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.
نوع مطالعه:
پژوهشي |
موضوع مقاله:
عمومى دریافت: 1404/1/15 | پذیرش: 1404/3/10 | انتشار: 1404/8/10