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Unveiling Disparities: NLP Analysis of Software Industry and Vocational Education Gaps
Mid Sweden University, Faculty of Science, Technology and Media, Department of Communication, Quality Management, and Information Systems (2023-).
Mid Sweden University, Faculty of Science, Technology and Media, Department of Communication, Quality Management, and Information Systems (2023-).
Mid Sweden University, Faculty of Science, Technology and Media, Department of Communication, Quality Management, and Information Systems (2023-).ORCID iD: 0000-0003-4153-5549
2024 (English)In: Proceedings - 2024 ACM/IEEE International Workshop on NL-Based Software Engineering, NLBSE 2024, IEEE conference proceedings, 2024, p. 9-16Conference paper, Published paper (Refereed)
Abstract [en]

The rapid growth of software industry highlights the importance of the education system in producing competent professionals to meet industry demands. Previous research has identified a gap between industry needs and the content of educational programs. This study presents Vocational Education and Labour Market Analyser (VELMA), a tool designed to extract information from job ads and educational curricula (both from Sweden), utilising topic modelling to identify the diverse technologies and skills in demand within the industry and those covered by professional education. Particularly, we use Latent Dirichlet Allocation (LDA) to categorise keywords into cohesive themes for document frequency analysis. Our findings highlight industry demand for skills in cloud and embedded technologies, security engineering, and software architecture. In contrast, the Higher Vocational Education (HVE) curricula emphasise the education of web developers and general object-oriented programming languages. 

Place, publisher, year, edition, pages
IEEE conference proceedings, 2024. p. 9-16
Keywords [en]
NLP Analysis, Software Industry, Topic Modeling, Vocational Education
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:miun:diva-52588DOI: 10.1145/3643787.3648029ISI: 001313494100002Scopus ID: 2-s2.0-85203809040ISBN: 9798400705762 (print)OAI: oai:DiVA.org:miun-52588DiVA, id: diva2:1900659
Conference
Proceedings - 2024 ACM/IEEE International Workshop on NL-Based Software Engineering, NLBSE 2024
Available from: 2024-09-24 Created: 2024-09-24 Last updated: 2025-09-25

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Öberg, Lena-MariaGomes de Oliveira Neto, Francisco

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Bäckstrand, EmilDjupedal, RasmusÖberg, Lena-MariaGomes de Oliveira Neto, Francisco
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Department of Communication, Quality Management, and Information Systems (2023-)
Production Engineering, Human Work Science and Ergonomics

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Citation style
  • apa
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Language
  • de-DE
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  • nn-NO
  • nn-NB
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  • Other locale
More languages
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