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Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student's affective state, to move them out of negative states that inhibit learning, into positive states such as engagement. In spite of their obvious potential to provide the personalisation that would give extra support for learners with intellectual disabilities, little work on AIEd systems that utilise affect recognition currently addresses this group. Our system used multimodal sensor data and machine learning to first identify three affective states linked to learning (engagement, frustration, boredom) and second determine the presentation of learning content so that the learner is maintained in an optimal affective state and rate of learning is maximised. To evaluate this adaptive learning system, 67 participants aged between 6 and 18 years acting as their own control took part in a series of sessions using the system. Sessions alternated between using the system with both affect detection and learning achievement to drive the selection of learning content (intervention) and using learning achievement alone (control) to drive the selection of learning content. Lack of boredom was the state with the strongest link to achievement, with both frustration and engagement positively related to achievement. There was significantly more engagement and less boredom in intervention than control sessions, but no significant difference in achievement. These results suggest that engagement does increase when activities are tailored to the personal needs and emotional state of the learner and that the system was promoting affective states that in turn promote learning. However, longer exposure is necessary to determine the effect on learning.

Scenario-based learning (SBL) has recently received more and more attention in the training and education fields as a mechanism for providing active and generative learning. E-learning systems can provide a solid platform upon which SBL can be created and used to promote relational competences development, and to offer open source e-learning tools so to overcome common lack of access to affordable training resources. Within this paper a project called ACCORD to develop a new e-learning system to promote intercultural skills in terms of intercultural literacy, inclusive education and conflict management will be described. This project aims to prepare secondary school teachers from five European countries (Austria, Belgium, Germany, Italy, Spain) to take an active stand against intercultural conflicts within the school context, by providing SBL and game-based learning approach. The present article will provide an overview of the ACCORD project, highlighting the theoretical framework underpinning its development, the methodologies that have been used, and the main preliminary outcomes.