Note that the information concluded by rule R4R4 could help to fire hybrid rules to give more personalized recommendations. For example, suppose that the OntoSakai model for the DBA subject includes information stating that the videoconference tool is the most used tool in the course. Then, combining the fact inferred by R4R4 (i.e., Alice is an active student in collaborative tools) with this information will fire rule R7R7 (see Section 4.3) to recommend she to use the videoconference tool better than forums since the former is the preferred tool in this course (and hopefully it LY450139 could help her to pass the evaluative tests). Note that this last inferred information is not included in Fig. 6 for the sake of readability.
In order to integrate OntoSakai into Sakai we are developing a new contrib module to perform the initial semantization of a subject and synchronization processes. The management of topic items and their assignments to tool elements have been also included in leaf veins module. Regarding the capture of events generated in Sakai we have used AspectJ3 to inject our code to update the OntoSakai model when an event is being processed. Finally, the management of the ontologies that compose OntoSakai and the expert rules has been accomplished by means of an API based on the Jena4 and Pellet5 libraries.