Abstract
The evaluation of the effectiveness of higher education is a crucial aspect of competitiveness of modern economies. In this contribution we investigate the quality and effectiveness of higher education in Italy using a structural equation model; in particular, we evaluate the performance of the university system from the users’ point of view, both immediately following (internal effectiveness), and one year after (external effectiveness), the completion of the degree. The model allows the construction of synthetic indexes and hence the ranking of study programs.
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Notes
- 1.
TLI and RMSEA are fit indexes both varying in [0, 1]. Values greater than 0.95 for the first one and value less than 0.06 for the second one are evidence of a good fitting to the data. For a brief review of the fit indexes see Hox and Bechger (1998).
- 2.
Since the available data have a hierarchical structure (students at the first level are nested in study programs or in universities), multilevel techniques could be used to take into account the hierarchical structure of the data and obtain the latent factor scores of the second level units. In this work, multilevel techniques for structural equation models (Skrondal and Rabe-Hesketh 2004) are not feasible with the available software because of the high number of latent variables involved in the model.
References
Bartholomew, D. J., & Knott, M. (1999). Latent variable models and factor analysis. London: Arnold.
Bayol, M. P., de la Foye, A., Tellier, C., & Tenenhaus, M. (2000). Use of PLS path modelling to estimate the European consumer satisfaction index (ECSI) model. Statistica Applicata, 12, 361–375.
Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
Chiandotto, B. (2004). Sulla misura della qualitá della formazione universitaria. Studi e note di Economia, 3, 27–61.
Chiandotto, B., Bini, M., & Bertaccini, B. (2007). Quality assessment of the University Educational Process: An application of the ECSI model. In Effectiveness of the University Education in Italy. Heidelberg: Physica.
Draper, D., & Gittoes, M. (2004). Statistical analysis of performance indicators in UK higher education. Journal of the Royal Statistical Society A, 167(3), 449–474.
ECSI Technical Committee. (1998). European customer satisfaction index: Foundation and structure for harmonized national pilot projects. Report prepared for the ECSI Steering Committee.
Eskildsen, J. K., Martensen, A., Gronholdt, L., & Kristensen, K. (2000). Benchmarking student satisfaction in higher education based on the ECSI methodology. Sinergie Rapporti di Ricerca, 9, 385–400.
Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. Journal of Marketing, 56, 6–22.
Hox, J. J., & Bechger, T. M. (1998). An introduction to structural equation modeling. Family Science Review, 11, 354–373.
Lockheed, M. E., & Hanushek, E. R. (1994). Concepts of educational efficiency and effectiveness. In T. Husen & T. N. Postlethwaite (Eds.), International encyclopedia of education (pp. 1779–1784). Oxford: Pergamon.
Martensen, A., Gronholdt, L., Eskildsen, J. K., & Kristensen, K. (2000). Measuring student oriented quality in higher education: Application of the ECSI methodology. Sinergie Rapporti di Ricerca, 9, 371–383.
Muthén, L. K., & Muthén, B. O. (1998–2007). Mplus users guide (5th edition). Los Angeles, CA: Muthén and Muthén.
O’Loughlin C., & Coenders G. (2002). Application of the European customer satisfaction index to postal services. Structural equation models versus partial least squares. Departament d’Economia, Universitat de Girona.
Pearl, J. (2000). Causality: Models, reasoning, and inference. New York: Cambridge University Press.
Skrondal, A., & Rabe-Hesketh, S. (2004). Generalized latent variable modeling Anders. Boca Raton: Chapman and Hall.
Spirtes, P., Glymour, C., & Scheines, R. (2000). Causation, prediction and search (2nd edition). Massachusetts, CA: The MIT press.
Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 48, 159–205.
Wold, H. (1985). Partial least squares. In S. Kotz & N. L. Johnson (Eds.), Encyclopedia of statistical sciences (Vol. 6, pp. 581–591). New York: Wiley.
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Chiandotto, B., Bertaccini, B., Varriale, R. (2010). The Effectiveness of University Education: A Structural Equation Model. In: Palumbo, F., Lauro, C., Greenacre, M. (eds) Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03739-9_25
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