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Research on teaching quality evaluation method of network course based on intelligent learning

机译：基于智能学习的网络课程教学质量评价方法研究

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摘要

In view of the problems of poor evaluation effect and high evaluation delay in the existing evaluation methods for network course teaching quality, this paper designs an evaluation method based on intelligent learning. The design idea is as follows: with the help of public services, different forms of teaching tasks are summarised and data reduction is processed. On this basis, the restricted Boltzmann machine method based on intelligent learning is adopted to design the evaluation algorithm, and the teaching quality is evaluated with weighting parameters and preference parameters. Through the application part, different application functions such as information query, scene construction, data management and view viewing during the network course teaching are realised. The experimental results show that this method has high evaluation efficiency, short evaluation delay, and significantly reduced actual use of class time, which guarantees the teaching quality of teachers and the overall learning effect of students, and has high application advantages.
机译：鉴于网络课程教学质量现有评估方法的评价效应差和高评价延迟问题，本文设计了一种基于智能学习的评估方法。设计理念如下：在公共服务的帮助下，总结了不同形式的教学任务，并处理了数据减少。在此基础上，采用基于智能学习的受限制的Boltzmann机器方法来设计评估算法，并使用加权参数和偏好参数进行教学质量。通过应用部分，实现了不同的应用程序功能，如信息查询，场景施工，数据管理和网络课程教学期间的视图观看。实验结果表明，该方法的评价效率高，评估延迟短，实际使用类时间的实际使用，这保证了教师的教学质量和学生的整体学习效果，具有高的应用优势。

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