Unlocking the Future of INFOCOMM Workforce: A Visual KSA Matrix Taxonomy Approach to Education and Occupational Profiles Academic Article in Scopus uri icon

abstract

  • Skills taxonomies are a useful classification system for all skills that an employee must count at the workplace. Taxonomies provide a framework for seeking, classifying, evaluating, and indicating the skills that are essential for all kinds of professions. Taxonomies based on Future Skills usually have a visual framework to show their occupational structures and provide upskilling and reskilling support through various pieces of training. This article proposes a web framework using a dynamic taxonomic system based on knowledge, skills, and abilities (KSA) matrices for submitting course and occupation structuring for the Industry 4.0 workforce. For the methodological process, firstly, a matrix taxonomic structure based on KSA was created through a review of the literature; secondly, an analysis of the data related to KSA presented by FutureSkills frameworks was carried out, such as those of the World Economic Forum (WEF), NESTA Taxonomy, SkillsFuture of the Government of Singapore, the Standard Occupational Classification (SOC), among others. Once the base taxonomy was created with the data from the frameworks mentioned above, the dynamic aspects were developed through new documents and publications, applying natural language processing tools to enrich and complete the KSAs identified as trends. The INFOCOMM technology sector was chosen as a case study under the dynamic matrix taxonomy structure, applying NLP tools to extract and explain KSA trends and potentially new ones. Among the results obtained is a web framework where the taxonomic structuring created for the INFOCOMM Technology sector can be dynamically displayed. The preliminary results show that this framework can serve as an international reference guide to designing future educational plans for active learning and experiential in higher education institutions and for designing occupational profiles for the industry's future. © 2024 IEEE.

publication date

  • January 1, 2024