Volume 11, Issue 4 (Autumn 2025)                   JCCNC 2025, 11(4): 297-306 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Pangandaman H K. Recontextualizing the Trust-adaptation-intention Framework for Generative Artificial Intelligence Integration in Nursing Education. JCCNC 2025; 11 (4) :297-306
URL: http://jccnc.iums.ac.ir/article-1-862-en.html
Department of Nursing, College of Health Sciences, Mindanao State University, Marawi, Philippines. , hamdoni.pangandaman@msumain.edu.ph
Abstract:   (605 Views)
Background: The integration of generative artificial intelligence (AI) tools transforms educational practices, particularly in self-directed learning, academic engagement, and critical thinking. However, nursing education, where clinical reasoning and ethical practice are paramount, requires a theoretical understanding tailored to its unique pedagogical environment. While the trust-adaptation-intention (TAI) framework has been previously conceptualized in broader technology adoption contexts, its application to nursing students’ behavioral responses to generative AI has remained unexplored. This study aims to recontextualize the TAI framework to explain how nursing students build trust in generative AI tools, adapt their learning behaviors accordingly, and develop sustained intentions to integrate these technologies into their academic routines. 
Methods: A deductive axiomatic approach was employed to reinterpret the TAI framework within the nursing education context. Five foundational axioms were formulated from the literature on technology acceptance, behavioral psychology, and nursing pedagogy. These axioms informed three propositions that explain the behavioral progression of nursing students as they engage with generative AI. 
Results: The recontextualized TAI framework illustrates a sequential process: Unmet educational needs and perceived benefits of AI support trust formation, trust facilitates adaptive learning behaviors, so that trust and adaptation jointly influence students’ intention to continue AI use. This adapted framework provides a mid-range theoretical lens specifically tailored to the nursing education setting.
Conclusion: This study gives a recontextualized interpretation of the TAI framework, offering practical insights for educators and policymakers in designing AI-integrated curricula that uphold the pedagogical and ethical standards of nursing education.
Full-Text [PDF 640 kb]   (350 Downloads) |   |   Full-Text (HTML)  (214 Views)  
Type of Study: Research | Subject: General
Received: 2025/04/4 | Accepted: 2025/05/31 | Published: 2025/11/1

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Designed & Developed by : Yektaweb