基于人工智能网络教学的现代网络教学质量评价模型

Hongyu Xie, He Xiao, Yu Hao
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引用次数: 0

摘要

现代网络教育系统是创新服务业中具有代表性的服务形式。本文设计了一个个性化服务域系统,优化了各种参数,可应用于不同的教育质量评价,并提出了一种决策树推荐算法。信息增益是通过改进决策树算法的许多现有原理进行的,算法的信息增益决定了信息的继承性。现代网络教学系统的过程是基于个性化教学和人性化智能交互的过程。本文从理论上分析了现有网络教学系统在教学质量评价方面的改进性能,显示出良好的分类效果。该模式为教育教学的拓展提供了参考资料,为网校个性化教学提供了可行的实践模式。作者为学生提供了良好的教育条件和环境,为社会培养了全面发展的人才。
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Evaluation Model of Modern Network Teaching Quality Based on Artificial Intelligence E-Learning
Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing principles of improved decision tree algorithm, and the information gain of the algorithm determines the inheritance of information. The process of modern e-learning system is based on personalized teaching and humanized intelligent interaction. This paper theoretically analyzes the improvement performance of the existing e-learning system in teaching quality evaluation and shows a good classification effect. This model provides reference materials for the expansion of education and teaching and provides a feasible practical model for personalized teaching in online schools. The authors provide good educational conditions and environment for students and cultivate all-around talents for the society.
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