Description
Learning Paths are pathways that guide the learner through a set of learning courses or materials to be undertaken progressively to acquire the desired knowledge and skills on a subject. Establishing and implementing Learning Paths will facilitate the learning process in any professional trajectory and career path.
What can you do with Learning Paths
The main aims of the ELIXIR Learning Paths project are:
- Develop guidelines and best practices on how to create Learning Paths
- Implement Learning Paths across different communities
- Raise awareness on the pedagogical aspects and promote their adoption
- Establish a community of practice to share knowledge, experiences, and ideas
Testimonials
The ELIXIR Learning Paths Protocol provided a coherent structure to build tailored training solutions, guiding learners to acquire the desired knowledge and skills on the subject of cancer research data management, in the context of the EOSC4Cancer project.
As part of the XV Einstein Telescope Symposium, we developed a FAIR Learning Path for Gravitational Wave Science, based on direct application of the ELIXIR Learning Paths Protocol. As participants in the ELIXIR Learning Paths workshop series, it was a great opportunity for us to transfer all the knowledge and resources gathered there to the Astronomy and Astrophysics domain.
Activities and resources related to Learning Paths
- Learning Paths guidelines:
- Developing Learning Paths - The Learning Paths Protocol - https://zenodo.org/records/10082795
- ELIXIR Learning Paths Handbook
- Use-cases:
- A guidance document for the EOSC4Cancer learning pathway - https://zenodo.org/records/10200523
- Learning path development for plant data management - Poster: Haurheeram V, ELIXIR Training Platform, Michotey C et al. (version 1; not peer reviewed). F1000Research 2023, 12(ELIXIR):590 - https://doi.org/10.7490/f1000research.1119444.1
- Towards a FAIR path for the Einstein Telescope: Poster presented at the XV Einstein Telescope Symposium. The poster describes a strategy to build a FAIR Learning Path for astrophysics of gravitational waves. The strategy is based on ELIXIR Learning Paths Protocol. https://dataverse.bsc.es/dataset.xhtml?persistentId=perma:BSC/HCRTFY
- Events:
Contacts
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Editor
University of Cambridge