Evaluation of overseas students´ performance in Chinese courses using statistical learning

It is necessary to evaluate overseas students´ performance in courses learning, which is closely associated with university-level management. In this work, based on supervised statistical learning, the training set includes overseas students´ marks written on their assignments, and some other attributes. Nowadays, combining different classifiers is proposed as a new direction for the improvement of the classification accuracy. Therefore we adopt such strategy to construct the whole classification system which includes Support Vector Machine, Artificial Neural Network and Binary Decision Tree, using the voting methodology. Among other significant conclusions it was found that the proposed algorithm is appropriate to be used for the construction of a software support tool.