Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2008.10931

Introducing students to research codes: A short course on solving partial differential equations in Python

Pavan Inguva·Vijesh J. Bhute·Thomas N. H. Cheng·Pierre J. Walker
View original source ↗Read source document ↗Export metadata ↓

Abstract

Recent releases of open-source research codes and solvers for numerically solving partial differential equations in Python present a great opportunity for educators to integrate these codes into the classroom in a variety of ways. The ease with which a problem can be implemented and solved using these codes reduce the barrier to entry for users. We demonstrate how one of these codes,FiPy, can be introduced to students through a short course using progression as the guiding philosophy. Four exercises of increasing complexity were developed. Basic concepts from more advanced numerical methods courses are also introduced at appropriate points. To further engage students, we demonstrate how an open research problem can be readily implemented and also incorporate the use of ParaView to post-process their results. Student engagement and learning outcomes were evaluated through a pre and post-course survey and a focus group discussion. Students broadly found the course to be engaging and useful with the ability to easily visualise the solution to PDEs being greatly valued. Due to the introductory nature of the course, due care in terms of set-up and the design of learning activities during the course is essential. This course, if integrated with appropriate level of support, can encourage students to use the provided codes and improve their understanding of concepts used in numerical analysis and PDEs.

Explore related subjects

physics.ed-phcs.NAmath.NA

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Pavan Inguva, Vijesh J. Bhute, Thomas N. H. Cheng, Pierre J. Walker. 2020-08-26. Introducing students to research codes: A short course on solving partial differential equations in Python. https://arxiv.org/abs/2008.10931

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Johann Bernoulli's analysis of elastic collisions (a teaching sequence to introduce the dynamic law thereby inspired)

In order to explain an elastic collision, Johann Bernoulli considered two bodies connected by a spring. Motion is defined as a succession of states of rest. Then, considering the spring to be a lever with a body at each extremity, the laws of equilibrium imply that `motion' is described by the time variation of the (common) quantity of motion of the bodies; the dynamic law is thus deduced. This inspires a teaching sequence to introduce the dynamic law (in one dimension) in introductory physics course; we call it ``bernoullian sequence''.

physics.ed-ph↗
arXiv2026

Design and Initial Evaluation of a Photovoltaics-focused Course-based Undergraduate Research Experience in Physics

Traditional physics laboratory courses often focus on experiments with well-known results, limiting students' engagement in authentic scientific practices. Course-based undergraduate research experiences (CUREs), where students engage in real research with unknown outcomes, have been shown to support positive student outcomes, such as increased self-efficacy, persistence, and engagement in scientific practices. However, discipline-specific studies of CUREs in physics remain limited. We describe the development, structure, and initial implementation of a photovoltaics-focused CURE in a second-year undergraduate physics laboratory course at the University of Colorado Boulder. To examine how students experienced the course, we analyzed end-of-semester reflection assignments using the five CURE components (i.e., scientific practices, discovery, relevance, collaboration, and iteration), as well as established dimensions of research authenticity, as analytic frameworks. Students described experiences associated with all five CURE components, with collaboration, relevance, and scientific practices appearing most prominently in their reflections. Students also associated authentic research with meaningful scientific contribution, engagement in authentic scientific practices, and navigating the uncertainty and setbacks inherent in research, although fewer explicitly identified themselves as researchers or scientists. A subset of students additionally connected the course to their immediate thinking about future academic and professional pathways. This work contributes both a discipline-specific model for implementing CUREs in experimental physics laboratory courses and provides insight into how students interpret and experience authentic research within this course context.

physics.ed-ph↗
arXiv2026

A Workshop Series for Effective Use of AI in Uncertain Times: Building a Physics Faculty Learning Community

Generative AI tools are being widely taken up by students in their physics courses and beyond, often before instructors and institutions can develop policies and effective approaches for the use of these tools. Building on a framework for change in the era of AI, we developed and implemented a faculty learning community to help a university physics department address these challenges collectively. Over six biweekly sessions, faculty worked through course policies, classroom conversations about AI, AI-integrated coursework tasks, and assessment. Each session shared a common structure: we presented local data and department-sourced materials, tested them in small groups, and discussed them together, emphasizing durable pedagogical approaches over specific tools and platforms, and leading with evidence of students' own AI use. The series produced a shared, evolving repository of resources for faculty to draw on. This workshop provides an adaptable, theoretically informed model for a faculty learning community that departments can build on.

physics.ed-ph↗