The dynamic TAN classifier for teacher comprehensive quality assessment

Teacher comprehensive quality assessment is an important way of teacher management in universities. At present, the method of weighted sum of indexes is used for teacher comprehensive quality assessment. In this method, timing history information and dependency information between indexes can not be effectively utilized. In this paper, the method of dynamic TAN classifier is presented for teacher comprehensive quality assessment. Timing history information and dependency information between indicators can be effectively used in the method. Experimental results show that dynamic TAN classifier is more reliable than other dynamic Bayesian network classifiers in assessment prediction.