Date of Award
Summer 2026
Document Type
Thesis
Abstract
Abstract
Background: Simulation has long been used to prepare pre-licensure nursing students for clinical practice. Traditional written pre-simulation assignments have been the assignment of choice for many years. However, artificial intelligence (AI) guided preparatory tools may offer students a more interactive, personalized way to enhance their simulation experience.
Purpose: The purpose of this project was to utilize AI technology in pre-simulation preparatory work to enhance learning in second-semester associate degree nursing students.
Methods: The study consisted of randomized traditional and AI-guided preparatory groups among consenting participants. The sample consisted of 23 participants. Both sets of students completed the same simulation. At the end of the simulation, students complete the Simulation Effectiveness Tool-Modified (SET-M) survey. Descriptive statistics were obtained from the data and analyzed for frequencies and medians of the learning sub-domain of the SET-M.
Results: Mann-Whitney U tests found no differences between the two groups on the six questions in the learning subdomain.
Conclusion: Incorporating AI-guided preparatory work was at least as effective as traditional post-outcome interventions and may lead to improvement in learning outcomes.
Keywords: artificial intelligence, simulation, ChatGPT, nursing student, pediatric, asthma
Recommended Citation
Price, Kaitlyn, "Evaluating the Use of Artificial Intelligence to Enhance Pediatric Simulation Among Associate Degree Nursing Students" (2026). Theses. 64.
https://roar.una.edu/theses/64
