Degree Name

Nursing Practice, DNP

Publication Date

4-28-2026

First Advisor

Sandy King

Second Advisor

Chandra Carter

Abstract

In rural nursing programs, student exposure to diverse cultures is limited, which can hinder development of cultural competence. Artificial intelligence (AI) simulation is an evidence-based strategy to improve cultural competence and clinical decision-making, a practice gap exists due to lack of structured, accessible tools. This quality improvement project evaluated whether Generative Pre-trained Transformer (GPT)–based structured prompts would increase culturally inclusive simulation activities and improve faculty perceptions of usefulness and ease of use at a rural community college. The guiding PICOT asked: Among nursing faculty, how does the use of GPT-based structured prompts, compared to an unstructured approach, impact perceived usefulness, perceived ease of use, and frequency of culturally inclusive simulations over one semester? A quantitative pre–post design grounded in Leininger’s Culture Care Theory and guided by Kotter’s 8-Step Change Model was implemented. The evidence-based intervention included GPT prompts, a training video, and an instructional guide. Outcomes were measured using the Technology Acceptance Model (TAM) survey, with data collected through anonymous electronic surveys using participant-generated identifiers. Wilcoxon signed-rank tests showed significant improvements in perceived usefulness (W = 0, Z = −2.67, p = .008), perceived ease of use (W = 0, Z = −2.80, p = .005), and simulations (W = 0, Z = −2.80, p = .005), with median simulations increasing from one to three. Findings suggest structured GPT prompts are a cost-effective strategy to reduce workload barriers and support culturally responsive nursing education despite limitations of small sample size and single-site design.

Included in

Nursing Commons

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