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The CODEE Journal is a peer-reviewed, open-access publication, distributed by the CODEE (Community of Ordinary Differential Equations Educators) and published by the Claremont Colleges Library, for original materials that promote the teaching and learning of ordinary differential equations.

The CODEE Journal is an open access journal, which means that all content is freely available without charge to the user or their institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access. All articles are licensed with a Creative Commons license. The journal is archived by LOCKSS.

CODEE Journal is seeking submissions for a 2026 Special Issue with a theme on Data-driven Modeling with Differential Equations. We seek scholarly contributions focused on undergraduate education and research that demonstrate how ODEs can be used to extract insight from data, support predictive modeling, and inform analysis in areas such as epidemiology, ecology, climate science, economics, public health, engineering, and beyond. Engaging students in modeling and data analysis using differential equations helps bridge theoretical mathematics with real-world challenges and builds essential skills for today’s data-rich world. Please see all the details here. Paper Submission Deadline: April 1, 2026