Early developmental trajectory of nursing students’ AIGC application experience: a short-term longitudinal qualitative study
AIGC is integrated into nursing education, but existing research focuses on short-term instruction, lacking in-depth study on long-term experience development and its potential association with decision-making-related capacities. This study aims to explore nursing students’ AIGC application experience development and its association with nursing decision-making-related development. This study employed a longitudinal qualitative research design within the constructivist paradigm. Twenty-two nursing students were recruited from a vocational college through purposeful maximum variation sampling. Data were collected via semi-structured interviews, reflective diaries, and homework materials, and analyzed using an integrated framework analysis based on Kolb’s experiential learning theory and the Information Seeking and Communication Model (ISCM). The study identified four themes in development stages: exploration and uncertainty in the initial contact stage, reflection and boundary recognition after trial and error, strategy construction and systematic application, and professional repositioning in human-AI collaboration. Students’ information behavior appeared to evolve from primarily retrieval-focused use toward more generative, verificatory, and integrative patterns of engagement, and students reported perceived deepening of critical judgment and professional role awareness, though these patterns varied considerably across participants. The potential relevance of AIGC application experience to nursing decision-making-related development depends on students’ evaluation, monitoring, and responsibility. Nursing education should combine experiential learning with critical information literacy cultivation.
Authors
- Chunxiu Xiao
- Feifei Liu
- Yanyan Zhang
- Lijiao Cai
Institutions
- Fujian Medical University (CN)
- Education Department of Fujian Province (CN)
Publication Details
- Journal
- BMC Medical Education
- Published
- 2026-10-07
- DOI
- https://doi.org/10.1186/s12909-026-10562-7
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00