دانلود رایگان مقاله بررسی کارایی دانشگاه مکزیک یکپارچه سازی تحلیل داده مقیاس چند بعدی

Abstract

 National policy initiatives require the expenditure of large amounts of resources over several years. It is common for these initiatives to generate large amounts of data that are needed in order to assess their success. Educational policies are an obvious example. Here we concentrate on Mexico's “Educational Modernisation Programme” and try to see how this plan has affected efficiency in teaching and research at Mexico's universities. We use a combined approach that includes traditional ratios together with Data Envelopment Analysis models. This mixture allows us to assess changes in efficiency at each individual university and explore if these changes are related to teaching, to research, or to both. Using official statistics for 55 universities over a six year period (2007–2012), we have generated 12 ratios and estimated 21 DEA models under different definitions of efficiency. In order to make the results of the analysis accessible to the non-specialist we use models that visualise the main characteristics of the data, in particular scaling models of multivariate statistical analysis. Scaling models highlight the important aspects of the information contained in the data. Because the data is three-way (variables, universities, and years) we have chosen the Individual Differences Scaling model of Carroll and Chang. We complete the paper with a discussion of efficiency evolution in three universities.

7. Conclusions and discussion

Governments spend large amounts of resources for the promotion of common good. A good example is education. Large amounts of data, in the form of official statistics, are collected in order to assess the success or otherwise of national policies. There is a need to analyse this data in a form that can be understood by individuals who are not conversant with the intricacies of mathematical statistics. Starting in 1989, Mexico has made a great effort in order to improve the quality and quantity of university education. In this paper we have asked the question of whether, on the basis of official statistics, we can assess if the extra resources have also improved the efficiency with which universities deliver their joint products of teaching and research. This is to say: are resources better employed? Clearly, this question needs to be answered university by university, since each institution has different ways of planning and decision making. We have developed a methodology that combines DEA and scaling in the production of statistical maps to reveal at a glance how a university has evolved in this efficiency framework.