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Application Research of an Innovative Online Education Model in Big Data Environment

机译:创新在线教育模式在大数据环境中的应用研究

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Online education is a network-based approach to teaching. It is a method of content dissemination and rapid learning through the application of UGC and Internet technology.Compared with traditional school education, online learning can obtain more resources, more autonomy, and no longer limited time and space for learning.Through the questionnaire, this paper finds that learners in the online education model still have some shortcomings in the learning process.For example, the learning process is not durable.Therefore, this paper uses neural network classification algorithm to analyze the related factors that affect the learning behavior of online education students.And propose corresponding control strategies for different influencing factors.By constructing a learning process control strategy model for large educational data, to help learners improve their learning efficiency, help the online education model break through the bottleneck, the online education industry has maintained rapid development.Finally, through the comparative analysis of the improved online education model and the traditional online education model, finding an improved online education model can better improve students' interest in learning.Provided a reference for the development of online education,It also provides a reference for the transformation and upgrading of traditional education to online education.
机译:在线教育是一种基于网络的教学方法。它是一种通过UGC和Internet技术的应用进一步传播和快速学习的方法。在传统学校教育中,在线学习可以获得更多资源,更自主,并且不再有限的时间和空间来学习。接受调查问卷,这纸质发现,在线教育模式中的学习者在学习过程中仍然存在一些缺点。例如,学习过程并不耐用。因此,本文采用神经网络分类算法分析了影响在线教育学习行为的相关因素提出了不同影响因素的相应控制策略。通过构建大型教育数据的学习过程控制策略模型,帮助学习者提高学习效率,帮助在线教育模式突破瓶颈,在线教育行业保持迅速开发。最后,通过比较分析在线教育模式和传统在线教育模式的改进,发现改善的在线教育模式可以更好地提高学生对学习的兴趣。提供了在线教育发展的参考,它还为传统的转型和升级提供了参考教育到在线教育。

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