Journal of Physics Conference Series · 2019 · 12 citations · 12 references
ComputingComputer ScienceEducational TechnologyData MiningEducational Data MiningMachine LearningClassificationDecision TreesLearner Behavior AnalysisLearner ModelingSupport Vector MachinesBehavioral Feature ExtractionLearner Performance PredictionNaive BayesNaive Bayes ClassificationStudent Performance AnalysisStudent Performance AssessmentSupport Vector ClassificationSupport Vector Machine Classification
Abstract 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.
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Data mining: concepts and techniques
Jiawei Han, Micheline Kamber · Choice Reviews Online · 2012 · 28.9K citations