Selection Model of Optimal Mixed Teaching Mode in Higher Vocational Colleges Based on Big Data

Qing Liu, Ming Zeng
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引用次数: 1

Abstract

Under the background of big data, we should select the best hybrid teaching mode in higher vocational colleges, improve the ability of big data analysis of the mixed teaching mode in higher vocational colleges, and improve the quality of hybrid teaching mode in higher vocational colleges. A model for selecting hybrid teaching mode in the optimal higher vocational colleges is proposed based on big data. The big data analysis model of hybrid teaching in the optimal higher vocational colleges is constructed, and the information fusion of the mixed teaching mode in the optimal higher vocational colleges is carried out by using the structured big data information recombination method. The characteristic quantity of the associated information describing the optimal hybrid teaching mode in higher vocational colleges is extracted, and the big data fusion scheduling and optimization selection of the mixed teaching mode based on the piecewise information fusion is adopted. According to the characteristic clustering results, the self-regression analysis of the evaluation ability of hybrid teaching in the optimal higher vocational colleges is carried out, and the test statistic model is constructed to optimize the selection of the hybrid teaching model in higher vocational colleges. The simulation results show that this method is used to select the mixed teaching mode in higher vocational colleges, the information fusion ability of outputting big data is better, and the accuracy of model selection is high.
基于大数据的高职混合教学模式优选模型
在大数据背景下,选择最适合高职院校的混合教学模式,提高高职院校混合教学模式的大数据分析能力,提高高职院校混合教学模式的质量。提出了一种基于大数据的高等职业院校混合教学模式选择模型。构建了最优高职院校混合教学的大数据分析模型,利用结构化的大数据信息重组方法对最优高职院校混合教学模式进行信息融合。提取描述高职院校最优混合教学模式的关联信息特征量,采用基于分段信息融合的混合教学模式大数据融合调度和优化选择。根据特征聚类结果,对最优高职院校混合教学评价能力进行自回归分析,构建检验统计模型,对高职院校混合教学模式的选择进行优化。仿真结果表明,该方法用于高职院校混合教学模式的选择,输出大数据的信息融合能力较好,模型选择的准确性较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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