Automatic Generation of Metadata for Learning Objects

Proper reuse of learning objects depends both on the amount and quality of attached semantic metadata such as "learning objective\´", "related concept", etc. Manually expressing such metadata is a time consuming and expensive task. Here we present an approach based on a probabilistic model, which through the automatic classification of learning resources on a given taxonomic organization of the knowledge, allows to associate ontological metadata to the learning resources