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
Source journal for Chinese Science Citation Database
China Academic Journals Full-text Database
China Core Journal Alternative Database
Scopus
AI-powered Nursing Education

The current situation and reflection on the application of generative artificial intelligence assisted learning for vocational nursing students

  • Nenping WU ,
  • Shaohua CHEN ,
  • Biaojun YU ,
  • Xiaojing CHEN
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Received date: 2024-08-09

  Online published: 2025-04-16

Abstract

Objective To understand the current application status of generative artificial intelligence(Gen AI) in the learning of vocational nursing students,analyze its positive impact and potential problems.Methods All the students(n=1 262) in nursing school of a medical college were selected as the research participants. In investigation,a self-made questionnaire was used to investigate the use of Gen AI,and multiple response analysis was carried out. The purpose sampling method was used to select students who had used Gen AI assisted learning in the survey to conduct interviews,and the theme analysis method was applied to refine the theme.Results Among the participated students,417(33.0%) had used Gen AI for assisted learning in the past six months,who mainly applied Gen AI in the scenarios of understanding knowledge points(58.5%),querying information(56.4%),and less in creative inspiration(28.3%) and tracking the latest medical progress(17.3%). The main way of asking questions was to directly inquiry of specific questions(68.6%),use open-ended questions to seek multiple answers(49.2%),and rarely use guiding prompts(38.4%) and professional terminology(36.0%). The interview results indicated that students believed that Gen AI provided an efficient and convenient path for knowledge acquisition,making it a powerful learning assistant. However,they also expressed concerns about the usage process and expectations for deep application.Conclusion Gen AI shows great potential in assisting students’ learning. Also,it faces many problems and challenges. Schools and teachers should intervene in the weak points and deficiencies of vocational nursing students in applying Gen AI assisted learning,and actively respond to new educational challenges and difficulties in the digital age.

Cite this article

Nenping WU , Shaohua CHEN , Biaojun YU , Xiaojing CHEN . The current situation and reflection on the application of generative artificial intelligence assisted learning for vocational nursing students[J]. Chinese Journal of Nursing Education, 2025 , 22(4) : 403 -408 . DOI: 10.3761/j.issn.1672-9234.2025.04.004

