Application of data mining for the classification of university programs of industrial engineering accredited in high quality in Colombia

Abstract

The present research article proposes a method to classify University engineering programs, placing special attention to relations between the subjects of the curriculum and the 12 areas of knowledge established in the body of competencies published by the Institute of industrial and System Engineers (IIES). Techniques of unsupervised data analysis such as Principal Components Analysis (PCA) and cluster analysis were used for the proposed classification. Twenty-one programs, accredited by high quality in Industrial Engineering in Colombia, are used as units of study. The results show that factors such as international accreditation, size of the faculties of engineering and University profile, influence the grouping of the programs of study. The research allowed to classify three large main components and profiles of accredited programs.