Applying Data Driven Decision Making to rank Vocational and Educational Training Programs with TOPSIS

TL;DR

A multi-criteria classification of Vocational and Educational Programs in Extremadura (Spain) during the period 2009-2016 is presented and it is compared to a well known global sensitivity analysis technique based on the Pearson's correlation ratio.

Abstract

In this paper we present a multi-criteria classification of Vocational and Educational Programs in Extremadura (Spain) during the period 2009-2016. This ranking has been carried out through the integration into a complete database of the detailed information of individuals finishing such studies together with their labor data. The multicriteria method used is TOPSIS together with a new decision support method for assessing the influence of each criterion and its dependence on the weights assigned to them. This new method is based on a worst-best case scenario analysis and it is compared to a well known global sensitivity analysis technique based on the Pearson's correlation ratio.

Figures (7)

• Figure 1: Data Warehouse Schema.
• Figure 2: Number of total VET programs available each year (dashed blue line) and number of VET programs with all criteria computed as medians of more then 5 data (solid red line). The horizontal dashed line shows the minimum number of programs considered for the ranking.
• Figure 3: Evolution of the general performance at each criterion in the period 2009-2016.
• Figure 4: VET programs ranking throughout the period 2009-2016. The colour reflects the percentile of each program at each year (the greener the better) and the overall sorting has been done according to the average percentile of each program during the whole time span.
• Figure 5: Mean percentile of the VET programs in each professional families (solid line), minimum and maximum percentiles (dashed lines) and number of VET programs considered each year (gray bars).