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Multi level didatic content for reactive personalization on intelligent tutor systems

机译:多级教学内容,用于智能导师系统上的反应式个性化

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This paper presents a model for organization of educational content in connectionists intelligent tutoring systems. The availability of educational content in a single format has emerged as a problem for many students. The inadequacy of a single format of content that ignores differences in individual profiles may have inefficient outcomes in the teaching-learning process. The proposed multilevel structure allows for different combinations of concepts for presentation to the same content. Assuming that the pattern of successful organization of the study by a student can be applied to other students with similar profiles, a system was structured to assist in the task of customization reactive content. The customization is provided by a neural network that links the student's profile to a proximal learning pattern. This pattern is combined with expert rules to enable a probabilistic selection so that the system presents the reactivity in the different learning stages. The results of experiments indicate that the approach is effective in providing better use of the content in the personal study and its potential use in Distance Education.
机译:本文提出了一种在连接员智能辅导系统中组织教育内容的模型。对于许多学生来说,以单一格式提供教育内容已成为一个问题。忽略单个档案中差异的单一内容格式不足可能会在教学过程中产生无效的结果。所提出的多级结构允许用于呈现给相同内容的概念的不同组合。假设一个学生成功组织学习的模式可以应用到其他具有相似特征的学生,那么系统就可以构建以协助定制反应性内容的任务。定制是由神经网络提供的,该网络将学生的个人资料链接到近端学习模式。这种模式与专家规则相结合,可以进行概率选择,以便系统显示不同学习阶段的反应性。实验结果表明,该方法可有效地更好地利用个人学习内容及其在远程教育中的潜在用途。

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