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Demonstrates enhanced neuroimaging learning through interactive notebooks, suggesting improved educational outcomes.
Neuroimaging education presents both conceptual and technical challenges: one must master complex foundational principles while navigating technical requirements including software installation, dependency management, and cross-platform compatibility. These tasks are valuable learning opportunities, but they can be time-consuming, which may shift focus away from learning about core neuroimaging concepts. While neuroimaging education benefits from many established resources, interactive notebooks can further integrate instruction with execution, providing a hands-on complement to existing educational materials. Here, we showcase NeurodeskEDU, an emerging learning resource developed using Neurodesk, an open-source, containerised neuroimaging platform, which enables neuroimaging workflows to be executed in a fully reproducible fashion through interactive Jupyter Notebooks. The notebooks integrate code, visualisations, narrative documentation, and direct access to open datasets into analysis workflows. Containerised software delivery reduces installation overhead while ensuring consistent execution across computing platforms. Community contributions undergo automated testing via GitHub Actions to ensure notebook quality and functionality, while persistent DOIs establish notebooks as formally citable scholarly outputs. This new community learning resource provides multiple deployment modes: zero-install cloud execution, downloadable notebooks for local use, static HTML documentation, and interactive slideshows for teaching scenarios. Through three use cases, we demonstrate how such interactive notebooks consolidate fragmented educational workflows, enable seamless multi-tool integration, and support scalable deployment from workshops to self-directed learning. By establishing educational materials as scholarly outputs with systematic quality assurance and version control, this work addresses ongoing challenges in computational publishing: maintaining reproducibility as software evolves, facilitating community contributions, and providing formal academic recognition for educational scholarship.
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Dörig et al. (2026) studied this question.
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