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Introduction to Volume 16 Issue 2
David Joinerpp. 1–1
A brief introduction to this issue of the Journal of Computational Science Education from the editor.
Volume 16 Issue 2 — November 2025
Contents
Scaling Instructional Workflows in Data Science Education using JupyterHub and Otter-Grader
Sai Annapragadapp. 2–4
https://doi.org/10.22369/issn.2153-4136/16/2/1BibTeX
@article{jocse-16-2-1,
author={Sai Annapragada},
title={Scaling Instructional Workflows in Data Science Education using JupyterHub and Otter-Grader},
journal={The Journal of Computational Science Education},
year=2025,
month=nov,
volume=16,
issue=2,
pages={2--4},
doi={https://doi.org/10.22369/issn.2153-4136/16/2/1}
}
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At the University of California, Merced (UCM), an instructional workflow was adopted to support the teaching of data science at scale. This workflow integrated JupyterHub, Otter-Grader, and GitHub to facilitate browser-based notebook execution, simplify assignment distribution, and automate grading. Initially built around a shared-folder model—--where instructors placed course materials in a shared---readwrite directory that automatically appeared as a read-only shared directory for all students—--the system transitioned to a GitHub-based setup using nbgitpuller. This shift allowed instructors to distribute assignments and course materials through direct links, removing the need for students to navigate the shared folder manually. By doing this, the need for admin privileges was removed, reducing the risk of accidental deletion of course content from the shared read-write folder. This paper presents our instructional strategy, key challenges addressed, implementation experience, and insights for educational institutions seeking to adopt similar models.
Coding through Storytelling: Narrative Reasoning and Software Engineering Education
S. Charlie Dey, Jeaime H. Powell, Victor Eijkhout, Joshua Freeze, and Susan Lindseypp. 5–9
https://doi.org/10.22369/issn.2153-4136/16/2/2BibTeX
@article{jocse-16-2-2,
author={S. Charlie Dey and Jeaime H. Powell and Victor Eijkhout and Joshua Freeze and Susan Lindsey},
title={Coding through Storytelling: Narrative Reasoning and Software Engineering Education},
journal={The Journal of Computational Science Education},
year=2025,
month=nov,
volume=16,
issue=2,
pages={5--9},
doi={https://doi.org/10.22369/issn.2153-4136/16/2/2}
}
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To become a successful software engineer, technical competence alone is not enough. Students must learn to reason about their code, articulate their intentions, and locate errors with clarity and confidence. This paper introduces a pedagogical approach rooted in the metaphor of "telling a story." By encouraging students to narrate their code—identifying protagonists (variables), plotlines (control flow), and conclusions (outputs), we promote a practice of self-explanation that strengthens metacognitive awareness and debugging skills. Drawing from experiences in the classroom, we show how storytelling helps students pinpoint bugs, communicate intent, and ultimately write more understandable code. We connect these practices with existing research on metacognition, program comprehension, and human-centered computing, and describe how this narrative approach provides a scalable, inclusive, and transferable tool for future computational engineers and scientists.
Classroom Applications of Question Formulation to Support Problem-Solving in Computer Science
James Quinlan and Michael Todd Edwardspp. 10–15
https://doi.org/10.22369/issn.2153-4136/16/2/3BibTeX
@article{jocse-16-2-3,
author={James Quinlan and Michael Todd Edwards},
title={Classroom Applications of Question Formulation to Support Problem-Solving in Computer Science},
journal={The Journal of Computational Science Education},
year=2025,
month=nov,
volume=16,
issue=2,
pages={10--15},
doi={https://doi.org/10.22369/issn.2153-4136/16/2/3}
}
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Questions are an integral part of the teaching and learning process. As students ask questions, they explore complex ideas, challenge assumptions, and confront contradictions. Too often, however, students do not know what questions to ask. They are hesitant to reveal their misunderstandings in front of their classmates. Other students don't participate because they are not invested in the course content. This paper presents the Question Formulation Technique (QFT), a teaching method designed to provide computer science students with targeted instruction on question-posing. As students learn to ask better questions, they become more confident in their abilities as learners. In this experience report, we provide a frame-work and implementation process, highlighting key steps and potential outcomes. Drawing on instructor observations, we report improvements in student engagement and critical thinking, while also discussing the limitations of anecdotal evidence and outlining directions for future research. Through in-class examples, we discuss the method's strengths and limitations while offering sample prompts that can be adapted for classroom use.
