摘要
为了提高体育课堂情景教学质量,提出基于大数据挖掘的体育课堂情景教学质量评价系统。系统由初始设置、数据准备、评价过程管理和评价结果管理4个模块组合而成,评价指标体系由一级指标与二级指标组成,且通过粗糙集理论完成各项指标的权重值标定,采用数据挖掘中决策树法完成综合评价的分析。最后给出系统的网页结构和具体工作流程,实现体育课堂情境教学质量评价系统的构建。实验证明系统评价结果符合客观实际基础上科学性更强,且系统运行速度较快、页面简洁、操作便捷,适用于实际的教学质量评价应用中。
In order to improve the quality of situational teaching in physical education classroom, a quality evaluation system of situational teaching in physical education classroom based on big data mining is proposed. The system is composed of four modules: initial setting, data preparation, evaluation process management and evaluation result management. The evaluation index system is composed of primary index and secondary index. The weight value of each index is calibrated by rough set theory, and the comprehensive evaluation is analyzed by decision tree method in data mining. Finally, the web page structure and specific workflow of the system are given to realize the construction of situational teaching quality evaluation system. Experiments show that the system evaluation results accord with the objective reality, on the basis of more scientific, and the system runs faster, the page is simple,easy to operate, suitable for the actual application of teaching quality evaluation.
作者
杨艳
何佳佳
卢琼
YANG Yan;HE Jia-jia;LU Qiong(Physical Education And Research Department,Shangluo University,Shangluo 726000 China;School of mathematics and computer Application,Shangluo University,Shangluo 726000 China)
出处
《自动化技术与应用》
2023年第2期147-150,共4页
Techniques of Automation and Applications
基金
商洛学院教改项目(20jyjx128)。
关键词
质量评价
粗糙集理论
权重值标定
决策树法
网页结构
quality evaluation
rough set theory
weight value calibration
decision tree method
Web page structure
