The ITSs and the new horizons of the educational and technological research. Since their first appearance the Intelligent Tutoring Systems (ITSs) has represented a field of research for technologies and for a reflection on teaching, learning and their relation. Their first development was connected to the idea that the best training was the one-to-one tutoring and a guided and deeply supported instruction. Soon afterwards that approach highlighted its downsides bringing also in this field the debate originated from the situated models and the role of motivation and emotions in the learning process. In the Nineties the cognitivist research produced the most interesting ITSs models: e.g. in the field of Physics, ANDES, of Geometry, CognitiveTutors, and Chemistry. At the beginning of the new millennium, the research in the cognitivist field moved its attention to the role of the emotions taking into account advantages underlined by the use of those systems and the need to cover their limitations.

A basic change occurred in the last 10 years when the attention was focused on the ill-defined domains and, following the wave of Web 2.0, on online collaboration. What does it mean to have an ITS that works in domains or in problems in which is not possible to build an ontology that can be validated in which the choices are related to the path, in which it’s difficult to build a process based on rules o a priori constraints ? What does it mean an ITS that takes into account the peer exchange as a productive aspect for learning?
The last years, just like reported by the two-year conferences ITS and AIED and the research by Underwood J. e Luckin R (2011), has highlighted a new attention to common topics in the educational field: the interest in the regulation during the teaching/learning process, the self regulating learning, and for a collaborative didactics.
As stated in the ITS 2012 document “The intelligence of these systems stems from the artificial intelligence technologies often exploited in order to adapt to the learners (e.g.: semantic technologies, user modelling), but also from the fact that today’s technologies, for instance the Web and the service oriented computing methods, facilitate new emergent collective behaviours”.
The developments in similar fields as Learning Analytics and Educational Data Mining set new challenges for the research and propose new ways in the direction of the personalization of the paths.
The present call aims at exploring the development of ITSs, the importance of profiling and of student modelling for such an evolution and the role that the EDM will have in the next years.