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Effectiveness of artificial intelligence chatbot-assisted flipped learning on patient handover for nursing students:
Wen Chang1, Chun-Chih Lin1, Hsiang-Chun Lee2
1Nursing Management Department of Administration Center, Chang Gung Medical Foundation, Taiwan, ROC; Department of Nursing, Chang Gung University of Science and Technology, Taiwan, ROC.
Aims:
To evaluate the learning outcomes of an artificial intelligence (AI) chatbot-assisted flipped learning program in relation to students' patient handover knowledge, oral performance, learning perceptions, attitudes and learning experiences.
Background:
Effective handover communication is essential for patient safety. However, nursing students often lack structured, theory-informed training in this process. Integration of AI chatbot-assisted flipped learning has potential to enhance handover competencies.
Design:
Convergent mixed-methods design.
Methods:
A quasi-experimental design and focus group interviews were used. Quantitative data were collected during pre- and post-tests to measure knowledge, learning perceptions and attitudes and via a rubric assessing oral performance. Qualitative data were obtained through focus group interviews exploring students' experiences with chatbot-assisted learning.
Results:
A total of 112 nursing students was recruited. The experimental group (n = 58) scored significantly higher than the control group (n = 54) on knowledge (p = 0.016). The experimental group scored higher on practical performance than the control group (p < 0.001). Focus group interviews revealed four themes in learning experiences: chatbots as a double-edged sword for learning; enhancing motivation and engagement; bridging theoretical gaps and expanding cognitive boundaries; and connecting classroom knowledge with clinical scenarios. The core theme emphasizes critical thinking to enhance technology-assisted collaborative learning.
Conclusions:
AI chatbot-assisted flipped learning effectively improved students' handover competency. Integration of the AI chatbot promoted reflective learning. The study presents an innovative strategy for preparing students for clinical communication.
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