IWT will constitute the technological basis and the reference platform for this project. This means that models, methodologies, learning resources and software tools that will be here defined and developed will be thought to be integrated in IWT for experimentation purposes. IWT logical architecture is divided in three main layers.

The first layer is the framework used by developers to design and implement core services, application services and learning applications. The second layer is composed by core services providing basic IWT features like resource management, workflow management, information extraction, ontology storing, user authentication, content storing, metadata management, role and membership management, learning customisation, logging and profiling and data mining. Core services are used by application services and learning applications.

Application services are services to be used as building blocks to compose e-learning applications for specific domains. They include document management, conferencing, authoring, learning management, learning content management, ontology management, communication and collaboration, business intelligence, process management and information search services. Applications represent complex solutions covering specific learning scenario obtained as integration of application services.

IWT architecture is modular enough to allow the deployment of solutions capable to cover application scenarios of different complexity and for different domains by composing service building blocks. Basing on these features, IWT will be part of the ALICE solution. In particular, starting from IWT, the results expected by the project can be summed up into the following key points:

– extension of the IWT adaptivity with the capability of managing feedbacks received from the emotionalaffective interaction learner-system;
– extension of IWT collaboration and communication skills, with specific attention to virtualized collaboration;
– assessment of new learning paradigms, guided by interactive-experiential approaches, but based on storytelling and serious games;
– experimentation of new paradigms of assessment distributed along the learning process and realised, thanks to advanced resources;
– generation of learning resources able to assess the progress done in the learning process about scientific themes and the cognitive impact after learning experiences enabling to integrate and manage aspects like adaptivity, driven not only by aspects of learner personalisation, user profiling, knowledge and didactic modelling but also by emotional/affective aspects and storytelling.