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Student model is a very important and time-consuming process in intelligent tutoring system. Furthermore, for many Web based educational systems, student personality is hard to apply explicitly. To address this problem, we proposed an approach for combining fuzzy compositive evaluation with Bayesian network to design an applied student model. This article describes improvements made to the method and its application to make corresponding tutoring strategy by reasoning student action that supports useful tutoring services in a practical tutoring system. The proposed framework has been integrated within the discrete mathematics tutor system. We obtain results of an experiment that shows the benefit of the integration of the way.