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AUTOMATIC FEEDBACK GENERATION Using Ontology in an Intelligent Tutoring System for both Learner and Author Based on Student Model

机译:基于学生模型的学习者和作者的智能辅导系统中使用本体的自动反馈生成

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Presenting feedback to learner is one of the essential elements needed for effective learning. Feedback can be given to learners during learning but also to authors during course development. But producing valuable feedback is often time consuming and makes delays. So with this reason and the others like incomplete and inaccurate feedback generating by human, we think that it's important to generate feedback automatically for both learner and author in an intelligent tutoring system (ITS). In this research we used ontology to create a rich supply of feedback. We designed all components of the ITS like course materials and learner model based on ontology to share common understanding of the structure of information among other software agents and make it easier to analyze the domain knowledge. With ontologies in fact, we specify the knowledge to be learned and how the knowledge should be learned. In this paper we also show a mechanism to make reason from the resources and learner model that it made feedbacks based on learner.
机译:向学习者提出反馈是有效学习所需的基本要素之一。在学习期间可以向学习者提供反馈,而且还可以在课程开发期间给作者。但产生宝贵的反馈通常是耗时的,并造成延误。因此,通过这种原因和人类产生不完整和不准确的反馈,我们认为在智能辅导系统(其)中为学习者和作者自动生成反馈非常重要。在本研究中,我们使用本体造成丰富的反馈供应。我们基于本体设计了其游泳课程材料和学习者模型的所有组成部分,以共同了解其他软件代理中信息结构,并更容易分析域知识。有了本体实际上,我们指定要学习的知识以及应该如何了解知识。在本文中,我们还显示了一种机制,从而从资源和学习者模型中制作了基于学习者的反馈。

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