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An Emotion Oriented Topic Modeling Approach to Discover What Students are Concerned about in Course Forums

机译:一种情绪导向的主题建模方法,以了解学生在课程论坛中关注的内容

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Course forums offer an interactive channel for learners to express opinions and feedback, which contain valuable emotions and topic information towards courses. In this paper, we propose an emotion oriented topic probabilistic model that can be used to calculate distributions of emotion-topic over words to discover what students are most concerned about. An experiment on real-life data indicates that students had a positive attitude for knowledge applications, a negative experience for the learning system, and expressed confusion about the final exam. We also visualize the temporal trends of emotions of the whole group and the groups with different levels of achievement. The proposed model has a potential in discovering students' emotions in their feedback, thus improving the online learning experience, and identifying at-risk students timely.
机译:课程论坛为学习者提供互动渠道,以表达意见和反馈,这些频道包含有价值的情绪和对课程的主题信息。在本文中,我们提出了一种情绪导向的主题概率模型,可用于计算情感主题的分布,以了解学生最关心的内容。真实生活数据的实验表明,学生对知识应用的积极态度,对学习系统的负面体验,并表达了关于期末考试的困惑。我们还可视化整个团体的情绪的时间趋势以及具有不同成就水平的群体。拟议的模型有潜力在反馈中发现学生的情绪,从而提高在线学习经验,及时识别风险学生。

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