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Big data oriented partner selection in collaborative learning

机译：协作学习中面向大数据的合作伙伴选择

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Collaborative Learning is seen as an effective leaning strategy to increase students' achievement, create positive relationships among learners in online education. The traditional hypothesis of partner selection in collaborative learning is that teachers must be skilled at the task to assign the learning partners, or the collaboration will not benefit an individual if he or she is below a certain developmental level. It is hard to assess whether the teachers are skillful, and whether the learners have the sufficient capabilities to be a good partner. In this paper, we give the classification and characteristics of the big data in the field of Collaborative Learning, and then discuss about data mining on Collaborative Learning and the user behavior analysis which is used to select the appropriate learning partner. Next we describe the overall framework of big data on partner Selection in collaborative learning, and emphasize the application which can be realized according to the different levels of learning participants. Our goal in this paper is to pave the way for partner selection to solve the fundamental problem of collaborative learning, which will contribute to the development of online education outcome with big data.
机译：协作学习被视为提高学生成绩，在在线教育中的学习者之间建立积极关系的有效学习策略。合作学习中合作伙伴选择的传统假设是，教师必须熟练掌握分配学习合作伙伴的任务，否则，如果合作伙伴的成长水平低于特定水平，则合作不会使个人受益。很难评估教师是否熟练，学习者是否具有足够的能力成为良好的伴侣。在本文中，我们给出了协作学习领域中大数据的分类和特征，然后讨论了关于协作学习中的数据挖掘和用于选择合适学习伙伴的用户行为分析。接下来，我们描述大数据合作伙伴选择在协作学习中的总体框架，并强调可以根据学习参与者的不同水平实现的应用程序。我们的目标是为合作伙伴的选择铺平道路，以解决协作学习的基本问题，这将有助于大数据在线教育成果的发展。

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