Use of contextualized attention metadata for ranking and recommending learning objects
CAMA '06 Proceedings of the 1st international workshop on Contextualized attention metadata: collecting, managing and exploiting of rich usage information
Application independent metadata generation
CAMA '06 Proceedings of the 1st international workshop on Contextualized attention metadata: collecting, managing and exploiting of rich usage information
Hi-index | 0.00 |
This paper addresses the challenge of providing users with personalized learning resources by gathering and sharing attention information. Starting from our previous works related to the tracking of learning objects' exploitation within learning systems, we suggest here an extension of this framework based on the Attention.XML standard to offer the opportunity to share attention information between various and heterogeneous applications. An Attention.XML service based on web technologies has been elaborated and integrated within the existing architecture, thus offering standardization and availability to the global environment. This approach makes it easy to integrate existing learning environments and tools, and thus facilitates the generation of attention data specific to these applications.