In order to obtain effective information from accumulated data and make awards and punishments for teachers such as appointment, promotion, or bonus increase, and provide convincing basis for this decision, an evaluation model of higher mathematics teaching quality based on improved ID3 algorithm is proposed. This paper introduces the definition and classification of data mining, and introduces the ID3 algorithm of decision tree in detail. According to the ID3 algorithm, a large number of teaching evaluation data samples collected in colleges and universities are analyzed to obtain information gain on different attributes and generate the final decision tree, which can be converted into a set of if then rules. Generate rules and decision trees, and then analyze and predict the new data. The results show that A1 teaching content attribute is the most important in this evaluation system. From here, we can get a fair and objective evaluation. Secondly, teaching methods are also important indicators.