Flexible education with individual learning paths (EDUFLEX)
Background and reason
Lifelong learning (LLL) is important for career development. This is pursued by supporting learners in their learning paths and by improving the connection within and between different levels of education (University, HBO, MBO). However, challenges exist in linking courses and programmes, which means that there is a need for a standardised and more efficient system for LLL education.
objective
The aim of this project is to develop an ecosystem in which learners can choose their own learning paths based on an integrated course offering. This should facilitate access to education by using technologies such as AI and by certifying courses with micro-credentials. The project focuses on the geoinformation, earth observation and space sector and will make recommendations for the application of the developed methods in other sectors.
Activities
The project is based on four pillars:
- Individual learning paths: Learners can mix courses based on their needs, supported by a learning path model.
- Data interoperability: Developing standards and systems to connect different courses into learning paths.
- Machine learning and AI: An AI-based search engine to predict learning paths for learners.
- Flexibilization within educational institutions: Collaboration with university and vocational education institutions to facilitate learning paths across different institutions.
Intended Outcomes
The project will result in a prototype and learning path visualisation that helps learners find suitable learning paths and in recommendations for linking courses based on user profiles. This will contribute to the efficiency and flexibility of LLL education, with the possibility of applying the approach to other domains.
