Degree Name
Nursing Practice, DNP
Publication Date
9-21-2026
First Advisor
Lisa Drake
Second Advisor
Alisha McAfee
Abstract
Artificial intelligence (AI) continues to integrate into healthcare and higher education; however, Health Science faculty at the project site lacked formal training to operate or teach AI responsibly. This Doctor of Nursing Practice quality improvement project evaluated whether computer-based AI literacy education improved Health Science faculty members’ self-reported AI literacy. It was predicted that faculty AI literacy scores would improve after completing the intervention. Kotter’s change model and Benner’s novice-to-expert framework informed implementation of change and faculty professional development. The Plan–Do–Study–Act model supported evaluation. In a one-group, quasi-experimental preintervention–postintervention study design at a North Texas two-year college, 19 eligible Health Science faculty were invited to participate, and 9 completed four computer-based modules within six weeks and both administrations of a 37-item Artificial Intelligence Literacy Questionnaire resulting in a 47.4% completion rate. Mean composite scores increased from 3.309 (SD = 0.345) preintervention to 3.871 (SD = 0.402) postintervention (mean difference = 0.562 points, 95% CI [0.334, 0.790]). A paired-samples t test revealed a statistically significant postintervention improvement, t(8) = 5.68, p < .001. The effect size was large (Cohen’s d = 1.89). The findings advanced knowledge at the project site by demonstrating that a faculty-development intervention can significantly improve perceived AI literacy and support the nursing discipline’s efforts to prepare educators and students for the safe, ethical, and responsible use of AI. Limitations of this study included a small, one-site sample size. Data were collected using self-report. Because there was no control group, we could not draw causal conclusions, and the findings may not generalize. Only 9 out of 19 eligible faculty participated, which could lead to participant/attrition bias. Results provide support for faculty developers to include AI literacy education in professional development and new-faculty orientation to continue advancing safe, responsible, and consistent AI practices in Health Sciences education.
Rights Management
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Recommended Citation
Boyle, Amanda, "Quality Improvement Project: Empowering Change: Evidence-Based Strategies to Improve AI Use in Pedagogy" (2026). Doctor of Nursing Practice Projects. 398.
https://arch.astate.edu/dnp-projects/398
