과학기술인의 학습민첩성 잠재 프로파일 유형 분류 및 무형식학습과 심리적 안전감의 영향 분석

This study aims to classify types of learning agility among science and technology professionals and to examine the effects of informal learning and psychological safety on these classifications, thereby enhancing our understanding of how learning agility manifests in this population. To achieve this objective, we utilized data from the 2023 Science and Technology Talent Development Activity Survey conducted by the Korea Institute of Human Resources Development in Science and Technology(KIRD). Through latent profile analysis, we identified distinct learning agility profiles and further explored the influence of informal learning and psychological safety on profile membership. The analysis revealed four distinct types of learning agility: low-level/low-adaptive, low-level/medium-adaptive, high-level/medium-adaptive, and high-level/high-adaptive. Results from a multinomial logistic regression analysis, with the low-level/low-adaptive group as the reference category, indicated that the psychological safety subdimension “freedom to ask for help among members” significantly increased the likelihood of belonging to the high-level/high-adaptive group. Additionally, most subcomponents of informal learning were found to have a statistically significant influence on membership in both the high-level/medium-adaptive and high-level/high-adaptive groups. These findings contribute to a more nuanced understanding of learning agility in the context of science and technology work and underscore the importance of fostering psychological safety and informal learning environments to enhance learning agility among professionals in this sector.