Enhancing HPC Education through Virtual Cluster Administration and Benchmarking
Charles Ross Lindsey, Jeffrey Valdez, Aaron Jezghani, Will Powell, and Richard Vuducpp. 16–21
https://doi.org/10.22369/issn.2153-4136/16/2/4BibTeX
@article{jocse-16-2-4,
author={Charles Ross Lindsey and Jeffrey Valdez and Aaron Jezghani and Will Powell and Richard Vuduc},
title={Enhancing HPC Education through Virtual Cluster Administration and Benchmarking},
journal={The Journal of Computational Science Education},
year=2025,
month=nov,
volume=16,
issue=2,
pages={16--21},
doi={https://doi.org/10.22369/issn.2153-4136/16/2/4}
}
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The rapid advancement in high-performance computing (HPC) poses significant challenges for the HPC community. Current HPC training approaches often are too generic or too customized to local environments, limiting their applicability and impact. Often, these shortcomings are due to the limited accessibility, excessive cost, and specialized support necessary to provide HPC environments for teaching. To address these challenges, we introduce Virtual Cluster, a hardware-agnostic platform designed to provide an easy-to-configure, generalizable, and scalable approach to HPC system management for training and education in computational research alongside production system configurations. We implemented this platform in a virtually integrated project (VIP) course aimed at training undergraduates for HPC cluster building. Drawing from our experience from the VIP course, we advocate for the integration of more comprehensive educational and training approaches, such as HPC Virtual Cluster, to better support HPC.
Facilitating Academic Research with FPGA Support in a University Data Center
Jeevesh Choudhury, Thomas Jennewein, and Gil Speyerpp. 22–28
https://doi.org/10.22369/issn.2153-4136/16/2/5BibTeX
@article{jocse-16-2-5,
author={Jeevesh Choudhury and Thomas Jennewein and Gil Speyer},
title={Facilitating Academic Research with FPGA Support in a University Data Center},
journal={The Journal of Computational Science Education},
year=2025,
month=nov,
volume=16,
issue=2,
pages={22--28},
doi={https://doi.org/10.22369/issn.2153-4136/16/2/5}
}
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Field Programmable Gate Arrays (FPGAs) offer a practical solution that balances computational power with energy efficiency, which could address the growing demand for sustainable high-performance computing (HPC). Moreover, because they can be reconfigured and optimized for specific applications, FPGAs open up numerous possibilities for adaptive, high-performance workloads. However, the substantial expertise required to deploy FPGA designs has traditionally been daunting, requiring proficiency in Hardware Description Languages (HDL) such as SystemVerilog or VHDL. To address this accessibility barrier, the field has shifted toward high-level synthesis (HLS), which allows developers to program FPGAs using familiar languages like C++ and Python---mirroring the evolution seen in GPU programming.<r> In this paper, the resources available on the Sol HPC cluster at Arizona State University (ASU) and the strategies employed to support and encourage researchers and instructors working with these nodes are examined. The practical challenges of using FPGAs, the integration of tools and libraries in the development workflow, and efforts to lower the expertise threshold required for effective use are explored. By sharing this experience, the aim is to contribute to the growing body of knowledge around accessible and sustainable FPGA development in HPC environments.
A Novel 3D Recurrent R-CNN for Medical Imaging Feature Detection: A Case Study for Coronary Calcium Detection
Vikas Sarvasya, Robert Gotwals, and Liam Butlerpp. 29–39
https://doi.org/10.22369/issn.2153-4136/16/2/6BibTeX
@article{jocse-16-2-6,
author={Vikas Sarvasya and Robert Gotwals and Liam Butler},
title={A Novel 3D Recurrent R-CNN for Medical Imaging Feature Detection: A Case Study for Coronary Calcium Detection},
journal={The Journal of Computational Science Education},
year=2025,
month=nov,
volume=16,
issue=2,
pages={29--39},
doi={https://doi.org/10.22369/issn.2153-4136/16/2/6}
}
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This student research project presents a pioneering network that utilizes specialized algorithms and propagation techniques to accurately identify small, dynamic structures in non-gated chest CT scans. The model's ability to provide reliable calcium scores enhances the clinical utility of chest CT scans, offering a promising tool for improving the diagnosis of coronary artery disease and optimizing the management of cardiac disease risk.