Degree Name

Nursing Practice, DNP

Publication Date

4-27-2026

First Advisor

Sandy King

Second Advisor

Jason Weger

Abstract

The rapid integration of artificial intelligence (AI) in healthcare has created a growing need for nursing faculty to develop competency in AI to adequately prepare students for modern clinical practice. Despite this need, limited faculty knowledge and low classroom application of AI persist. The purpose of this Doctor of Nursing Practice (DNP) quality improvement project was to evaluate the impact of an evidence-based AI educational intervention on nursing faculty competency and classroom application. Guided by the Stetler Model of Evidence-Based Practice and Lewin’s Change Theory, a quasi-experimental pretest-posttest design was implemented with nursing faculty at a rural community college in East Texas. The six-week intervention included structured AI education, hands-on application, and instructional resources. Data was collected using the C-scale and investigator-developed surveys, which measured AI knowledge, confidence, and application. A paired t-test revealed a statistically significant increase in faculty competency scores from pre-intervention to post-intervention with a p value equal to 0.032. Descriptive findings indicated 100% of participants reported AI integration into teaching, with improvements in engagement and instructional efficiency. Limitations included small sample size and single-site design. This project demonstrates that targeted AI education significantly improves faculty competency and classroom application, supporting the integration of AI into nursing education and advancing faculty development practices.

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