The Journal of Open Source Education is an educator friendly journal for publishing open-source educational materials and software.
JOSE, pronounced [hoe-zay], is a sibling journal to the Journal of Open Source Software (JOSS), which publishes open-source research software. JOSE relies on the journal management infrastructure and tools developed for JOSS.
JOSE publishes two types of articles that describe:
Currently, academia lacks a mechanism for crediting efforts to develop software for assisting teaching and learning or open-source educational content and materials. As a result, beyond personal motivation, there is little incentive to develop and share such material.
The Journal of Open Source Education (JOSE) is a scholarly journal with a formal peer review process designed to improve the quality of the software or content submitted. Upon acceptance into JOSE, a CrossRef DOI is minted and we list your paper on the JOSE website.
This is an initiative led directly by the Editorial Board on a purely volunteer basis. There is no publisher seeking revenue through the journal. JOSE runs on the efforts of the editors, authors, and reviewers, to communicate scholarly work to the open-source community without intermediaries.
"Open-source" implies that there are source files that are converted and rendered into a final learner-presentable form. Examples include Jupyter notebooks or plaintext/markup language documents like LaTeX, Markdown, ReStructuredText, AsciiDoc, and R Markdown. These documents should contain the lesson content and be designed to be reusable by other instructors. Lastly, the course content should make use of computation for learning with embedded or associated code snippets/programs.
We do not mean openly available slides, lecture notes, or YouTube videos, though these may be acceptable as supplementary materials. In addition, course syllabi by themselves are not suitable for submission (Syllabus may be more appropriate).
tl;dr: your course or lesson content must contain or use code to teach. We are not focused exclusively on learning to code, but coding to learn.
Open-source software that serves as educational technology; examples include (but are not limited to) alternatives to learning management systems, autograders, cloud systems for lesson delivery, student collaboration tools. For these tools, peer review will follow a similar process as JOSS.
We consider submissions from all areas of academia, although our computational focus may result in more natural submissions from STEM fields—but all are welcome!
Submissions must be "feature complete" to the extent that another educator could adopt, reuse, and/or extend for their purposes.
The ideal submission size is a course module, although entire courses are also acceptable.
JOSE submissions must:
JOSE submissions must be fully open, under the Open Definition. This means that any text content or graphical objects should be under a Creative Commons license (ideally CC-BY) and code components should be under an OSI-approved license.
Computational learning modules should be complete and immediately usable for self-learning or adoption by other instructors. They should make a clear contribution to teaching and learning of any subject, supported by computing. JOSE is not focused in OER for "learning to code" as much as "coding to learn."
Software submissions should make a clear contribution to the available open-source software that supports teaching and learning, or makes an educational process better (e.g., faster, easier, simpler). Examples include software to auto-grade student work, learning management systems, and student collaboration frameworks. Software should be feature-complete (no half-baked solutions).
Professor of Mechanical and Aerospace Engineering at the George Washington University, leading a research group in computational fluid dynamics, computational physics and high-performance computing. Member of the Board for NumFOCUS, a non-profit in support of open-source scientific software.
Mechanical engineer in the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University. Computational researcher in combustion, fluid dynamics, and chemical kinetics, with an interest in numerical methods and GPU computing strategies.
Ian Hawke is an Associate Professor in Applied Mathematics at the University of Southampton. His research focuses on relativistic fluid dynamics to compute the gravitational waves from neutron star mergers. He teaches numerical methods and mathematical computing across STEM subjects, with particular interest in postgraduate training.
Kathryn Huff is an Assistant Professor in Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign. Her research focuses on modeling and simulation of advanced nuclear reactors and fuel cycles. She also advocates for best practices in open, reproducible scientific computing.
Attending surgeon at Groote Schuur Hospital, Head of Postgradute Surgical Research. and Head of Surgical Education in the Department of Surgery at The University of Cape Town. He serves as the Health Sciences Faculty member on the University Senate Committee on online education. His research and educational passions include machine learning and data science, open science, open source software, and open educational resource development.
Erin McKiernan is a professor in the Department of Physics, Biomedical Physics Program at the National Autonomous University of Mexico, specializing in experimental and theoretical neuroscience and cellular biophysics. She teaches several courses, including biochemistry, cellular and molecular biology, and human physiology. She is currently developing electrophysiology laboratory practicals as open educational resources.
