토픽 모델링을 활용한 진로전담교사 관련 국내 연구 동향 분석 = Analysis of Research Trends on Career Teachers in Korea Using Topic Modeling

다국어 초록 (Multilingual Abstract)

This study aims to systematically analyze Korean research trends related to career teachers, who are key agents of career education in rapidly changing future society, and to derive directions and implications for future research. To achieve this purpose, Latent Dirichlet Allocation(LDA)-based topic modeling, a text mining technique, was conducted on the abstracts of 102 relevant studies published by 2025. The results showed that research on career teachers began in 2009 and has steadily increased in conjunction with changes in career education policies such as the implementation of the Career Education Act, the Free Semester System, and the High School Credit System. The optimal number of topics derived through LDA analysis was six. Topic labels were finalized by comprehensively reviewing the top 10 keywords with high occurrence probabilities (β) and the content of representative studies assigned to each topic. The proportion of analyzed topics appeared in the following order of prevalence: 'Job Importance-Performance Analysis', 'Operational Status by School Level', 'Competency Modeling and Scale Development', 'Policy and Support', 'Factors Influencing Job Performance', and 'Professional Development'. The validity of the six named topics was cross-verified through word cloud visualization. Furthermore, the analysis of annual trends empirically demonstrated that the research paradigm has dynamically shifted from an initial focus on identifying operational status and policy support (Topics 2 and 4) to exploring factors influencing job performance and professional development (Topics 1 and 3) in recent years. Based on these findings, this study suggests the need for specific and practical follow-up research to substantially strengthen the professionalism of career teachers in the field.