Modelling Accelerating Acquisition of Teamwork Competences with Transversal Competences and Artificial Intelligence
Modelling Accelerating Acquisition of Teamwork Competences with Transversal Competences and Artificial Intelligence

Summary/Abstract: Objective: The purpose of this paper was to develop a model for accelerating the acquisition ofthe selected transversal competence of teamwork. Based on data from four EU countries, fourmodels were developed and the best of them was selected, describing the results and variablesrelevant to that model.Research Design & Methods: Data on improving transversal competences were collected fromstudents in four countries, i.e. Poland, Slovakia, Slovenia and Finland. 26 variables were takeninto account in the modelling which was based on four methods. They included the MultipleLinear Regression Model, Multivariate Adaptive Regression Splines, Support Vector Machineand two Artificial Neural Network methods.Findings: The analyses show that the method of educating students and young employees, e.g.during training courses, can be a catalyst for accelerating teamwork competence acquisition.Other transversal competences including creativity, communicativeness and entrepreneurshipcorrelate positively with growth in teamwork competence.Implications / Recommendations: The study was conducted on an international group, alsotaking into account cross-cultural variables. However, to deepen the results, it is suggested thatthe sample size be increased and the research updated. The ranking of the education method isindicated to have an impact on the growth of transversal competences, including teamwork.Contribution: New approaches in the paper include the analytical approach to modelling thegrowth in teamwork competence in relation to many variables describing students and youngworkers in the labour market in the UE. The use of multiple analytical and statistical methodsallows the most fitting model to be selected and the error to be minimised.

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