Open AccessWhich Factors Have the Greatest Impact on Student’s Performance
Author(s) -
Li Feng,
Yu Zhang,
Mo Chen,
Kening Gao
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1288/1/012077
Subject(s) - support vector machine , decision tree , computer science , artificial intelligence , machine learning , artificial neural network , feature (linguistics) , classifier (uml) , naive bayes classifier , bayesian network , educational data mining , data mining , data science , philosophy , linguistics
Nowadays, a great deal of educational data has been produced by E-learning system and MOOC. Educational data is important for Teaching and research. These educational data can be classified many kinds of feature, such as demographic features, social features and behavioral features. And which feature is the most import for student’s performance? In this paper, In this paper, we use some common data mining technologies including Naïve Bayesian(NB), Artificial Neural Network(ANN), Support Vector Machine(SVM) and Decision Tree Classifier(DT) to predict students’ performance, and try to find out the influence of characteristics on students’ academic performance. From the conclusion, we can see that SVM technique outperform others, and Behavioral Features have good effect on students’ performance.