An Integrated Statistical Model to Measure Academic Teaching Quality
ABSTRACT
The aim of this paper is to present a new proposal for the classification of Academic institutions in terms of quality of teaching. Our methodological proposal borrows concepts from operational risk, such as scorecard models, employed to assess University performances, on the basis of both the perceived and the actual quality. We propose to summarize opinion data using new non parametric indexes able to exploit efficiently the ordinal nature of the analysed variables and to integrate different sources of data. In particular we show how web survey methods can improve the quality and robustness of collected data, especially when integrated with students career data. Empirical evidence is given on the basis of real data from the University of Pavia.
The aim of this paper is to present a new proposal for the classification of Academic institutions in terms of quality of teaching. Our methodological proposal borrows concepts from operational risk, such as scorecard models, employed to assess University performances, on the basis of both the perceived and the actual quality. We propose to summarize opinion data using new non parametric indexes able to exploit efficiently the ordinal nature of the analysed variables and to integrate different sources of data. In particular we show how web survey methods can improve the quality and robustness of collected data, especially when integrated with students career data. Empirical evidence is given on the basis of real data from the University of Pavia.
Cite this paper
P. Cerchiello and P. Giudici, "An Integrated Statistical Model to Measure Academic Teaching Quality," Open Journal of Statistics, Vol. 2 No. 5, 2012, pp. 491-497. doi: 10.4236/ojs.2012.25063.
P. Cerchiello and P. Giudici, "An Integrated Statistical Model to Measure Academic Teaching Quality," Open Journal of Statistics, Vol. 2 No. 5, 2012, pp. 491-497. doi: 10.4236/ojs.2012.25063.
References
[1] N. C. Liu, “The Story of the Academic Rankig of World Universities,” International Higher Education, Vol. 54, 2009, pp. 2-3. [2] D. Jobbins, “Global Rankings: Thousands Respond to the Survey,” 2010. http://www.universityworldnews.com/article.php? story=20100617192654650 [3] M. Cruz, “Modelling, Measuring and Hedging Operational Risk,” John Wiley and Sons, Chichester, 2002. [4] C. Alexander, “Regulation, Analysis and Management,” Financial Times, Prentice Hall, Upper Saddle River, 2003. [5] J. King, “Operational Risk. Measurement and Modelling,” John Wiley and Sons, Chichester, 2001. [6] E. C. Bonafede, P. Cerchiello and P. Giudici, “Statistical models for Business Continuity Management,” Journal of Operational Risk, Vol. 2, No. 4, 2007, pp. 79-96. [7] P. Cerchiello, P. Dequarti, P. Giudici and C. Magni, “Scorecard Models to Evaluate Perceived Quality of Academic Teaching,” Statistica & Applicazioni, Vol. 2, 2010, pp.145-156. [8] P. Giudici, “Governo dei Rischi: Il Ruolo dei Modelli Statistici,” Isituto Lombardo (Rendiconti), Vol. 141, 2007, pp. 361-376. [9] P. Cerchiello and P. Giudici, “Fuzzy Methods for Variable Selection in Operational Risk Management,” Journal of Operational Risk, Vol. 7, No. 4, 2012, pp. 1-17. [10] P. Cerchiello and P. Giudici, “On the Distribution of Functionals of Discrete Ordinal Variables, Statistics and Probability Letters, Vol. 82, No. 11, 2012, pp. 2044- 2049. [11] P. Cerchiello, “Statistical Models to Measure Corporate Reputation,” Journal of Applied Quantitative Methods, Vol. 6, No. 4, 2011, pp. 58-71.
[1] N. C. Liu, “The Story of the Academic Rankig of World Universities,” International Higher Education, Vol. 54, 2009, pp. 2-3. [2] D. Jobbins, “Global Rankings: Thousands Respond to the Survey,” 2010. http://www.universityworldnews.com/article.php? story=20100617192654650 [3] M. Cruz, “Modelling, Measuring and Hedging Operational Risk,” John Wiley and Sons, Chichester, 2002. [4] C. Alexander, “Regulation, Analysis and Management,” Financial Times, Prentice Hall, Upper Saddle River, 2003. [5] J. King, “Operational Risk. Measurement and Modelling,” John Wiley and Sons, Chichester, 2001. [6] E. C. Bonafede, P. Cerchiello and P. Giudici, “Statistical models for Business Continuity Management,” Journal of Operational Risk, Vol. 2, No. 4, 2007, pp. 79-96. [7] P. Cerchiello, P. Dequarti, P. Giudici and C. Magni, “Scorecard Models to Evaluate Perceived Quality of Academic Teaching,” Statistica & Applicazioni, Vol. 2, 2010, pp.145-156. [8] P. Giudici, “Governo dei Rischi: Il Ruolo dei Modelli Statistici,” Isituto Lombardo (Rendiconti), Vol. 141, 2007, pp. 361-376. [9] P. Cerchiello and P. Giudici, “Fuzzy Methods for Variable Selection in Operational Risk Management,” Journal of Operational Risk, Vol. 7, No. 4, 2012, pp. 1-17. [10] P. Cerchiello and P. Giudici, “On the Distribution of Functionals of Discrete Ordinal Variables, Statistics and Probability Letters, Vol. 82, No. 11, 2012, pp. 2044- 2049. [11] P. Cerchiello, “Statistical Models to Measure Corporate Reputation,” Journal of Applied Quantitative Methods, Vol. 6, No. 4, 2011, pp. 58-71.