eISSN 2097-6054 ISSN 1672-9234 CN 11-5289/R
Responsible Institution:China Association for Science and Technology
Publishing:Chinese Nursing Journals Publishing House Co.,Ltd.
Sponsor:Chinese Nursing Association
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Chinese Journal of Nursing Education ›› 2026, Vol. 23 ›› Issue (6): 689-696.doi: 10.3761/j.issn.1672-9234.2026.06.008

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Analysis of the gap between nursing students’ acceptance and use behavior of artificial intelligence technology in courses and its causes

JIN Wentao(), ZHAO Juanjuan, CAO Xi, BAI Yang, CHENG Li, ZHENG Jing, LI Kun*()   

  1. School of NursingSun Yat-Sen UniversityGuangzhou 510080, China
  • Received:2025-12-12 Online:2026-06-15 Published:2026-06-18
  • Contact: *LI Kun,E-mail:likun22@mail.sysu.edu.cn E-mail:jinwt5@mail.sysu.edu.cn;likun22@mail.sysu.edu.cn
  • Supported by:
    Key Project of Higher Education Teaching Reform Research and Practice under the Sun Yat-sen University Teaching Quality Engineering Program:a teacher-student dual-perspective study on technology acceptance of generative AI application scenarios in nursing courses and curriculum optimization

Abstract:

Objective To explore the gap between nursing students’ acceptance of artificial intelligence(AI) technology in courses and their actual use behavior,as well as the underlying causes. Methods An explanatory sequential mixed-methods design was adopted. In June 2025,a convenience sample of 72 nursing students was recruited from three nursing AI-enhanced courses. A self-designed questionnaire on technology acceptance and a use behavior survey were used for data collection. From July to August 2025,purposive sampling was employed to select 12 students and 5 teachers for semi-structured interviews,and interview data were analyzed using thematic analysis. Results Quantitative results showed that among the 72 students,the acceptance of AI technology in the courses was moderately high(median of the mean item score of the questionnaire was 3.93 points),compared with the midpoint score of 3 on the scale. However,the frequency of actual use was low,with only 14% of students reporting using AI frequently(4-6 times per week) or daily,indicating a cognition-behavior gap. Qualitative findings suggested that this gap was attributed to a mismatch between platform functions and learning needs,insufficient motivation to use AI,limited AI literacy,and inertia in traditional learning habits. Conclusion There is a gap between nursing students’ technology acceptance of AI-enhanced courses and their actual use behavior. Targeted measures,including demand-oriented function optimization,strengthening use motivation,providing AI literacy training,and organically integrating AI into teaching,are needed to narrow this gap and promote the development and application of nursing AI-enhanced courses.

Key words: Education, Nursing, AI-Enhanced Courses, Technology Acceptance, Technology Use Behavior, Mixed-Methods Research