Date
12-16-2025
Department
School of Nursing
Degree
Doctor of Philosophy in Nursing (PhD)
Chair
Jordan Lee Slowik
Keywords
artificial intelligence, nursing faculty, nursing education, faculty attitudes, curriculum development
Disciplines
Education | Nursing
Recommended Citation
McSpadden, Micaela, "Nursing Faculty Attitudes toward Artificial Intelligence: A Quantitative Causal-Comparative Cross-Sectional Study" (2025). Doctoral Dissertations and Projects. 7779.
https://digitalcommons.liberty.edu/doctoral/7779
Abstract
The rapid growth of artificial intelligence (AI) in healthcare has highlighted the importance of understanding how nursing faculty perceive this technology. Although prior studies have explored public views, nurses’ perceptions, and faculty attitudes toward technology and curriculum change, limited research has focused on nursing faculty perspectives toward AI. Through the lens of the Theory of Reasoned Action (TRA) and the Technology Acceptance Model (TAM), this study examined factors that influence nursing faculty attitudes toward AI in nursing education. This study used a quantitative, causal-comparative, cross-sectional design with 263 nursing faculty participants from undergraduate pre-licensure programs in the United States. Participants were recruited through professional networks and social media and completed an anonymous online survey containing demographic questions and the General Attitudes toward Artificial Intelligence Scale (GAAIS). The majority of participants were White, female, mid-career nursing faculty with advanced degrees. The GAAIS scores were found to violate the assumption of normality, therefore, nonparametric testing was used. A Mann-Whitney U test identified a significant difference in attitudes toward AI between religious and non-religious participants, whereas Kruskal-Wallis H tests revealed no significant differences based on years of teaching experience, U.S. region, or geographic setting of employment. These results indicate that religiosity was the primary factor influencing variations in AI attitudes among nursing faculty. Overall, the findings offer meaningful insights for nursing education leaders aiming to better support nursing faculty with the integration of AI in both nursing practice and nursing education.
