An Introduction to the Artificial Intelligence-Driven Technology Adoption in Nursing Education Conceptual Framework: A Mixed-Methods Study.

Background/Objectives: Technological advancements are revolutionizing nursing education by improving precision, patient outcomes, and learning experiences. There is an urgent need for systematic frameworks to help nurse educators effectively integrate advanced technologies into their teaching method...

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Published in:Nursing Reports Vol. 15; no. 6; pp. 184 - 199
Main Authors: Maguire, Mary Beth, White, Anne
Format: research tables/charts Journal Article
Published: MDPI Jun2025
Online Access:View this record in EBSCOhost
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      dt: Jun2025
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      pub: MDPI
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        10.3390/nursrep15060184
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        atl: An Introduction to the Artificial Intelligence-Driven Technology Adoption in Nursing Education Conceptual Framework: A Mixed-Methods Study.
      aug:
        au:
          Maguire, Mary Beth
          White, Anne
        affil: Laerdal Medical, Wappingers Falls, NY 12590, USA
      sug:
        subj:
          Education, Nursing
          Artificial Intelligence Utilization
          Technology Utilization
          Teaching Methods
          Program Evaluation
          Conceptual Framework
          Students, Nursing
          Human
          Male
          Female
          Adolescence
          Multimethod Studies
          Surveys
          Attitude to Health
          Educational Measurement
          Curriculum
          Quantitative Studies
          Qualitative Studies
          Aging Education
          Adolescent: 13-18 years
          Male
          Female
      ab: Background/Objectives: Technological advancements are revolutionizing nursing education by improving precision, patient outcomes, and learning experiences. There is an urgent need for systematic frameworks to help nurse educators effectively integrate advanced technologies into their teaching methods. This manuscript introduces the Artificial Intelligence-Driven Technology Adoption in Nursing Education (AID-TANE) framework and operationalizes its use through a pilot study with undergraduate nursing students. Methods: The framework was tested through a convergent mixed-methods pre/post-test study design involving 160 senior-level community health nursing students who participated in an AI-driven educational intervention. Quantitative data were collected using the Facts on Aging quiz, while qualitative data were gathered from a reflective survey. Statistical analyses included paired-sample t-tests and a qualitative content analysis. Results: The study revealed a statistically significant increase in learners' knowledge about older adults, with mean scores improving from 33.29 (SD = 5.33) to 36.04 (SD = 6.76) post-intervention (t = 5.05, p < 0.001). The qualitative analysis identified four key themes: communication and understanding, patience and empathy, respect for independence, and challenging stereotypes. Conclusions: This study found that AI-driven educational tools significantly improved nursing students' knowledge about older adults and positively influenced their learning experiences. The findings highlight the need for targeted frameworks like AID-TANE to effectively integrate AI into nursing education, ensuring that students are ready for a technologically advanced practice setting.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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