The following figure shows an architectural sketch of IWT that takes care of services, tools, subsystems, interfaces, content and data involved in definition, delivery and reconfiguration of personalized learning experiences. IWT follows the principles of e-learning service-oriented architectures so its architecture is natively extensible.






The above figure shows how the (IWT) Learner Intelligent Advisor (LIA) uses a Learner Profile in order to define a personalized learning activity workflow for a specific learner. The workflow definition also takes care of specific didactic methods selected with respect to the learning style of the learner. During the execution-phase, the personalized learning activity workflow is instantiated by the Delivery System that manages learning content, complex learning object, tools and services in a coordinated way in order to realize a Personalized Learning Experience. Furthermore, the Learner interacts with the Delivery System in order to advance with respect to the learning activity workflow, to assess his/her knowledge, to collaborate with other learners and so on. The Learner’s interactions are captured by the Delivery System interfaces and forwarded to the Profiling Service. The Profiling Service (by using the Learner Model) is able to update the right Learner Profile that is newly used in order to adapt the Personalized Learning Experience exploiting the learner’s feedbacks and behaviour.

The above figure also clarifies how ALICE results will enrich the IWT system. More in details, the set of available learning objects and complex learning objects will be extended with Storytelling C-LOs, Collaborative C-LOs and Simulations/Serious Games by instantiating the models defined in the ALICE project. Some C-LOs will need tools or support services. For instance, in order to create a Collaborative C-LO we need to extend collaboration tools and to provide specific authoring tools, while Simulations may need the computation provided by Symbolic Calculus Engines. Furthermore, authoring tools able to establish semantic connections between Learning Objects will be also released as project results.