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

Sabine Moebs ¹ Christophe Piombo ² Hadj Batatia ² Stephan Weibelzahl ¹

2 IRIT - Institut de recherche en informatique de Toulouse

Abstract : 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)

Document type :

Conference papers

Domain :

Computer Science [cs] / Technology for Human Learning

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https://telearn.archives-ouvertes.fr/hal-00197294
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A Tool Set Combining Learning Styles Prediction, a Blended Learning Methodology and Facilitator Guidebooks – Towards a Best Mix in Blended Learning

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

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347

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