机器学习在学生课程评价分类中的应用

Application of Machine Learning in Classification of Student Course Evaluation

对教育大数据进行挖掘,可以得到很多有用的信息以此来指导学生、教师改进学习或教学.文章利用公开的Turkiye Student Evaluation数据集,通过使用经典的机器学习算法来预测学生对课程的喜爱程度,并得出对预测结果最相关的一些因素,以便于教师对课程进行改进.此外,文章还使用图卷积网络来探究可能存在密切联系的学生间的交互对评价结果的影响.

Mining education big data can obtain many useful information to guide students and teachers to improve learning and teaching.This paper uses the open Turkiye Student Evaluation data set and classical machine learning algorithm to predict students’preference for the curriculum,and obtains factors most relevant to the predicted results,so as to facilitate teachers to improve the curriculum.In addition,this paper also uses the graph convolution network to explore whether the interaction between students may have an impact on the evaluation results.