Research on Student Performance Evaluation Based on Random Forest

Abstract

The evaluation of student performance provides scientific decision-making basis for educational institutions, which is helpful to the improvement of teaching quality. In this paper, the Gini index was used to sort the importance of factors affect student performance and the Random Forest was used to predict the student performance. Experiment results show that the prediction accuracy reaches 83.82%. Experimental results can guide students to targeted learning and instruct teachers to strengthen the corresponding teaching.