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On the radar: Predicting near-future surges in skills’ hiring demand to provide early warning to educators

The AI-driven Fourth Industrial Revolution and the COVID-19 pandemic have one important thing in common: they both have caused significant and rapid changes to the skill set landscape of various industries. These disruptive forces mean that the early identification of the newly rising skills in a la...

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Autores principales: Yazdanian, Ramtin, Lee Davis, Richard, Guo, Xiangcen, Lim, Fiona, Dillenbourg, Pierre, Kan, Min-Yen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643103/
http://dx.doi.org/10.1016/j.caeai.2021.100043
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author Yazdanian, Ramtin
Lee Davis, Richard
Guo, Xiangcen
Lim, Fiona
Dillenbourg, Pierre
Kan, Min-Yen
author_facet Yazdanian, Ramtin
Lee Davis, Richard
Guo, Xiangcen
Lim, Fiona
Dillenbourg, Pierre
Kan, Min-Yen
author_sort Yazdanian, Ramtin
collection PubMed
description The AI-driven Fourth Industrial Revolution and the COVID-19 pandemic have one important thing in common: they both have caused significant and rapid changes to the skill set landscape of various industries. These disruptive forces mean that the early identification of the newly rising skills in a labour market — which we call its “emerging skills” — is crucial to its workforce. It is also crucial to the educators who, in order to provide lifelong training to the workforce, need to quickly adapt their curricula to the new skills. We propose a classification methodology that uses the past job ad trends of skills to predict the emerging skills of a future period, defined as the skills that have experienced a surge in hiring demand in said period. This general definition allows for freedom in specifying the criteria for a skill being emerging (through thresholds on hiring demand and its growth), which could be important to educators. Applying our methodology to the Information and Communication Technologies (ICT) labour market in Singapore, we show that we are able to predict future emerging skills with good precision and recall and beat two baseline classifiers for multiple threshold sets. Our methodology also allows us to see where job ads fail to provide sufficient predictive signals, pointing to auxiliary data sources (such as Stack Overflow for ICT) and skill ontologies as potential remedies. The success of our method shows how AI can be used to empower learners and educators in the ICT domain (and potentially other domains) with useful and well-curated insights at a moment’s notice, thus helping speed up the process of curricular change.
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spelling pubmed-96431032022-11-14 On the radar: Predicting near-future surges in skills’ hiring demand to provide early warning to educators Yazdanian, Ramtin Lee Davis, Richard Guo, Xiangcen Lim, Fiona Dillenbourg, Pierre Kan, Min-Yen Computers and Education: Artificial Intelligence Article The AI-driven Fourth Industrial Revolution and the COVID-19 pandemic have one important thing in common: they both have caused significant and rapid changes to the skill set landscape of various industries. These disruptive forces mean that the early identification of the newly rising skills in a labour market — which we call its “emerging skills” — is crucial to its workforce. It is also crucial to the educators who, in order to provide lifelong training to the workforce, need to quickly adapt their curricula to the new skills. We propose a classification methodology that uses the past job ad trends of skills to predict the emerging skills of a future period, defined as the skills that have experienced a surge in hiring demand in said period. This general definition allows for freedom in specifying the criteria for a skill being emerging (through thresholds on hiring demand and its growth), which could be important to educators. Applying our methodology to the Information and Communication Technologies (ICT) labour market in Singapore, we show that we are able to predict future emerging skills with good precision and recall and beat two baseline classifiers for multiple threshold sets. Our methodology also allows us to see where job ads fail to provide sufficient predictive signals, pointing to auxiliary data sources (such as Stack Overflow for ICT) and skill ontologies as potential remedies. The success of our method shows how AI can be used to empower learners and educators in the ICT domain (and potentially other domains) with useful and well-curated insights at a moment’s notice, thus helping speed up the process of curricular change. The Authors. Published by Elsevier Ltd. 2022 2021-12-16 /pmc/articles/PMC9643103/ http://dx.doi.org/10.1016/j.caeai.2021.100043 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Yazdanian, Ramtin
Lee Davis, Richard
Guo, Xiangcen
Lim, Fiona
Dillenbourg, Pierre
Kan, Min-Yen
On the radar: Predicting near-future surges in skills’ hiring demand to provide early warning to educators
title On the radar: Predicting near-future surges in skills’ hiring demand to provide early warning to educators
title_full On the radar: Predicting near-future surges in skills’ hiring demand to provide early warning to educators
title_fullStr On the radar: Predicting near-future surges in skills’ hiring demand to provide early warning to educators
title_full_unstemmed On the radar: Predicting near-future surges in skills’ hiring demand to provide early warning to educators
title_short On the radar: Predicting near-future surges in skills’ hiring demand to provide early warning to educators
title_sort on the radar: predicting near-future surges in skills’ hiring demand to provide early warning to educators
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643103/
http://dx.doi.org/10.1016/j.caeai.2021.100043
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