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Optimization Analysis and Implementation of Online Wisdom Teaching Mode in Cloud Classroom Based on Data Mining and Processing

机译:基于数据挖掘和处理的云课堂在线智慧教学模式的优化分析与实现

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The rapid development of Internet technology and information technology is rapidly changing the way people think, recognize, live, work and learn. In the context of Internet education, the emerging learning form of a cloud classroom has emerged. Cloud classroom refers to the process in which learners use the network as a way to obtain learning objectives and learning resources, communicate with teachers and other learners through the net-work, and build their own knowledge structure. Because it breaks the boundaries of time and space, it has the characteristics of freedom, high effi-ciency and extensiveness, and is quickly accepted by learners of different ag-es and occupations. The traditional cloud classroom teaching mode has no personalized recommendation module and cannot solve an information over-load problem. Therefore, this paper proposes a cloud classroom online teach-ing system under the personalized recommendation system. The system adopts a collaborative filtering recommendation algorithm, which helps to mine the potential preferences of users and thus complete more accurate recommendations. It not only highlights the core position of personalized curriculum recommendation in the field of online education, but also makes the cloud classroom online teaching mode more intelligent and meets the needs of intelligent teaching.
机译:互联网技术和信息技术的快速发展正在迅速改变人们认为,认识,生活,工作和学习的方式。在互联网教育的背景下,出现了云课堂的新兴学习形式。云课堂是指学习者使用该网络作为获得学习目标和学习资源的方式的过程,通过网络工作与教师和其他学习者沟通,并建立自己的知识结构。因为它破坏了时间和空间的界限,所以它具有自由,高效率和广泛性的特点,并通过不同的AG-es和职业的学习者迅速接受。传统的云课堂教学模式没有个性化推荐模块,无法解决信息过负载问题。因此,本文提出了在个性化推荐系统下的云课堂在线教学系统。该系统采用协同过滤推荐算法,有助于挖掘用户的潜在偏好,从而完成更准确的建议。它不仅突出了在线教育领域的个性化课程推荐的核心位置,而且还使云课堂在线教学模式更加聪明,满足智能教学的需求。

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