Intelligent decision system for accessing academic performance of candidates for early admission to university

Abstract

With the promotion of Early Admission (EA) among the universities in China, its prediction accuracy of the potential of the students with regard to their academic performance is highly concerned. In this study, the statistical methods and the artificial intelligence technologies were used comparatively to build the prediction models. According to our best knowledge, this is the first time that a model is established to evaluate student candidates for admission to the university. We carried out a comparison of the current EA system based on the real admission data from a reputed university with typical EA procedures. The results show that prediction capability of EA is improved significantly with the help of the models. Afterwards, the impact of predictors was discussed and presented.