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An intelligent tutoring system aims to provide immediate and customized instruction and feedback to learners. In this context, existing tutoring systems have limitations in the areas of dialogue, feedback and emotion-motivation, which are important elements in the learning process. These aspects are related with the learner abilities, capacities, and motivations. To overcome these limitations, we propose to model the user characteristics that are involved in the learning process and in the human- machine interaction. In this paper we present a proposal to consider an integral user profile in order to gain effectiveness and to achieve more adaptability to the learner.
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Juárez‐Ramírez et al. (2013) studied this question.
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