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Research on Evaluation and Confirmation of College Students' Learning Behavior Based on Comprehensive Weighted Fusion Algorithm

机译:基于综合加权融合算法的大学生学习行为评价与确认研究

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In order to solve the problem of the lack of information in the evaluation of university students' learning behavior with single data, a multi-source data fusion evaluation of university students' learning behavior is proposed to explore the application value of data fusion technology in teaching. First use Spearman to calculate the correlation between different data sources, calculate the relationship weight and optimization weight of different data sources, and then comprehensively weight for fusion calculation. The fusion calculation of students' comprehensive learning behavior evaluation through comprehensive weighted fusion can not only balance the differences in learning behavior evaluation of students under different teaching methods, but also integrate the advantages and disadvantages of different learning methods. Experiments verify that the comprehensive weighted data fusion algorithm is effective, which can provide help for a more comprehensive analysis of the evaluation of college students' learning behavior and provide a basis for adapting to their own learning.
机译:为了解决大学生学习行为评估中缺乏信息的问题,提出了大学生学习行为的多源数据融合评估,探讨了数据融合技术在教学中的应用价值。首先使用Spearman来计算不同数据源之间的相关性,计算不同数据源的关系权重和优化权重,然后进行融合计算的全面重量。通过全面加权融合的学生综合学习行为评估的融合计算不仅可以平衡学生在不同教学方法下学习行为评估的差异,而且整合了不同学习方法的优缺点。实验验证了全面的加权数据融合算法是否有效,可以帮助更全面分析大学生学习行为的评估,为适应自身学习提供依据。

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