A Support Vector Regression-Based Prediction of Students´ School Performance

The relationship between a person´s personality and performance has long been studied by psychologists. Research suggests that a person´s performance and behavior are related to personality characteristics and background data to a certain degree. In this paper, the Big Five personality model is adopted for measuring profiles of students, whose undergraduate performance and behavior are then analyzed. A machine learning approach, support vector regression (SVR), is employed to find correlations from the given sample data. The performance and behavior of a person are predicted from the obtained regression values. Personality, biological, performance, and behavior data of 120 undergraduates in Taiwan were collected through questionnaires. Ninety valid data samples are used for training in SVR and the others are used for evaluating the regression predictions. Most of the predicted performance yielded near 80% accuracy. It is shown that there are correlations between a person´s performance and personality characteristics. SVR is shown to be a suitable method for exploring personality correlations.