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Structural Equation Models and Student Evaluation of Teaching: A PLS Path Modeling Study

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Statistical Methods for the Evaluation of University Systems

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

In Italian universities, teaching evaluation is in part based on students judgments concerning aspects related to courses and considered of preeminent interest for university management. A questionnaire is generally used to collect such data. The students judgments are expressed as a score on an ordinal scale.

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References

  1. Aiello F, Attanasio M (2004) How to transform a batch of simple indicators to make up a unique one. In: Atti della XLIII Riunione Scientifica della SIS, Padova, pp 327–338

    Google Scholar 

  2. Amato S, Esposito Vinzi V, Tenenhaus M (2005) A global goodness-of-fit index for PLS structural equation modeling. Technical report HEC School of Management, France

    Google Scholar 

  3. Bollen KA (1989) Structural equations with latent variables. Wiley, New York, NY

    Google Scholar 

  4. Balzano S, Trinchera L (2008) Structural equation models and student evaluation of teaching: a PLS approach. In: Atti del convegno DIVAGO, Palermo

    Google Scholar 

  5. Capursi V, Porcu M (2001) La didattica universitaria valutata dagli studenti: un indicatore basato su misure di distanza fra distribuzioni di giudizi. In: Atti Convegno Intermedio della Società Italiana di Statistica “Processi e Metodi Statistici di Valuatzione”, Rome

    Google Scholar 

  6. Chiandotto B, Bini M, Bertaccini B (2006) Evaluating the quality of the university educational process: an application of the ECSI model. In: Fabbris L (ed) Effectiveness of university education in Italy: employability, competences, human capital. Springer, Heidelberg

    Google Scholar 

  7. Chin WW (1998) The partial least squares approach to structural equation modeling. In: Marcoulides GA (ed) Modern methods for business research. Lawrence Erlbaum Associates, Mahwah, NJ, pp 295–336

    Google Scholar 

  8. CNVSU – Comitato Nazionale per la Valutazione del Sistema Universitario (2007) Note tecniche su dati ed informazioni per la Rilevazione Nuclei 2007, DOC 3/07

    Google Scholar 

  9. Efron B, Tibshirani RJ (1993) An introduction to the bootstrap. Chapman and Hall, New York, NY

    Google Scholar 

  10. Esposito Vinzi V, Trinchera L, Squillacciotti S, Tenenhaus M (2008) REBUSPLS: A response-based procedure for detecting unit segments in PLS path modeling. Appl Stochastic Models Bus Ind (ASMBI) 24:439–458

    Article  Google Scholar 

  11. Grilli L, Rampichini C (2007) Multilevel factor models for ordinal variables. Struct Equ Modeling 14(1):1–25

    Article  Google Scholar 

  12. Guolla M (1999) Assessing the teaching quality to student satisfaction relationship: applied customer satisfaction research in the classroom. J Mark Theory Pract 7(3):87–98

    Google Scholar 

  13. Hahn C, Johnson M, Herrmann A, Huber F (2002). Capturing customer heterogeneity using a finite mixture PLS approach. Schmalenbach Bus Rev 54:243–269

    Google Scholar 

  14. Jöreskog KG, Sörbom D (1979) Advances in factor analysis and structural equation models. Abstract Books, Cambridge, MA

    Google Scholar 

  15. Lovaglio PG (2002) La stima di variabili latenti da variabili osservate miste. Statistica LXII 2:203–213

    Google Scholar 

  16. Martensen A, Gronholdt L, Eskildsen JK, Kristensen K (2000) Measuring student oriented quality in higher education: application of the ECSI methodology. Sinergie Rapporti di Ricerca 9:372–383

    Google Scholar 

  17. Nardo M, Saisana M, Saltelli A, Tarantola S, Hoffman A, Giovannini E (2005) Handbook on constructing composite indicators: methodology and user guide. OECD statistics working paper

    Google Scholar 

  18. Ramipichini C, Grilli L, Petrucci A (2004) Analysis of university course evaluations: from descriptive measures to multilevel models. Stat Methods Appt 13(3):357–373

    Google Scholar 

  19. Tenenhaus M (2008) Component-based structural equation modelling. Total Qual Manage Bus Excel 19(7):871–886

    Article  Google Scholar 

  20. Tenenhaus M, Esposito Vinzi V, Chatelin YM, Lauro NC (2005) PLS path modeling. Comput Stat Data Anal 48:159–205

    Article  Google Scholar 

  21. Trinchera L (2007) Unobserved heterogeneity in structural equation models: a new approach in latent class detection in PLS path modeling. PhD thesis, DMS, University of Naples

    Google Scholar 

  22. Trinchera L, Russolillo G (2009) Role and treatment of categorical variables in PLS path models for composite indicators. In Esposito Vinzi V, Tenenhaus M, Guan R (eds) Proceedings of the 6th international conference on partial least squares and related methods, pp 23–27, PHEI, ISBN: 978-7-121-09342-5

    Google Scholar 

  23. Werts CE, Linn RL, Jöreskog KG (1974) Intraclass reliability estimates: testing structural assumptions. Educ Psychol Meas 34(1):25–33

    Article  Google Scholar 

  24. Wold H (1982) Soft modeling: the basic design and some extensions. In: Jöreskog KG, Wold H (eds) Systems under indirect observation, Part 2. North-Holland, Amsterdam, pp 1–54

    Google Scholar 

  25. XLSTAT (2009) Addinsoft, Paris, France (www.xlstat.com)

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Correspondence to Simona Balzano .

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Balzano, S., Trinchera, L. (2011). Structural Equation Models and Student Evaluation of Teaching: A PLS Path Modeling Study. In: Attanasio, M., Capursi, V. (eds) Statistical Methods for the Evaluation of University Systems. Contributions to Statistics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2375-2_4

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