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首页> 外文会议>International Conference on Information Technology Based Higher Education and Training >A Novel ontology-based automatic method to predict learning style using Felder-silverman model
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A Novel ontology-based automatic method to predict learning style using Felder-silverman model

机译：基于新型本体论的自动方法，用于使用Felder-Silverman模型预测学习风格

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Learning style is considered as preferred manner in which learners acquire effectively new knowledge. Individual's learning style contains mainly his preferences, his expectations and his needs. In addition, it represents a key asset in improving teaching methods that meet learners' needs. During the last decades, the identification of learning style methods has been relied on two basic measure methods: collaborative and automated ones. In this paper, we propose automatic test PRFSLM is based on Felder-Silverman learning style model (FSLM) that helps instructors to create and personalize their placement task's items. Our proposed ontology-based automatic method aims (1) to assess the learner's prerequisites and also (2) to provide explicitly an extensive knowledge about learner preferences that could predict his own learning style at the beginning of an online training.
机译：学习风格被认为是学习者有效地获得新知识的首选方式。个人的学习风格主要包含他的偏好，他的期望和他的需求。此外，它代表了改善符合学习者需求的教学方法的关键资产。在过去几十年中，识别学习风格方法的依赖于两种基本测量方法：协作和自动化。在本文中，我们提出了自动测试PRFSLM基于Felder-Silverman学习风格模型（FSLM），帮助教师创建和个性化其放置任务的项目。我们提出的基于本体的自动方法（1）旨在评估学习者的先决条件，并（2）还有关于学习者偏好的明确知识，可以在在线培训开始时预测他自己的学习风格。

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