These chapters situate computing as a core scientific practice in physics and emphasize that, despite its centrality to physics research, its integration into undergraduate instruction remains highly uneven. Instead of advocating for a single model, language, or toolset, Caballero frames the volume as a col-lection of instructor narratives that foreground local goals, constraints, and institutional contexts. He highlights recurring themes across the chapters such as alignment between computational activities and disciplinary learning goals, instructor preparation, and curricular tradeoffs, and argues that mean-ingful integration of computing requires sustained, context-sensitive instructional design. In the con-cluding chapter, he synthesizes lessons from across the volume and points toward future directions, including the potential implications of generative AI for computational practice and physics instruc-tion.
Benjamin Zwickl, who also has a 20% appointment with the CCSE, contributed two chapters co-authored with Charles Lusignan and Aaron McGowan that focus on integrating computation into upper-division physics laboratory courses. Drawing on multi-year implementations at a single institu-tion, these chapters examine how computational work can be aligned with core laboratory learning goals such as modeling, experimental design, data analysis, and technical skill development.
The authors identify a set of instructional decisions that shape how computation functions in lab con-texts, including decisions that are specific to laboratories, such as how computational work is inter-leaved with hands-on experimentation and how students collaborate on code while working in lab pairs. Through detailed case studies from electronics, modern physics/advanced lab, and physical optics courses, the chapters illustrate how computation can open new experimental possibilities, sup-port richer modeling and uncertainty analysis, and enable more rapid cycles of exploration and sensemaking, while also discussing persistent challenges related to student workload and instruction-al support.
Associate Professor Tor Ole B. Odden contributed a chapter titled Teaching scientific writing using computational essays. In this chapter, he examines how computational essays (documents that inte-grate narrative text, equations, figures, and executable code, which have been heavily researched through the CCSE) can be used to create authentic opportunities for scientific writing in physics courses. The chapter introduces the core features of computational essays, surveys examples from physics instruction, and synthesizes findings from several published studies examining their use. Odden emphasizes how computational essays can be adapted to serve different instructional goals, such as conceptual explanation, model development, or scientific argumentation, while making stu-dents’ reasoning visible and closely aligning writing practices with disciplinary norms.
In all, this book serves as a concise, educator-facing synthesis of current perspectives and approaches to integrating computing into undergraduate physics instruction, and provides a set of concrete, re-search-informed examples that align closely with CCSE’s broader work on computational literacy and curriculum development.
- Danny Caballero is a professor at Michigan State University, and has a 20% appointment with the CCSE.
- Benjamin Zwickl is a Professor at Rochester Institute of Technology, and has a 20 % appointment with th CCSE.
- Tor Ole B. Odden is Accociate Professor at the CCSE.