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Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study
Computer science graduates face a massive gap between industry-relevant skills and those learned at school. Industry practitioners often counter a huge challenge when moving from academics to industry, requiring a completely different set of skills and knowledge. It is essential to fill the gap betw...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10130881/ https://www.ncbi.nlm.nih.gov/pubmed/37123955 http://dx.doi.org/10.1016/j.heliyon.2023.e15407 |
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author | Hassan, Muhammad Umair Alaliyat, Saleh Sarwar, Raheem Nawaz, Raheel Hameed, Ibrahim A. |
author_facet | Hassan, Muhammad Umair Alaliyat, Saleh Sarwar, Raheem Nawaz, Raheel Hameed, Ibrahim A. |
author_sort | Hassan, Muhammad Umair |
collection | PubMed |
description | Computer science graduates face a massive gap between industry-relevant skills and those learned at school. Industry practitioners often counter a huge challenge when moving from academics to industry, requiring a completely different set of skills and knowledge. It is essential to fill the gap between the industry's required skills and those taught at varsities. In this study, we leverage deep learning and big data to propose a framework that maps the required skills with those acquired by computing graduates. Based on the mapping, we recommend enhancing the computing curriculum to match the industry-relevant skills. Our proposed framework consists of four layers: data, embedding, mapping, and a curriculum enhancement layer. Based on the recommendations from the mapping module, we made revisions and modifications to the computing curricula. Finally, we perform a case study of the Norwegian IT jobs market, where we make recommendations for data science and software engineering-related jobs. We argue that by using our proposed methodology and analysis, a significant enhancement in the computing curriculum is possible to help increase employability, student satisfaction, and smart decision-making. |
format | Online Article Text |
id | pubmed-10130881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101308812023-04-27 Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study Hassan, Muhammad Umair Alaliyat, Saleh Sarwar, Raheem Nawaz, Raheel Hameed, Ibrahim A. Heliyon Research Article Computer science graduates face a massive gap between industry-relevant skills and those learned at school. Industry practitioners often counter a huge challenge when moving from academics to industry, requiring a completely different set of skills and knowledge. It is essential to fill the gap between the industry's required skills and those taught at varsities. In this study, we leverage deep learning and big data to propose a framework that maps the required skills with those acquired by computing graduates. Based on the mapping, we recommend enhancing the computing curriculum to match the industry-relevant skills. Our proposed framework consists of four layers: data, embedding, mapping, and a curriculum enhancement layer. Based on the recommendations from the mapping module, we made revisions and modifications to the computing curricula. Finally, we perform a case study of the Norwegian IT jobs market, where we make recommendations for data science and software engineering-related jobs. We argue that by using our proposed methodology and analysis, a significant enhancement in the computing curriculum is possible to help increase employability, student satisfaction, and smart decision-making. Elsevier 2023-04-11 /pmc/articles/PMC10130881/ /pubmed/37123955 http://dx.doi.org/10.1016/j.heliyon.2023.e15407 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Hassan, Muhammad Umair Alaliyat, Saleh Sarwar, Raheem Nawaz, Raheel Hameed, Ibrahim A. Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study |
title | Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study |
title_full | Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study |
title_fullStr | Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study |
title_full_unstemmed | Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study |
title_short | Leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: A Norwegian case study |
title_sort | leveraging deep learning and big data to enhance computing curriculum for industry-relevant skills: a norwegian case study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10130881/ https://www.ncbi.nlm.nih.gov/pubmed/37123955 http://dx.doi.org/10.1016/j.heliyon.2023.e15407 |
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