基于大数据模糊K均值聚类的英语教学能力评估算法研究

发布时间：2018-09-17 20:16

【摘要】：针对传统的英语教学能力评估算法存在大数据信息分类不准的问题,提出基于大数据模糊K均值聚类和信息融合的英语教学能力估计算法。首先,建立约束参量指标分析模型;其次,使用定量递归分析方法对大数据信息模型的能力进行评估,实现能力约束特征信息的熵特征提取;最后,融合大数据信息融合及K均值聚类算法,实现英语教学能力的指标参数聚类和整合,编制相应的教学资源分配计划,实现英语教学能力评估。试验结果表明,采用该方法进行英语教学能力评估,具有较好的信息融合分析能力,提高了教学能力评估的准确性和教学资源应用效率。
[Abstract]:Aiming at the problem of inaccurate classification of big data information in the traditional English teaching ability assessment algorithm, an English teaching ability estimation algorithm based on big data fuzzy K-means clustering and information fusion is proposed. Firstly, a constraint parameter index analysis model is established; secondly, the ability of big data information model is evaluated by using quantitative recursive analysis method. Finally, the entropy feature extraction of capability constraint feature information is realized. By combining big data's information fusion and K-means clustering algorithm, the index parameters of English teaching ability can be clustered and integrated, the corresponding teaching resource allocation plan can be worked out, and the evaluation of English teaching ability can be realized. The experimental results show that this method has a good ability of information fusion and analysis, and improves the accuracy of teaching ability assessment and the efficiency of teaching resources application.
【作者单位】：泰州学院;
【基金】：江苏省现代教育技术研究2015年度课题(2015-R-41638)
【分类号】：H319.3;TP311.13

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