Developing a project-based computational physics course grounded in expert practice

Abstract

We describe a project-based computational physics course developed using a backwards course design approach. From an initial competency-based model of problem solving in computational physics, we interviewed faculty who use these tools in their own research to determine indicators of expert practice. From these, a rubric was formulated that enabled us to design a course intended to allow students to learn these skills. We also report an initial implementation of the course and, by having the interviewees regrade student work, show that students acquired many of the expert practices identified.

Computational Programming as a Tool in the Teaching of Electromagnetism in Engineering Courses: Improving the Notion of Field

“…In this sense, the two laboratory projects that we presented sought to be a cognitive support for the students, as mentioned by Azmi et al [15]. From the analysis of the questionnaires, the answers to the last three questions, suggest that the computational programming is, in the opinion of the students, a good strategy to overcome the difficulties described above as expected [11,12]. This positive aspect of programming strategies is more pronounced in the question of understanding the notion of field given the mode and the mean deviation we obtained in questions 5 and 7.…”

“…There are many works developed in this decade [4][5][6][7][8][9][10][11][12]. With the increasing development of the graphic potentialities associated with the various programming languages, simulation and modelling activities for the teaching of physics become increasingly appealing, enhancing the understanding/visualization of the physical phenomena.…”

Comparison of student and instructor reasons for using computation

“…These students described professionally and personally important reasons for using computation. Collectively, the students identified many reasons for using computation consistent with those expressed by the physics community [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]: accuracy, aiding learning, conceptual and mathematical accessibility, data collection and analysis, efficiency, experimental control, manipulation of variables, personal applications, sense-making, simulation, and visualization.…”

“…To study this issue, we consider computation through the Communities of Practice (COP) framework [23][24][25][26], which is particularly useful when studying computation in physics education [3,5,27,28]. The community of physicists can be considered on the scale of a research group, a class, a department, or a discipline.…”

“…The use of computers to study, solve, and visualize physics problems is valuable in undergraduate physics education. Computation helps prepare students for careers in STEM research and industry [1][2][3][4][5] and enables students to pursue creative solutions [6,7], engage in sense-making [8][9][10], and test model-based predictions in analytically intractable problems [2,7,[11][12][13][14][15][16]. Although computation is widely adopted in university physics programs [17] and there is a consensus that computational experience is beneficial for students, research is needed to address challenges that arise when integrating computation, such as student motivation [18,19] and "making room" in the curriculum [2,14,19].…”