ScholarWorks@숙명여자대학교

초록

The purpose of this study is to empirically analyze the job congruency between the National Key and Strategic Industry Training and National Technical Qualification items, aiming to strengthen the linkage between training and qualification systems and promote internal stability in their operation. To achieve this, a 'Weighted Jaccard Similarity' model reflecting seven qualitative variables—including qualification level, training hours, and employment rate—was developed based on the National Competency Standards classification system. Furthermore, Borich Needs Analysis and The Locus for Focus model were applied to examine the discrepancies between the necessity and appropriateness of qualifications across different occupations. The analysis results indicate that while the training-qualification linkage in base industries such as machinery and construction is relatively stable, digital and new technology fields like BIM, AI, and Big Data demonstrate high necessity in the field but low appropriateness, confirming a significant gap between training and qualifications. Accordingly, this study suggests restructuring the classification system of the National Key and Strategic Industry Training based on the Korean Employment Classification of Occupations (KECO) to ensure data consistency, establishing flexible qualification linkage strategies for digital and new technology sectors, and constructing a precise job-qualification matching system by expanding the panel of field experts.

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