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The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy

The complexity of creating and updating workforce frameworks and standards is limiting the manoeuvrability of TVET educational outcomes as the world of work is constantly changing, putting stakeholders at risk of poor visibility. A literature review based on 39 documents from various types of docume...

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Main Authors: Azman Shah, S. M. S., Haron, H. N., Mahrin, M. N.
Format: Article
Published: Penerbit UTHM 2021
Subjects:
T Technology (General)
Online Access:http://eprints.utm.my/id/eprint/94502/
http://dx.doi.org/10.30880/jtet.2021.13.01.019
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id my.utm.94502
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spelling my.utm.945022022-03-31T14:55:07Z http://eprints.utm.my/id/eprint/94502/ The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy Azman Shah, S. M. S. Haron, H. N. Mahrin, M. N. T Technology (General) The complexity of creating and updating workforce frameworks and standards is limiting the manoeuvrability of TVET educational outcomes as the world of work is constantly changing, putting stakeholders at risk of poor visibility. A literature review based on 39 documents from various types of documents including articles, conference papers, book chapters, short surveys, conference reviews and reviews within the period of 2011 to 2020 found that existing occupational taxonomies are not granular enough to support occupational classification in big data applications. On the other hand, workforce frameworks and standards although sufficient in providing detail occupational taxonomies, they are complex to develop and update thus making them inflexible to changing workforce requirements. Trend in the literature also suggests that organizations that employ occupational classification in big data applications among developed countries are in a transition from evidence-based decision making which is based on limited sampling; to a data-driven decision making which is based on the total population. This trend establishes a notion on the emergence of a data driven organization. Given evidence that support the need to improve in the flexibility of workforce frameworks and standards, and the emerging prevalence of a data driven organizations, the idea of improving workforce frameworks and occupational standards through educational intelligence is proposed to improve the manoeuvrability of TVET educational outcomes. Penerbit UTHM 2021 Article PeerReviewed Azman Shah, S. M. S. and Haron, H. N. and Mahrin, M. N. (2021) The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy. Journal of Technical Education and Training, 13 (1). ISSN 2229-8932 http://dx.doi.org/10.30880/jtet.2021.13.01.019 DOI: 10.30880/jtet.2021.13.01.019
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Azman Shah, S. M. S.
Haron, H. N.
Mahrin, M. N.
The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy
description The complexity of creating and updating workforce frameworks and standards is limiting the manoeuvrability of TVET educational outcomes as the world of work is constantly changing, putting stakeholders at risk of poor visibility. A literature review based on 39 documents from various types of documents including articles, conference papers, book chapters, short surveys, conference reviews and reviews within the period of 2011 to 2020 found that existing occupational taxonomies are not granular enough to support occupational classification in big data applications. On the other hand, workforce frameworks and standards although sufficient in providing detail occupational taxonomies, they are complex to develop and update thus making them inflexible to changing workforce requirements. Trend in the literature also suggests that organizations that employ occupational classification in big data applications among developed countries are in a transition from evidence-based decision making which is based on limited sampling; to a data-driven decision making which is based on the total population. This trend establishes a notion on the emergence of a data driven organization. Given evidence that support the need to improve in the flexibility of workforce frameworks and standards, and the emerging prevalence of a data driven organizations, the idea of improving workforce frameworks and occupational standards through educational intelligence is proposed to improve the manoeuvrability of TVET educational outcomes.
format Article
author Azman Shah, S. M. S.
Haron, H. N.
Mahrin, M. N.
author_facet Azman Shah, S. M. S.
Haron, H. N.
Mahrin, M. N.
author_sort Azman Shah, S. M. S.
title The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy
title_short The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy
title_full The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy
title_fullStr The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy
title_full_unstemmed The trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy
title_sort trend of big data in workforce frameworks and occupational standards towards an educational intelligent economy
publisher Penerbit UTHM
publishDate 2021
url http://eprints.utm.my/id/eprint/94502/
http://dx.doi.org/10.30880/jtet.2021.13.01.019
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score 13.211869

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