基于决策树分类思想的线上思政教学课程推荐方法设计
Design of online Civics teaching course recommendation method based on decision tree classification idea
张成玉 1刘宁1
作者信息
- 1. 西安医学院学生工作部,陕西西安 710021
- 折叠
摘要
随着教育形式的快速发展,线上思政教学已经逐渐成为一种常见的教育模式.为了提高线上思政教育的效率,此次研究通过引入信息增益率和重要度参数,对决策树分类算法中的迭代二叉树三代算法进行改进.再采用改进后的迭代二叉树三代算法构建思政教育资源分类模型,并根据该模型构建了思政教育课程推荐系统.实验结果表明,改进迭代二叉树三代算法下的思政教育分类模型可以达到 99.5%的分类准确率和 0.4%的损失率.在系统应用中,该系统的功能模块满意度均在 90%以上.故此次研究提出的思政教育课程推荐系统可以良好地应用于线上教学课程推荐.
Abstract
With the rapid development of education forms,online Civics teaching has gradually become a common education mode.In order to improve the efficiency of online Civics education,this study improves the ID3 algorithm in decision tree classification algorithm by introducing information gain rate and importance parameters.The improved ID3 algorithm is then used to construct a civic education resource classification model,and a civic education course recommendation system is constructed based on the model.The experimental results show that the classification model of Civic Education under the improved ID3 algorithm can achieve 99.5%classification accuracy and 0.4%loss rate.In the application of the system,the satisfaction rate of the functional modules of the system is above 90%.Therefore,the Civic Education course recommendation system proposed in this study has good application value.
关键词
决策树/改进ID3算法/课程推荐/教学资源/思政教学Key words
decision tree/improved ID3 algorithm/classification/teaching resources/system design引用本文复制引用
基金项目
陕西教师发展研究计划重大项目(2022)(2022JSZD005)
陕西省教育科学规划课题(十四五)(2023)(SGH23Q0325)
出版年
2024
国家科技期刊平台
NSTL
万方数据