BMC Nursing (May 2024)

Experience of undergraduate nursing students participating in artificial intelligence + project task driven learning at different stages: a qualitative study

  • Weijuan Kong,
  • Yanhua Ning,
  • Ting Ma,
  • Fei Song,
  • Yuxin Mao,
  • Cailing Yang,
  • Xinjin Li,
  • Yahong Guo,
  • Haiyan Liu,
  • Jing Shi,
  • Lingna Liu

DOI
https://doi.org/10.1186/s12912-024-01982-1
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 10

Abstract

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Abstract Background Artificial intelligence is a growing phenomenon that will soon facilitate wide-scale changes in many professions, and is expected to play an important role in the field of medical education. This study explored the realistic feelings and experiences of nursing undergraduates participating in different stages of artificial intelligence + project task driven learning, and provide a basis for artificial intelligence participation in nursing teaching. Methods We conducted face-to-face semi-structured interviews with nursing undergraduates participating in Nursing Research Course which adopts artificial intelligence + project task driven learning from a medical university in Ningxia from September to November 2023, to understand their experience of using artificial intelligence for learning and the emotional changes at different stages. The interview guide included items about their personal experience and feelings of completing project tasks through dialogue with artificial intelligence, and suggestions for course content. Thematic analysis was used to analyze interview data. This study followed the COREQ checklist. Results According to the interview data, three themes were summarized. Undergraduate nursing students have different experiences in participating in artificial intelligence + project task driven learning at different stages, mainly manifested as diverse emotional experiences under initial knowledge deficiency, the individual growth supported by external forces during the adaptation period, and the expectations and suggestions after the birth of the results in the end period. Conclusions Nursing undergraduates can actively adapt to the integration of artificial intelligence into nursing teaching, dynamically observe students’ learning experience, strengthen positive guidance, and provide support for personalized teaching models, better leveraging the advantages of artificial intelligence participation in teaching.

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