PLUMED Tutorials: A collaborative, community-driven learning ecosystem.

Saved in:
Bibliographic Details
Title: PLUMED Tutorials: A collaborative, community-driven learning ecosystem.
Authors: Tribello, Gareth A., Bonomi, Massimiliano, Bussi, Giovanni, Camilloni, Carlo, Armstrong, Blake I., Arsiccio, Andrea, Aureli, Simone, Ballabio, Federico, Bernetti, Mattia, Bonati, Luigi, Brookes, Samuel G. H., Brotzakis, Z. Faidon, Capelli, Riccardo, Ceriotti, Michele, Chan, Kam-Tung, Cossio, Pilar, Dasetty, Siva, Donadio, Davide, Ensing, Bernd, Ferguson, Andrew L.
Source: Journal of Chemical Physics; 3/7/2025, Vol. 162 Issue 9, p1-14, 14p
Subject Terms: SOFTWARE compatibility, SOFTWARE maintenance, ONLINE education, COMPUTATIONAL physics, COVID-19 pandemic
Abstract: In computational physics, chemistry, and biology, the implementation of new techniques in shared and open-source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several challenges. Common methods like direct knowledge transfer and in-person workshops are limited in reach and comprehensiveness. Furthermore, while the COVID-19 pandemic highlighted the benefits of online training, traditional online tutorials can quickly become outdated and may not cover all the software's functionalities. To address these issues, here we introduce "PLUMED Tutorials," a collaborative model for developing, sharing, and updating online tutorials. This initiative utilizes repository management and continuous integration to ensure compatibility with software updates. Moreover, the tutorials are interconnected to form a structured learning path and are enriched with automatic annotations to provide broader context. This paper illustrates the development, features, and advantages of PLUMED Tutorials, aiming to foster an open community for creating and sharing educational resources. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Chemical Physics is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
Be the first to leave a comment!
You must be logged in first