A Tool Set Combining Learning Styles Prediction, a Blended Learning Methodology and Facilitator Guidebooks – Towards a Best Mix in Blended Learning

Sabine Moebs (1) , Christophe Piombo (2) , Hadj Batatia (3) , Stephan Weibelzahl (1)

1 School of Informatics
2 IRIT - Institut de recherche en informatique de Toulouse
3 IRIT-TCI - Traitement et Compréhension d’Images

One of the challenges in the development in blended learning is to facilitate the individual learning styles of the learners. The alignment of a learning styles assessment with a learning methodology, a mapping between learning styles and social media, recommendations in a guidebook for facilitators and a checklist provide a tool set for a sustainable approach for a responsive learning environment. This paper analyzes how the different approaches, methods and studies interact to form an overall tool set to develop a learnercentered mix in blended learning. It proposes a tool set to adapt blended learning to the learning styles of the learners.

Keywords: bayesian networks; metadatas; index learning style (ILS)

Domains: Computer Science [cs]; Technology for Human Learning

Sabine Moebs, Christophe Piombo, Hadj Batatia, Stephan Weibelzahl. A Tool Set Combining Learning Styles Prediction, a Blended Learning Methodology and Facilitator Guidebooks – Towards a Best Mix in Blended Learning. Conference ICL2007, September 26 -28, 2007, 2007, Villach, Austria. 8 p. ⟨hal-00197294⟩