The Research Of The Knowledge Mining On The STRE Data

In the current, the Student Rating of Teaching Effectiveness is commonly used as Teaching quality management tools in China’s universities, it is also the hot issue which arosed a lot of dispute in the field of higher education research. Since the mid-1980s,our country has been carrying out the SRTE practice, and so far it has been implemented nearly30years, many universities have accumulated a plenty of SRTE data, but because of the lack of information awareness and lack of technology, the managers can only obtain some surface informations by simple sum and sorting operations. The informations hidden in these data are consistent with no further excavation.First of all, the thesis summarized the basic knowledge of data mining and introduced the classical association rules Apriori algorithm, the Partitioning Methods and the Hierarchical Methods of clustering, the correlation coefficient and so on.Then Iused these algorithms to study the SRTE data which is from one College of Tianjin Normal University and7semesters’SRTE data (under half the school year of2006-2007until2009-2010the next school year):Studying the10index in the teachers’teaching quality assessment card is to find the hidden relation between the10questions;using these algorithms is to want to see the relation between the SRTE and teachers’personal informations (title, degree, age, gender),then I design the corresponding questionnaire to verify the obtained conclusions. At last, the thesis summarized the conclusions and proposed relevant measures to improve the quality of our school teachers’teaching evaluation card, provide a quantifiable basis for our college further improves, promote the teaching quality evaluation and enhance the quality of teaching.