Application Effect Robust Evaluation Algorithm of Online and Offline Hybrid Teaching Mode in Undergraduate Colleges

Keqiang Xu, Y. Xiong
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引用次数: 0

Abstract

In order to improve the practical application effect of the mixed teaching mode, an application effect evaluation algorithm of online and offline hybrid teaching mode in undergraduate colleges is proposed. Firstly, the big data technology is used to collect the big data in the online and offline mixed teaching process of undergraduate colleges, and an evaluation index system is built from three dimensions to extract the required data according to the indicators. Then the association rules between the relevant data of the evaluation indicators are established to obtain the phase space distribution of the data. Finally, the constraint parameter analysis method is used to fuse the control variables and explanatory variables of the index related data to realize the online and offline mixed teaching effect evaluation. The experimental results show that the proposed algorithm achieves an ideal evaluation result of online and offline mixed teaching effect, which is conducive to improving the teaching quality.
本科院校线上线下混合教学模式应用效果稳健评价算法
为了提高混合教学模式的实际应用效果,提出了一种本科院校线上线下混合教学模式的应用效果评价算法。首先,利用大数据技术采集本科院校线上线下混合教学过程中的大数据,并从三个维度构建评价指标体系,根据指标提取所需数据。然后建立评价指标相关数据之间的关联规则,得到数据的相空间分布。最后,采用约束参数分析法融合指标相关数据的控制变量和解释变量,实现线上线下混合教学效果评价。实验结果表明,所提算法取得了较为理想的线上线下混合教学效果评价结果,有利于提高教学质量。
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