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A system for relevance analysis of performance indicators in higher education using Bayesian networks

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Abstract

In this paper, we propose a methodology for relevance analysis of performance indicators in higher education based on the use of Bayesian networks. These graphical models provide, at first glance, a snapshot of the relevant relationships among the variables under consideration. We analyse the behaviour of the proposed methodology in a practical case, showing that it is a useful tool to help decision making when elaborating policies based on performance indicators. The methodology has been implemented in a software that interacts with the Elvira package for graphical models, and that is available to the administration board at the University of Almería (Spain) through a web interface. The software also implements a new method for constructing composite indicators by using a Bayesian network regression model.

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Authors and Affiliations

  1. Department of Statistics and Applied Mathematics, University of Almería, 04120, Almería, Spain

    Antonio Fernández, María Morales, Carmelo Rodríguez & Antonio Salmerón

Authors
  1. Antonio Fernández
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  2. María Morales
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  3. Carmelo Rodríguez
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  4. Antonio Salmerón
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Corresponding author

Correspondence to Antonio Salmerón.

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Fernández, A., Morales, M., Rodríguez, C. et al. A system for relevance analysis of performance indicators in higher education using Bayesian networks. Knowl Inf Syst 27, 327–344 (2011). https://doi.org/10.1007/s10115-010-0297-9

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  • DOI: https://doi.org/10.1007/s10115-010-0297-9

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