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A Research on Techniques for Data Fusion and Analysis of Cross-platform MOOC Data

机译：跨平台MOOC数据数据融合和分析技术的研究

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Massive open online courses(MOOCs) tends to open up equal educational opportunities for people around the globe, with characters of great scale, zero threshold, any-time access and so on. It has exerted a profound influence on learning environments and changed people's way of receiving education. In the promotion of MOOC practice, there still remain problems among which, the low course-completion rate is one of the biggest challenges. This paper presents AMMP, an alliance MOOC management platform which aggregates information, resources, services and people across a number of MOOC platforms. Its overarching goal as a whole is to design and develop methods for learning and teaching analytics to facilitate a personal learning environment. It focuses on the techniques for data fusion and analysis. Particularly, we figure out how to link multiple online identities of learners and data transmission; we also show a couple of examples of data mining. AMMP tends to exert a tremendous influence on researching students learning behavior and offering advice and suggestions to improve service quality.
机译：大规模开放的在线课程（MOOCS）倾向于为全球人民开辟平等的教育机会，具有大规模，零门槛，任何时间访问等特征。它对学习环境产生了深远的影响，改变了人们接受教育的方式。在促进MooC实践中，仍然存在问题，其中，低级接地率是最大的挑战之一。本文介绍了AMMP，这是一个联盟MooC管理平台，它聚集了许多MoOC平台的信息，资源，服务和人员。其整体的总体目标是设计和开发学习和教学分析的方法，以促进个人学习环境。它侧重于数据融合和分析的技术。特别是，我们弄清楚如何链接学习者和数据传输的多个在线身份;我们还显示了一些数据挖掘的例子。 AMMP对研究学生的学习行为和提供建议和建议来提高服务质量的建议和建议倾向于发挥巨大影响。

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