Student questionnaire analyses for class management by text mining both in Japanese and in Chinese

By combining statistical analyses and information retrieval techniques, an efficient way for knowledge discovery from questionnaires is discussed. Since usual questionnaires include questions answered by a fixed format and those by a free format, it is important to introduce the methods by both data mining and text mining. The answers by the fixed format are called "items", and those by the free format, simply "texts". In this paper, using an algorithm for processing answers with both the items and the texts and that for extracting important sentences from texts combined with statistical techniques, a method for analyzing the questionnaires is established. The method is applied to a case of improvements for the quality of education by which the student questionnaire is executed to a class, and we obtain useful knowledge which leads to faculty development.