Research of higher engineering education quality on the base of students Interviewing data by nonlinear principal components analysis (NLPCA)
The paper explores a suitability of higher education quality measurement from student’s point of view, and analyses results of interviewing of students from engineering specialties in Perm universities. Nonlinear Principal Components Analysis (NLPCA) in interpretation of Gifi system was used as the tool for data processing. It takes into account a dissimilar statistical nature of questionnaire indicators. The method can be very promising for various socio-economic researches.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Voss, Roediger & Gruber, Thorsten & Szmigin, Isabelle, 2007. "Service quality in higher education: The role of student expectations," Journal of Business Research, Elsevier, vol. 60(9), pages 949-959, September.
- Francesco Lagona & Fabio Padovano, 2007. "A nonlinear principal component analysis of the relationship between budget rules and fiscal performance in the European Union," Public Choice, Springer, vol. 130(3), pages 401-436, March.
When requesting a correction, please mention this item's handle: RePEc:ris:apltrx:0014. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Anatoly Peresetsky)
If references are entirely missing, you can add them using this form.