Management Sciences

Statistical Evaluation of University Student’s Motivation and Personal Competency with Principal Component and Cluster Analysis

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December 12, 2017
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Nagy, R., & Balogh, P. (2017). Statistical Evaluation of University Student’s Motivation and Personal Competency with Principal Component and Cluster Analysis. International Journal of Engineering and Management Sciences, 2(4), 365-374. https://doi.org/10.21791/IJEMS.2017.4.29.
Abstract

The aim of the research is to do a statistical evaluation of agricultural and rural development engineer student’s motivation and personal competency. It sums up the late generation Y’s characteristics and challenges. To be a successful, graduated employee, not only the skill is needed but the personal competency as well. Altogether, 121 filled out questionnaires were collected from the students which were the prime source of the research. They had to evaluate influential factors to their motivation level and competence. The database was analyzed with descriptive statistic methods, principal component and cluster analysis. Studying the personal competency, five different factors were divided based on Belbin’s team roles and four clusters. The four clusters were established by the five factors. Analyzing the student’s educational motivation four different components were divided: the need of performance, social entertainment, the benefits of learning in the near future and the reach of the financial freedom. Based on the four components, generating clusters was not possible due to the significance level of the K-means cluster analysis because it was higher than 0,05 in every grouping variables.

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