MACRO-COMPETENCIES DETECTION FOR THE EXCELLENT PROFESSIONAL IN BISCAY
University of The Basque Country (UPV/EHU) (SPAIN)
About this paper:
Appears in:
EDULEARN15 Proceedings
Publication year: 2015
Pages: 3087-3095
ISBN: 978-84-606-8243-1
ISSN: 2340-1117
Conference name: 7th International Conference on Education and New Learning Technologies
Dates: 6-8 July, 2015
Location: Barcelona, Spain
Abstract:
The present research work tries to identify the basic crosscurricular competencies for Biscay’s professionals to achieve the excellence in their current activity in any sector. In this way, the identification made will allow us to meet the abilities, attitudes and values needed for both leading the organizations’ transformation processes in the XXI century and establishing the genuine training and learning needs to adequate university education to society´s demand.
The methodology used in the different stages of this study has been qualitative (group dynamics) and also quantitative (telephone surveys and after statistical analysis). It has been carried out a quote sampling, in which the selected sample was composed by people registered in the professional associations of “BasquePRO Elkargoak”: doctors, lawyers, industrial engineering technicians, industrial engineers, psychologists, mining engineering technicians, civil engineers, social workers, biologists, physics and topographers.
With the statistically representative population sample selected we have obtained 519 valid surveys, which means that for a universe of 30.563 registered people in the associations, with a 95,45% confidence interval and P=Q=50% observations, there is an error of 4,36% for the study.
From the initial univariate analysis it is extracted that there are interdependent values, skills and attitudes, so it brought the idea for a multivariate analysis, in order to try to reduce the number of questioned competencies in a smaller group of dimensions (factors), with a minimum loss of reliability. Thus, a multivariate statistical analysis will be applied using an exploratory factor analysis carried out with SPSS (statistical software for social science). More specifically, we used principal components analysis method with Varimax rotation, because it helps to simplify the factorial structure and usually it defines more significant factors.
The most remarkable conclusion from the univariate analysis is the difference between the women´s profile and the general profile. In this sense, the attitude of “having the capabilities of self-criticism, analysis and improvement of professional labour” and the skills such as “having the ability of analyse and synthesize to communicate the essential interpreting macro and micro contexts” appeared.
There is also a great discrepancy with the group aged more than 65, in which only appeared one ability containing “commitment with the project, generating confidence, motivation and illusion in their professional environment”, “avoidance of the fear of making mistakes, admitting others’ criticisms and learning to learn from mistakes” and knowledge like “use of new technologies, but believing that they are just a tool, not the solution for the problem”.
Finally, the multivariate analysis allows the classification of the obtained factors into macrocompetencies to encompass the investigated competencies with the surveys and to originate a unique competency of superior level due to the convergence of its components, because it is observed that the probability of when one of the variables of the macrocompetence varies, the rest of the variables will also vary is high.Keywords:
Macrocompetencies, Multivariate analysis, Higher education, Professional skills.