저자 김소영
국문제목 간호대학생의 취업 준비 역량 향상을 위한 AI 기반 모의면접 경험: 현상학적 연구
영문제목 Exploring Nursing Students' Experiences with AI-Based Mock Interviews to Enhance Job Readiness Competencies: A Phenomenological Study
국문키워드 간호대학생, 인공지능, 면접, 질적연구
영문키워드 Nursing students; Artificial intelligence; Interviews as topic; Qualitative research
출판정보 질적연구 27권 1호
발행년월 2026년 05월

저자

김소영

국문제목

간호대학생의 취업 준비 역량 향상을 위한 AI 기반 모의면접 경험: 현상학적 연구

영문제목

Exploring Nursing Students' Experiences with AI-Based Mock Interviews to Enhance Job Readiness Competencies: A Phenomenological Study

국문키워드

간호대학생, 인공지능, 면접, 질적연구

영문키워드

Nursing students; Artificial intelligence; Interviews as topic; Qualitative research

출판정보

질적연구 27권 1호

발행년월

2026년 05월

첨부파일

27-1-48-김소영-최종.pdf 

초록

Purpose: This study examined the essence and significance of nursing students' experiences with AI-based mock interviews. Methods: In-depth individual interviews were conducted with 12 nursing students who participated in AI-based mock interview programs from September to October 2025. Data were analyzed using Colaizzi's phenomenological method. Results: Five theme clusters emerged: tension and adaptation in unfamiliar tech- nological environments, increased self-awareness through feedback, enhanced performance competency through repetitive learning, development of employment preparation strategies, and recognition of technology's limitations and the need for human feedback. Participants initially felt tension but adapted through repeated participation, became aware of their nonverbal habits through objective AI feedback, and developed strategic self-expression skills. However, they acknowledged the impersonal nature of AI feedback and the necessity for human input. Conclusion: This study demonstrated that nursing students' experiences with AI-based mock interviews encompassed not only technical training but also emotional growth, self-regulation, performance enhancement, and professional identity formation. The findings highlight the need for a hybrid feedback system that integrates technology-centered objective analysis with human-centered relational feedback.