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Automatic Classification for Cognitive Engagement in Online Discussion Forums: Text Mining and Machine Learning Approach

机译:在线讨论论坛中的认知参与的自动分类:文本挖掘和机器学习方法

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For effective learning, students must set learning objectives and adopt the ad hoc cognitive behavior to achieve them. Our research work aims to ensure good scaffolding by offering tutors the opportunity to observe learners' cognitive behaviors, especially their cognitive engagement. In this respect, we propose in the present work an automatic system for classifying learners according to their levels of cognitive engagement. To this end, we focus on the analysis of social interactions within online discussion forums. Hence, the proposed system has two main steps: I/Learners' vector construction and 2/SVM-based classifier. The results show the efficiency of the proposed system with an accuracy = 0.9 and a Cohen's K = 0.89.
机译:为了有效学习,学生必须设定学习目标,并采取特殊的认知行为来实现这些目标。我们的研究工作旨在通过为导师提供观察学习者的认知行为,尤其是他们的认知参与度的机会,来确保良好的脚手架。在这方面,我们在当前的工作中提出了一个自动系统,用于根据学习者的认知参与程度对其进行分类。为此,我们重点分析在线讨论论坛中的社交互动。因此,所提出的系统具有两个主要步骤:I /学习者的向量构造和基于2 / SVM的分类器。结果表明,所提系统的效率为精度= 0.9和Cohen's K = 0.89。

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