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Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students
This study aims to explore the role of digital education in the development of skills and employability for engineering students through researching the role of big data analytics courses. The empirical study proposes the hypothesis that both soft and hard skills have positive effects on human capit...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9627341/ https://www.ncbi.nlm.nih.gov/pubmed/36337501 http://dx.doi.org/10.3389/fpsyg.2022.974574 |
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author | Xu, Lin Zhang, Jingxiao Ding, Yiying Sun, Gangzhu Zhang, Wei Philbin, Simon P. Guo, Brian H. W. |
author_facet | Xu, Lin Zhang, Jingxiao Ding, Yiying Sun, Gangzhu Zhang, Wei Philbin, Simon P. Guo, Brian H. W. |
author_sort | Xu, Lin |
collection | PubMed |
description | This study aims to explore the role of digital education in the development of skills and employability for engineering students through researching the role of big data analytics courses. The empirical study proposes the hypothesis that both soft and hard skills have positive effects on human capital, individual attributes, and the career development dimensions of engineering students. This is achieved through constructing a framework of three dimensions of engineering students’ employability and two competency development dimensions of big data analytics courses. A questionnaire survey was conducted with 155 college engineering students and a structural equation model (SEM) was used to test the hypotheses. The results found that courses on big data analytics have a positive impact on engineering students’ abilities in both hard skills (p < 0.01) and soft skills (p < 0.001) dimensions, while soft skills have a more significant impact on engineering students’ employability. The study has practical and theoretical implications that further enriches the knowledge base on engineering education and broadens our understanding of the role of digitalization in enhancing the skills and employability of engineering students. |
format | Online Article Text |
id | pubmed-9627341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96273412022-11-03 Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students Xu, Lin Zhang, Jingxiao Ding, Yiying Sun, Gangzhu Zhang, Wei Philbin, Simon P. Guo, Brian H. W. Front Psychol Psychology This study aims to explore the role of digital education in the development of skills and employability for engineering students through researching the role of big data analytics courses. The empirical study proposes the hypothesis that both soft and hard skills have positive effects on human capital, individual attributes, and the career development dimensions of engineering students. This is achieved through constructing a framework of three dimensions of engineering students’ employability and two competency development dimensions of big data analytics courses. A questionnaire survey was conducted with 155 college engineering students and a structural equation model (SEM) was used to test the hypotheses. The results found that courses on big data analytics have a positive impact on engineering students’ abilities in both hard skills (p < 0.01) and soft skills (p < 0.001) dimensions, while soft skills have a more significant impact on engineering students’ employability. The study has practical and theoretical implications that further enriches the knowledge base on engineering education and broadens our understanding of the role of digitalization in enhancing the skills and employability of engineering students. Frontiers Media S.A. 2022-10-19 /pmc/articles/PMC9627341/ /pubmed/36337501 http://dx.doi.org/10.3389/fpsyg.2022.974574 Text en Copyright © 2022 Xu, Zhang, Ding, Sun, Zhang, Philbin and Guo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Xu, Lin Zhang, Jingxiao Ding, Yiying Sun, Gangzhu Zhang, Wei Philbin, Simon P. Guo, Brian H. W. Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students |
title | Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students |
title_full | Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students |
title_fullStr | Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students |
title_full_unstemmed | Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students |
title_short | Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students |
title_sort | assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9627341/ https://www.ncbi.nlm.nih.gov/pubmed/36337501 http://dx.doi.org/10.3389/fpsyg.2022.974574 |
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