Jason K. Moore is an assistant professor of BioMechanical Engineering at Delft University of Technology, where he leads the Bicycle Lab and teaches multibody dynamics and engineering computation. He is active in the Scientific Python community where he is a core developer of the SymPy and PyDy projects.
Shannon Quinn is an Assistant Professor at the University of Georgia, jointly appointed in the Departments of Computer Science and Cellular Biology. His research focuses on modeling diseases at the cellular level using a variety of imaging and machine learning techniques. He also advocates for best practices in open and reproducible research and education.
Charles is a Clinical Associate Professor in the School of Information at the University of Michigan. He also works on developing standards for teaching and learning technology. Previously, he was the Executive Director of the Sakai Foundation and the Chief Architect of the Sakai Project. He has written several books including Using the Google App Engine, Python for Informatics, High Performance Computing, and Sakai: Free as in Freedom.
Rachel Thomas is a is a deep learning researcher, and co-founder of fast.ai, which offers free courses in deep learning, a software library and conducts research in AI. She is Director of Center for Applied Data Ethics at the University of San Francisco Data Institute, has developed many popular courses, and is a prolific speaker and writer.
Assistant Professor of Teaching in the Department of Statistics and Co-Director for the Master of Data Science program (Vancouver Option) at the University of British Columbia. She develops curriculum and teaches on responsible application of data science, collaborative software development and creating R and Python packages using modern tools and workflows. Co-author of two open textbooks: Data Science: A First Introduction and Python Packages.
Bryan is teaching faculty and the Director of Undergraduate Studies in Mechanical Engineering at the University of Connecticut. He specializes in all areas related to Mechanical Engineering, especially thermodynamics, combustion, chemistry, and fluids. Bryan is interested in applications of Jupyter Notebooks to educational materials. He is also the co-lead developer of Cantera, https://cantera.org, the largest open-source software package for thermodynamics, chemical kinetics, and transport calculations.
Jason Williams is Assistant Director of External Collaborations at Cold Spring Harbor Laboratory’s DNA Learning Center. He has been the Education, Outreach, and Training lead for CyVerse (A US national life science cyberinfrastructure funded by NSF), and he organizes, instructs, and speaks at a variety of bioinformatics-related workshops, conferences, and meetings. He is an active Carpentries instructor, and a former Chair of the Software Carpentry foundation (an international organization of researchers that promote training and education in software development, scientific data management, and open science).
Associate Professor in the Mathematics Department at Grand Valley State University in Allendale, Michigan USA. In this position he teaches 2-3 classes a semester, conducts research (mostly in the teaching and learning of undergraduate mathematics, but sometimes in pure mathematics), and serves the university and broader community in a number of ways.
Executive Director of Data Carpentry and Adjunct Professor in the BEACON Center for the Study of Evolution in Action at Michigan State University. Her research background in is microbial metagenomics and bioinformatics, and she has been a developer and contributor to several open source bioinformatics projects. She also focuses on best practices in data analysis software development.
Although spaces may feel informal at times, we want to remind authors and reviewers (and anyone else) that this is a professional space. As such, the JOSE community adheres to a code of conduct adapted from the Contributor Covenant code of conduct.
Authors and reviewers will be required to confirm they have read our code of conduct, and are expected to adhere to it in all JOSE spaces and associated interactions.
We also want to remind authors and reviewers (and anyone else) that we expect and require ethical behavior. Some examples are:
Any potentially unethical behavior should be brought to the attention of the JOSE staff. See Contacting JOSE.
The JOSE Editors will track any concerns and respond to the submitter with a resolution, which will range from doing nothing if the editors disagree about the issue to withdrawing papers and notifying authors' institutions.
Journal of Open Source Education is an open access journal committed to running at minimal costs, with zero publication fees (article processing charges) or subscription fees.
Under the NumFOCUS nonprofit umbrella, JOSE is now eligible to seek grants for sustaining its future. With an entirely volunteer team, JOSE is seeking to sustain its operations via donations and grants, keeping its low cost of operation and free service for authors.
In the spirit of transparency, below is an outline of our current running costs:
Assuming a publication rate of 200 papers per year this works out at ~$3.50 per paper ((19*12) + 200 + 275) / 200.
A more detailed analysis of our running costs is available on our blog.
JOSE is an open access journal. Copyright of JOSE papers is retained by submitting authors and accepted papers are subject to a Creative Commons Attribution 4.0 International License.
Any code snippets included in JOSE papers are subject to the MIT license regardless of the license of the submitted software package under review.
Public user content licensed CC BY 4.0 unless otherwise specified.