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

机译：数据融合技术及跨平台MOOC数据分析技术研究

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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：大规模的开放式在线课程（MOOC）倾向于为全球人们提供平等的教育机会，其特点是规模大，阈值零，可随时访问等。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。在推广MOOC实践中，仍然存在一些问题，其中，课程完成率低是最大的挑战之一。本文介绍了AMMP，这是一个联盟MOOC管理平台，该平台聚集了多个MOOC平台上的信息，资源，服务和人员。总体而言，其总体目标是设计和开发用于学习和教授分析的方法，以促进个人学习环境。它着重于数据融合和分析技术。特别是，我们弄清楚了如何链接学习者的多个在线身份和数据传输。我们还展示了几个数据挖掘的例子。 AMMP倾向于对研究学生的学习行为以及提供建议和建议以提高服务质量产生巨大影响。

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