Intelligent tutoring systems need a model of learning goals for the personalization of educational content, tailoring of the learning path, progress monitoring, and adaptive feedback. This article presents such a model and corresponding interaction designs for the coaches and learners (respectively, a monitor-and-control dashboard and mobile app with supportive communications trough a virtual agent), all deployed and tested in a system for child diabetes self-management training. We developed a domain-independent upper ontology to structure learning goals and related concepts (such as achievements and tasks) and a domain ontology that specifies the knowledge base (for, in our case, diabetes self-management training). With this approach, we relate knowledge elements (e.g., skill) to educational tasks and to learners' knowledge development (e.g., achievements). The ontology was implemented in a multimodal tutoring system consisting of mobile educative games, a health diary, an embodied conversational agent (ECA), and a web application for authoring and monitoring. We show that our model provides a coherent and concise foundation for: 1) the formalization of learning in the diabetes self-management domain, but also for other domains such as mathematics; 2) personal goal setting and thereby personalization of the educational process including ECA's guidance; and 3) creating awareness of progress on the personal educational path. We found that a motivational tutoring system requires a rich set of learning activities and accompanying materials of which a subset is offered to the learner based on personal relevance. The implemented model proved to accommodate the personal agent-guided learning paths of children with diabetes, under different treatments from hospitals in Italy and the Netherlands.
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- Diabetes self-management
- human-agent interaction
- Knowledge based systems
- learning goal
- Task analysis