Qi‐qi Ke
Papers
1
Total Citations
23
H-Index
1
About
Qi-qi Ke is a nursing education researcher whose work centers on integrating conversational artificial intelligence into clinical training, with a particular focus on history-taking instruction for nursing students. Her most-cited study, a 2023 qualitative investigation using focus group interviews, systematically assessed the need for chatbot-based history-taking programs—revealing that students find traditional history-taking challenging and explicitly desire AI-driven simulation tools to bridge the gap between theory and practice. This foundational work, which has garnered 23 citations, directly informs the design of interactive, chatbot-mediated curricula that enhance students' clinical reasoning and communication skills. Ke’s research sits at the intersection of nursing pedagogy, human-computer interaction, and patient-centered care, offering practical, student-informed solutions to a persistent educational bottleneck. Her contributions are notable for their methodological rigor and translational potential, providing evidence-based guidance for educators seeking to modernize clinical training. By centering learner voices through qualitative inquiry, Ke has laid critical groundwork for scalable, technology-enhanced interventions that promise to improve both educational outcomes and, ultimately, patient care quality.
Research Focus
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Top Papers
- 1