Principal component clustering approach to teaching quality discriminant analysis

Abstract

Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students’ evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET by clustering the result of extracting the indexes through the principal component analysis (PCA), then we also test the rationality of the rating using Fisher’s discriminant function. Finally, the model and algorithm are proved to be effective and objective according to the empirical analysis.

Keywords

• principal component analysis
• clustering analysis
• discriminant analysis
• students’ evaluation of teaching
• index system