Child health nursing research · 2026
Development and pilot evaluation of an AI-based pediatric medication safety virtual simulation program for nursing students: a quasi-experimental study in South Korea.
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Cho In Young, Cho Soohyeon, Im Min Yeong, Jeong Hui Jung, Choi Jimin, Choi In Hyeong, Kim Hee Young
Аннотация
PURPOSE: This study aimed to develop an artificial intelligence (AI)-based pediatric medication safety competence (PMSC) virtual simulation program and evaluate its effectiveness among nursing students.
METHODS: This quasi-experimental study used a nonequivalent control group pretest-posttest design and was conducted in December 2025. The AI-based PMSC virtual simulation program was developed based on Kolb's experiential learning theory, following its 4-stage cycle of concrete experience, reflective observation, abstract conceptualization, and active experimentation. Participants were 48 third-year nursing students in South Korea who were assigned to either the experimental group (n=24) or the control group (n=24) through a nonrandomized allocation procedure. The experimental group participated in the PMSC virtual simulation program. Outcomes included PMSC, medication calculation confidence (MCC), Simulation Task Load Index (SIM-TLX), and learning immersion (LI). Data were collected before and after the intervention using validated instruments, and statistical tests were used to evaluate program effectiveness.
RESULTS: Compared with the control group, the experimental group showed significant improvement in PMSC (t=2.48, p=.017). No significant between-group differences were observed in MCC (t=-0.87, p=.389) or LI (t=0.97, p=.336). In addition, SIM-TLX scores decreased significantly from pretest to posttest in the experimental group (t=-2.61, p=.016).
CONCLUSION: The AI-based PMSC virtual simulation program may help strengthen PMSC among nursing students and may be suitable for use in pediatric nursing education. Future research should refine the program to better address individual learning needs and integrate complementary simulation-based strategies into pediatric medication nursing education.
METHODS: This quasi-experimental study used a nonequivalent control group pretest-posttest design and was conducted in December 2025. The AI-based PMSC virtual simulation program was developed based on Kolb's experiential learning theory, following its 4-stage cycle of concrete experience, reflective observation, abstract conceptualization, and active experimentation. Participants were 48 third-year nursing students in South Korea who were assigned to either the experimental group (n=24) or the control group (n=24) through a nonrandomized allocation procedure. The experimental group participated in the PMSC virtual simulation program. Outcomes included PMSC, medication calculation confidence (MCC), Simulation Task Load Index (SIM-TLX), and learning immersion (LI). Data were collected before and after the intervention using validated instruments, and statistical tests were used to evaluate program effectiveness.
RESULTS: Compared with the control group, the experimental group showed significant improvement in PMSC (t=2.48, p=.017). No significant between-group differences were observed in MCC (t=-0.87, p=.389) or LI (t=0.97, p=.336). In addition, SIM-TLX scores decreased significantly from pretest to posttest in the experimental group (t=-2.61, p=.016).
CONCLUSION: The AI-based PMSC virtual simulation program may help strengthen PMSC among nursing students and may be suitable for use in pediatric nursing education. Future research should refine the program to better address individual learning needs and integrate complementary simulation-based strategies into pediatric medication nursing education.