Evaluation method of teaching reform quality in colleges and universities based on big data analysis

被引：0
作者：
Wang, Xiumin [1 ]
机构：
[1] College of Information and Electronics Engineering, Shangqiu Institute of Technology, Henan, Shangqiu
来源：
International Journal of Business Intelligence and Data Mining | 2024年 / 25卷 / 3-4期
关键词：
big data analysis; colleges and universities; multivariate logistic model; reform quality evaluation; support vector machine model; whale algorithm;
D O I：
10.1504/IJBIDM.2024.140881
中图分类号：
学科分类号：
摘要：
Research on the quality evaluation of teaching reforms plays an important role in promoting improvements in teaching quality. Therefore, an evaluation method of teaching reform quality in colleges and universities based on big data analysis is proposed. A multivariate logistic model is used to select the evaluation indicators for the quality evaluation of teaching reforms in universities. And clustering and cleaning of the evaluation indicator data are performed through big data analysis. The evaluation indicator data is used as input vectors, and the results of the teaching reform quality evaluation are used as output vectors. A support vector machine model based on the whale algorithm is built to obtain the relevant evaluation results. Experimental results show that the proposed method achieves a minimum recall rate of 98.7% for evaluation indicator data, the minimum data processing time of 96.3 ms, the accuracy rate consistently above 97.1%. © 2024 Inderscience Enterprises Ltd.
引用
收藏
页码：306 / 322
页数：16
相关论文
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