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

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.