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A Composite Indicator for University Quality Assesment: The Case of Spanish Higher Education System

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Abstract

This study presents a synthetic indicator for quality assessment in the Spanish public university system. The indicator is based on a series of components and simple indicators that were obtained from the public universities’ financial planning estimates. The paper takes a quantitative, wide-ranging approach to analyse the quality of university institutions and is intended to be complimentary to other qualitative approaches. Data Envelopment Analysis was used in order to facilitate the aggregation and weighting of the data used to construct the synthetic indicator. This technique allows the analyst to endogenously determine the weighting of the partial indicators while respecting the peculiarities intrinsic to each university. The results reveal that there are significant differences among Spanish public universities. In addition to how relatively well each of the institutions performs, other factors would seem to be influencing the results; essentially these are related to socio-economic factors and to the application of university policy in Spain over recent decades.

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Notes

  1. Ley Orgánica 6/2001 de Universidades, de 21 de Diciembre (B.O.E. de 24 de Diciembre)

  2. Some of the financial planning estimates revised for this paper regarded the Autonomous regions of Comunidad Valenciana, Canarias or a proposal for Galicia (Fernández 2001)

  3. A further recent example of the application of the systemic perspective of higher education may be found in Brown (1999).

  4. The abstract nature via which the general goals of higher education are normally formulated make it difficult for the concept of quality as functionality to be operationalized.

  5. In general, these objectives are common to university institutions from any other country, particularly those within the EU. Hence, the model is may be easily adapted in order to utilise data relevant to different contexts.

  6. The elaboration and analysis of this paper drew on the collaboration of scholars, researchers and managemers of the University of Santiago de Compostela as well as of other public universities in Spain.

  7. DEA facilitates the efficiency estimation of organizations within production contexts characterized by multiple inputs and outputs. Developed after Farrell (1957) and Charnes et al. (1978), the technique has been used extensively to investigate performance in the public sector. The origins of DEA can be explored in Forsund and Sarafoglou (2002) and a discussion on the technique itself and its potential applications can be found in Charnes et al. (1993) and more briefly in Boussofiane et al. (1991).

  8. It is assumed that all of the indicators should be as high as possible, and thus an output-oriented DEA is used. An input oriented DEA would have been more suitable if the converse had been true, that is, if the partial indicators were preferred to be as low as possible.

  9. For more about radial DEA models without inputs or outputs, see Lovell and Pastor (1999).

  10. See for example, Bessent et al. (1982).

  11. On registering for a degree a student is obliged to state his 5 degree preferences. Places on the degree are assigned in accordance with the student’s marks at school i.e. those marks that constitute the student’s grade average.

  12. Exchange students are considered to be, both, those students that travel abroad from Spain and foreign students on exchange programmes from abroad.

  13. Similar indicators (overseas students) appear in Sarrico et al. (1997).

  14. Beasley (1995) uses the number of postgraduates on taught courses in order to compare university departments.

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Correspondence to Pilar Murias.

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Murias, P., de Miguel, J.C. & Rodríguez, D. A Composite Indicator for University Quality Assesment: The Case of Spanish Higher Education System. Soc Indic Res 89, 129–146 (2008). https://doi.org/10.1007/s11205-007-9226-z

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