Student evaluation of teaching would be fruitful only when it leads to an enhancement in teaching. Using basic statistics, classifications and regression trees to measure student satisfaction, and association rules to mine data and text, we develop an effective feedback system to analyze student evaluations and provide their results to concerned faculties. The system provides faculties with information they may use for further improvement of their teaching. An opinion survey conducted among the faculties who used the feedback system revealed that, by and large, the system was perceived to be useful towards class improvement. Moreover, the function employing the association rule for free descriptions was considered to be an effective tool for enhancing education. The binary tree analysis, on the other hand, did not receive a high appraisal on account of the presentation of the result and the fact that the teachers were not familiar with the concept. Given that the evaluation questions addressing visibility and understandability were scored relatively lower, the system will be improved in the near future through a modification to its interface.