스킬 미스매치에 따른 과학기술분야 재직자의 무형식학습 및 지식공유 유형 분류: 잠재 프로파일 분석

This study aims to identify types of informal learning and knowledge sharing by perceived skill mismatch among researchers in science and technology, and to examine how factors and outcomes vary across different groups. The data were drawn from the 2023 KIRD Survey of Human Resource Development in Science and Technology, which included a sample of 1,490 respondents. Latent profile analysis was conducted based on respondents’ perceptions of skill mismatch, participation in informal learning activities, and knowledge sharing practices. The analysis revealed four distinct groups: (a) skill-mismatched proactive learners; (b) passive learners; (c) moderately engaged learners; and (d) skill-matched self-directed learners. Subsequently, we explored the factors influencing group membership probabilities; the findings demonstrate that the relationships between factors varied according to the identified groups. Additionally, the extent to which respondents’ perceptions of outcomes differed by group was closely associated with their levels of participation in informal learning and knowledge sharing activities. Based on the findings, we suggest implications for policy and practice to facilitate career development interventions and human resource development initiatives for researchers in science and technology.