텍스트마이닝을 활용한 국내 과학기술인력개발 연구동향 분석

초록

The purpose of this study is to utilize text mining to identify the research trends, key keywords, research topics, and academic fields of domestic science and technology human resources development research by period, and to provide practical and policy-based reference materials for the future. To this end, keyword frequency analysis and topic modeling were conducted using Google Colab on a total of 182 abstracts from domestic academic papers and theses. The results revealed that, first, research in the field of science and technology human resource development began in 1994, increased sharply after the mid-2010s, and then declined in the early 2020s. Second, the main keywords in science and technology human resource development research were “education”, “innovation”, “job”, “career”, and “engagement” which appeared with high frequency. Third, the topic modeling results categorized research topics into five categories: ① academic experiences at universities, ②organizational characteristics of companies and individual career and competency development, ③foundational competency education in writing and liberal arts at universities, ④ job engagement and career mobility of science and technology human resources, ⑤ organizational innovation competencies based on leadership and trust. These findings demonstrate that science and technology human resource development is interconnected and develops across individual, organizational, and societal dimensions. This study is significant in that it provides a comprehensive analysis of research trends across all HRD fields (ID, CD, OD) targeting science and technology personnel. From a policy and practical perspective, it suggests the need to strengthen foundational competency education in universities, expand job transition and career development programs for employed personnel, improve job engagement and organizational culture, and enhance innovation capabilities based on leadership. Academically, it confirms that text mining are an effective method for comprehensively understanding research trends across the entire field of science and technology human resource development.

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