决策树算法在高校教学中的应用研究  

Research on the Application of Decision Tree Algorithm in University Teaching

作　　者：虞烨青 朱子怡 许新华 李逸雪 许超焕 YU Ye-qing;ZHU Zi-yi;XU Xin-hua;LI Yi-xue;XU Chao-huan(School of Computer and Information Engineering,Hubei Normal University,Huangshi 435002,China)

机构地区：[1]湖北师范大学计算机与信息工程学院,湖北黄石435002

出　　处：《电脑与信息技术》2025年第1期152-156,共5页Computer and Information Technology

基　　金：湖北师范大学2024年研究生创新科研项目(No.2024Y034)。

摘　　要：为了解决高校教师开课前未能充分了解学生导致不能设计个性化教学和深度互动活动的问题,利用决策树算法对H师范大学50名本科生的课程成绩进行处理,构建教育技术与媒体课程成绩等级预测模型,帮助教师根据学生预测成绩进行同质分组和异质分组。研究发现,决策树算法在高校中的应用包括预测、分类、推荐和辅助教育决策,这4种数据处理方法中仅将目标课程成绩按分数段分类得到的决策树模型性能最优。To address the issue that university teachers cannot design personalized teaching and in-depth interactive activities due to insufficient understanding of students before the start of a course,the decision tree algorithm was used to process the course grades of 50 undergraduate students at H Normal University,and a grade level prediction model for the educational technology and media course was constructed to assist teachers in homogeneous and heterogeneous grouping based on students'predicted grades.The study found that the application of decision tree algorithms in universities included prediction,classification,recommendation,and assistance in educational decision-making.Among the four data processing methods,the decision tree model that classifies the target course grades by score segments performed the best.

关 键 词：决策树 成绩预测 学生分类 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]