Currently submitted to: JMIR Medical Education
Date Submitted: Jan 23, 2026
Open Peer Review Period: Jan 28, 2026 - Mar 25, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
ChatGPT-Assisted PBL Teaching Model in Pediatric Nursing Undergraduate Internship: A Randomized Controlled Pilot Study
ABSTRACT
Background:
Traditional Problem-Based Learning (PBL) in pediatric nursing education often uses static cases and lacks personalized, real-time feedback. The integration of generative AI like ChatGPT could address these limitations, yet its systematic application in nursing internships remains understudied.
Objective:
To explore the effectiveness and feasibility of a ChatGPT-assisted Problem-Based Learning (PBL) model in pediatric nursing undergraduate internship education, providing empirical evidence for artificial intelligence(AI) nursing education integration.
Methods:
A single-center, assessor-blinded randomized controlled pilot study was conducted. Eighty-four interns were randomly assigned to the ChatGPT-PBL group (n=42) or traditional PBL group (n=42) at a 1:1 ratio. Based on traditional PBL, the experimental group integrated ChatGPT-4 to construct a "instructor-student dual-layer" supported PBL teaching framework, including dynamic generation of personalized clinical cases, provision of real-time operational feedback, and decision-making simulation training. The traditional PBL group received standardized traditional PBL teaching. The intervention lasted for 4 weeks. The primary outcome measures included theoretical assessment scores, Objective Structured Clinical Examination (OSCE) scores, Chinese Version of Critical Thinking Disposition Inventory (CTDI-CV) scores, Holistic Clinical Assessment Tool for Nursing Undergraduates (HCAT) scores, and teaching satisfaction.
Results:
Post-intervention, the theoretical score of the ChatGPT-PBL group was significantly higher than that of the traditional PBL group (82.76±5.02 vs 71.88±5.88, P<0.001). The ChatGPT-PBL group also showed significant advantages over the traditional PBL group in OSCE total score (43.24±2.75 vs 36.99±3.71, P<0.001), CTDI-CV total score (60.14±5.21 vs 49.87±5.74, P<0.001), and HCAT total score (51.14±3.46 vs 41.88±4.71, P<0.001). The overall satisfaction rates of the ChatGPT-PBL group with Instructors, teaching plans, and teaching content were 90.5%-95.2%, which were significantly higher than those of the traditional PBL group (64.3%-71.4%,<0.05).
Conclusions:
The ChatGPT-assisted PBL teaching model significantly improves the theoretical knowledge level, specialized operational skills, critical thinking ability, and clinical nursing competence of pediatric nursing undergraduate interns, with higher teaching satisfaction. It provides a replicable practical paradigm for the in-depth integration of AI and pediatric nursing education, and holds important clinical application and promotion value. Clinical Trial: The study protocol was registered in the Chinese Clinical Trial Registry (ChiCTR2500114150) .
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