Multivariate analysis for students' evaluation of teaching effectiveness in teleinformatics engineering

In this work, we propose the use a multivariate analysis tool, called principal components analysis (PCA), to address the problem of Students' Evaluation of Teaching Effectiveness (SETE). We conducted a research with Engineering Students in an undergraduate course. The values obtained after collecting research data were transformed from a 3D array to a 2D array performing an average of students' responses. The PCA was applied in order to take same intrinsic information of the dataset collected. The Cronbach's α validates the PCA application in the dataset. The results show that our study allows an analysis of how students perceive different disciplines about different criteria, which may serve as an indicator for an educational assessment area.