergraduates in science and engineering; it also benefits beginning graduate students. The book, Computational Physics, Problem Solving with Computers, 1 contains more than enough projects for a twoquarter course and is enhanced by links to free, interactive Web tutorials containing sonifications, animations, Java applets, and research-based codes. To appreciate the Web enhancements, the reader is encouraged to follow the links given as references or to read the Web version of this article at . We developed the course and wrote the text over a sevenyear period with support from the U.S. Department of Energy, the U.S. National Science Foundation (NSF), and the IBM Corp. Our Web materials were developed over the last three years with support from the Undergraduate Computational Engineering and Science project (UCES) 2 and the Northwest Alliance for Computational Science and Engineering (NACSE), 4 an NSF Metacenter Regional Alliance. To supplement our materials, we have also included links to Webenhanced instructional materials at Syracuse University 5 and the Shodor Foundation. Our package of educational materials is not what we planned to write 10 years ago when we started the discussions that led to our Computational Physics course. We thought then that the Computer Science Department would teach students what they needed to know about computers, and the Mathematics Department would teach them what they needed to know about numerical methods and statistics. We would teach them how to apply mathematical and computer knowledge to doing physics problems on computers. However, we have found that the students who take our Computational Physics course generally do not bring knowledge of these other disciplines with them. Many of the materials we have developed would, in a more perfect world, be taught and written by experts in other fields. It is probably for the better that we could not follow our original plans. On the one hand, if physicists who conduct research with computers tell students they need to know "this" in computer science and "that" in mathematics, students get the message that the knowledge they acquire in their other courses is useful. On the other hand, it easier for students to understand interdisciplinary subject matter and to master complex systems when they study physics, mathematics, and computer science concepts in the language and from the perspective of a scientist focused on problem solving.