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Teacher interventions to enhance the quality of student comments and their effect on prediction performance

机译:教师干预以提高学生评论的质量及其对预测绩效的影响

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Today, the use of learning analytics is becoming more crucial in the learning environment for the purpose of understanding and optimizing students' learning situations. The purpose of this paper is to examine the impacts of Teacher Interventions (TIs) on students' attitudes and achievements involved with the lesson by analyzing their freestyle comment data after every lesson. The current study proposes a new method for building an accessible prediction model, which represents students' activities, situations and viewpoints; the method classifies words in the student comments into six attribute types and indicates the most important types that affect the prediction results. Further, the prediction results are compared with the topic-based statistical method that uses Latent Dirichlet Allocation and Support Vector Machine models. The results proved that there were positive correlations between TIs and the quality of writing comments that affect on improving the prediction results.
机译:如今,为了了解和优化学生的学习状况,在学习环境中使用学习分析变得越来越重要。本文的目的是通过分析每节课后的自由式评论数据,研究教师干预(TIs)对学生态度和成就的影响。当前的研究提出了一种新的方法来建立可访问的预测模型,该模型代表学生的活动,情况和观点。该方法将学生注释中的单词分为六种属性类型,并指示影响预测结果的最重要类型。此外,将预测结果与使用隐式狄利克雷分配和支持向量机模型的基于主题的统计方法进行比较。结果证明,TI与写作评论的质量之间存在正相关关系,这影响了预测结果的改进。

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