Abstract
This paper offers an extended abstract of a PhD project that focuses on supporting learners in finding most suitable learning activities in informal learning environments. For this purpose we aim to develop a personal recommender system, which will recommend most suitable learning activities to learners regarding their personal needs and preferences.
As a theoretical framework for informal learning environments we use the concept of Learning Networks. Learning Networks can be filled with lots of learning activities stemming from different providers. Such networks are dynamic, because each member could add or delete content at any time. A personal recommender system is needed to support learners in selecting learning activities from a Learning Network that will enable them to achieve their learning goals in a specific domain.
It is expected that such support will minimize the amount of time learners need for finding suitable learning activities. A better alignment of the characteristics of learners and learning activities is expected to increase both effectiveness and efficiency of learning progress of the learners.
Original language | English |
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Journal | Default journal |
Publication status | Published - 21 Jul 2008 |
Keywords
- Measurement
- Human Factors
- Experimentation
- Technology Enhanced Learning
- Informal Learning
- Learning Networks
- Recommender Systems
- Collaborative Filtering