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A learner model in a reading tutor is a crucial component to individualize the teaching. Our intelligent agent-based system named AMICAL aims to teach the reading to a single seven year old French child in his mother tongue. In our system, we defined three different sections of the learner model: domain knowledge, cognitive and meta-cognitive aspect and the behaviour of the child. From the reports recorded during the interactions between the child and our system, we build step by step the learner model of that child. It is represented with complex frames. It has three goals: first for our system, second for the teacher and third for the child. The learner model is build from different analysis at different levels of the reports. We have three levels of analysis: a local analysis for each activity in the work session, a synthetic analysis that involves the entire work session and a historical analysis that takes in consideration the current session and the sessions before. An intelligent agent of our system builds and manages the learner model. In this paper, we discuss the importance of a learner model in a reading tutor, its content, its representation and the construction such a model..
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