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Research on Data Mining of Learning Behaviours of College Students on MOOC Platform

机译:MOOC平台上大学生学习行为的数据挖掘研究

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With the continuous development of computer network and the popularity of internet applications, technology is constantly changing the traditional education model. The rise of the MOOC has set off a worldwide revolution in educational technology, which has been widely welcomed by university teachers and students. On the platforms of MOOC, the learning behaviours of college students have generated massive amounts of relevant data. Teachers can tap learning behaviours, master different types of learning styles to better control the learning steps and urge college students to better participate in all aspects of learning. Based on the MOOC platform, this paper classifies the students into excellent learners, middle learners, poor learners and non-learners by cluster analysis to teach students of different levels in different ways to optimize the MOOC teaching effect.
机译:随着计算机网络的不断发展和互联网应用的普及,技术正在不断改变传统教育模式。 MooC的兴起已经掀起了全球教育技术的革命,已被大学师生迅视受到广泛欢迎。在MooC的平台上,大学生的学习行为产生了大量的相关数据。教师可以挖掘学习行为,掌握不同类型的学习方式,以更好地控制学习步骤,并敦促大学生更好地参与学习的各个方面。基于MOOC平台,本文通过集群分析将学生分类为优秀的学习者,中学,贫困学习者和非学习者,以不同的方式教授不同水平的学生,以优化MOOC教学效果。

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