Hierarchic Principal Component Analysis Method for the Organization of Components Weights in Employment Process, from Employer Prospective Cover Image

Hierarchic Principal Component Analysis Method for the Organization of Components Weights in Employment Process, from Employer Prospective
Hierarchic Principal Component Analysis Method for the Organization of Components Weights in Employment Process, from Employer Prospective

Author(s): Adrian Vilcu, Mihaela Cojan, Ion Verzea
Subject(s): Social Sciences, Education, Higher Education
Published by: Carol I National Defence University Publishing House
Keywords: Principal Component Analysis method; hierarchized PCA; employability index; educational software; professional competence; technical competences; transversal competences; statistic modeling;

Summary/Abstract: The knowledge-based society and the evolutions that mark the Romanian economic and social context require from the graduates of technical higher education a series of specific and transversal competences that will provide them with the potential to adapt to rapid changes, short-term problems that arise in the flow of professional activities, critically analyzing data, correlating them with practical needs, working in parallel to multiple tasks, rapidly integrating into flexible working teams and constantly monitoring their career plan. The purpose of this exploratory study was to identify the general, specific and transversal professional competencies that contribute to increasing employability among Romanian higher education graduates. The study should be correlated with the changes in the labor market in the field of engineering, characterized by dynamism and competitiveness, as well as with the need to correlate the educational offer of the technical higher education with the local economic realities. This work responds to the need of an efficient correlation of educational offer with the present employers’ demands in terms of competences and professional, technical and transversal (behavior) performances, by optimizing the employability index using a software instrument based on hierarchically implemented Principal Component Analysis (PCA) method. Study structure is algorithmic: establish the participants in the study (employers), draw up the questionnaire for the three types of competences, validate it, organize statistically the gathered data, systemize them by using the hierarchic PCA method, extract the results and compare them with those from specialized literature. Finally, one proposes the software instrument and the valorization of the systemic analysis results at the main agents involved in the dynamics of educational and labor market: offers of educational and professional training programs, as well as graduates of high level studies.

  • Issue Year: 15/2019
  • Issue No: 03
  • Page Range: 444-450
  • Page Count: 7
  • Language: English
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