决策树分类算法在课程成绩预测中的应用  

Application of decision tree classification algorithm in course grade prediction

作　　者：杨丽萍[1] 郭宏升[2] Yang Liping;Guo Hongsheng(Information Science and Technology Department,Baotou Normal Institute,Baotou Neimenggu,014030;Politics and Law Department,Baotou Normal Institute,Baotou Neimenggu,014030)

机构地区：[1]包头师范学院信息科学与技术学院,内蒙古包头014030 [2]包头师范学院政治与法律学院,内蒙古包头014030

出　　处：《电子测试》2022年第17期56-58,共3页Electronic Test

基　　金：包头师范学院本科教学质量工程项目:校级重点建设课程“C语言程序设计”;2021年包头师范学院“专创融合”课程建设项目:“C语言程序设计”;2020年包头师范学院创新创业教育科学研究项目“创新创业教育与计算机专业教育深度融合的探索与实践(BSCY2020-03)”。

摘　　要：为了提高“C语言程序设计”课程的教学效果,本文采用2020学年度该课程教学中学生的课程学习数据以及期末考试成绩数据作为样本数据,采用决策树分类算法构造决策树分类器,并利用该决策树分类器对2021学年度该课程前期阶段学生的学习数据进行分类,来预测2021学年度学生该课程的考试通过情况,根据预测结果,对分类结果为不合格的学生在后期课程的教学中加强专项辅导,同时根据分类结果为不合格的学生所占的比例,适当调整教学方案,因材施教。In order to improve the teaching effect of the “C language programming” course,this paper uses the course learning data and final examination score data of the students learning the course in 2020 as the sample data,uses the decision tree classification algorithm to construct the decision tree classifier,and uses the decision tree classifier to classify the learning data of the students in the early stage of the course in 2021,To predict the students’ passing of the course in the 2021 academic year.According to the prediction results,strengthen special guidance for the students whose classification results are unqualified in the teaching of later courses.At the same time,adjust the teaching plan appropriately and teach students according to their aptitude according to the proportion of students whose classification results are unqualified.

关 键 词：样本数据 决策树分类器 成绩预测 学习数据 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]