References

[1] Lee U, Han A, Lee J, et al. Prompt Aloud!Incorporating image-generative AI into STEAM class with learning analytics using prompt data[J]. Educ Inf Technol, 2024, 29(8):9575-9605.
[2] 吴河江, 吴砥. 生成式人工智能教育应用:发展历史、国际态势与未来展望[J]. 比较教育研究, 2024, 46(6):13-23.
[2] Wu HJ, Wu D. Generative artificial intelligence application in education:history,international situation and future development[J]. Int Comp Educ, 2024, 46(6):13-23.
[3] 杨扬, 姬靖. 国内人工智能辅助教育研究现状、热点与趋势[J]. 航海教育研究, 2024, 41(2):1-7.
[4] 马欣悦. 高职学生学习者特征及教学策略研究[D]. 上海: 华东师范大学, 2021.
[5] Saunders B, Sim J, Kingstone T, et al. Saturation in qualitative research:exploring its conceptualization and operationalization[J]. Qual Quant, 2018, 52(4):1893-1907.
[6] 李艳, 许洁, 贾程媛, 等. 大学生生成式人工智能应用现状与思考:基于浙江大学的调查[J]. 开放教育研究, 2024, 30(1):89-98.
[6] Li Y, Xu J, Jia CY, et al. Investigation of college students’ generative artificial intelligence(GAI) usage status and its implication:taking Zhejiang University as an example[J]. Open Educ Res, 2024, 30(1):89-98.
[7] Braun V, Clarke V. Using thematic analysis in psychology[J]. Qual Res Psychol, 2006, 3(2):77-101.
[8] 戚佳, 徐艳茹, 刘继安, 等. 生成式人工智能工具使用对高校学生批判性思维与自主学习能力的影响[J]. 电化教育研究, 2024, 45(12):67-74.
[8] Qi J, Xu YR, Liu JA, et al. The impact of generative artificial intelligence tools on college students’ critical thinking and autonomous learning ability[J]. E Educ Res, 2024, 45(12):67-74.
[9] 沈唯. 新兴技术描绘医学教育多样前景[N]. 科技日报, 2024-01-10(005).
[10] 赵晓伟, 戴岭, 沈书生, 等. 促进高意识学习的教育提示语设计[J]. 开放教育研究, 2024, 30(1):44-54.
[11] Liu PF, Yuan WZ, Fu JL, et al. Pre-train,prompt,and predict:a systematic survey of prompting methods in natural language processing[J]. ACM Comput Surv, 2023, 55(9):1-35.
[12] Giray L. Prompt engineering with ChatGPT:a guide for academic writers[J]. Ann Biomed Eng, 2023, 51(12):2629-2633.
[13] 赵晓伟, 祝智庭, 沈书生. 教育提示语工程:构建数智时代的认识论新话语[J]. 中国远程教育, 2023(11):22-31.
[14] 戴岭, 赵晓伟, 祝智庭. 智慧问学:基于ChatGPT的对话式学习新模式[J]. 开放教育研究, 2023, 29(6):42-51,111.
[14] Dai L, Zhao XW, Zhu ZT. A new inquiry learning:conversational learning with ChatGPT[J]. Open Educ Res, 2023, 29(6):42-51,111.
[15] Zhang P, Tur G. A systematic review of ChatGPT use in K-12 education[J]. Eur J Educ, 2024, 59(2):e12599.
[16] 翟雪松, 楚肖燕, 焦丽珍, 等. 基于“生成式人工智能+元宇宙” 的人机协同学习模式研究[J]. 开放教育研究, 2023, 29(5):26-36.
[16] Zhai XS, Chu XY, Jiao LZ, et al. An empirical study on the effectiveness of human-computer collaborative learning based on “generative artificial intelligence + metaverse”[J]. Open Educ Res, 2023, 29(5):26-36.
[17] 单俊豪, 刘永贵. 生成式人工智能赋能学习设计研究[J]. 电化教育研究, 2024, 45(7):73-80.
[17] Shan JH, Liu YG. Research on learning design empowered by generative artificial intelligence[J]. E Educ Res, 2024, 45(7):73-80.
[18] 刘三女牙, 郝晓晗. 生成式人工智能助力教育创新的挑战与进路[J]. 清华大学教育研究, 2024, 45(3):1-12.
[18] Liu SNY, Hao XH. The challenges and approaches of AIGC in facilitating educational innovation[J]. Tsinghua J Educ, 2024, 45(3):1-12.
[19] 黄露葵, 程思嘉, 张孝琳, 等. 基于ChatGPT、文心一言等生成式人工智能的新商科人才培养策略研究[J]. 大学教育, 2024, 13(10):129-132,138.
[20] Tom K. ChatGPT(We need to talk)[EB/OL]. (2023-04-03)[2024-07-23]. https://news.educ.cam.ac.uk/230403-chat-gpt-education.
[21] Alkaissi H, McFarlane SI. Artificial hallucinations in ChatGPT:implications in scientific writing[J]. Cureus, 2023, 15(2):e35179.
[22] Wong GKW, Ma XJ, Dillenbourg P, et al. Broadening artificial intelligence education in K-12:where to start?[J]. ACM Inroads, 2020, 11(1):20-29.
[23] 张惠彬, 许蕾. 生成式人工智能在教育领域的伦理风险与治理路径:基于罗素大学集团的实践考察[J]. 现代教育技术, 2024, 34(6):25-34.
[23] Zhang HB, Xu L. Ethical risks and governance approaches of generative artificial intelligence in education:based on the practical investigation of the Russell University Group[J]. Mod Educ Technol, 2024, 34(6):25-34.
[24] UNESCO. Guidance for generative AI in education and research[EB/OL]. (2023-09-07)[2024-07-25]. https://www.unesco.org/en/articles/uidance-generative-ai-education-and-research.
[25] 李云晓, 李红, 陈选超. 人工智能生成式预训练模型辅助的对话式学习审视[J]. 成都师范学院学报, 2023, 39(7):116-124.
[25] Li YX, Li H, Chen XC. A review of conversational learning assisted by AI generative pre-trained transformers[J]. J Chengdu Norm Univ, 2023, 39(7):116-124.
[26] 赵晓伟, 沈书生, 祝智庭. 数智苏格拉底:以对话塑造学习者的主体性[J]. 中国远程教育, 2024(6):13-24.
[26] Zhao XW, Shen SS, Zhu ZT. I-Socratic:shaping the learner’s agency through dialogue[J]. Chin J Distance Educ, 2024(6):13-24.
[27] 卢宇, 余京蕾, 陈鹏鹤. 基于大模型的教学智能体构建与应用研究[J]. 中国电化教育, 2024(7):99-108.
[27] Lu Y, Yu JL, Chen PH. Design and application of pedagogical agent with foundation model[J]. China Educ Technol, 2024(7):99-108.
[28] 刘明, 杨闽, 吴忠明, 等. 教育大模型智能体的开发、应用现状与未来展望[J]. 现代教育技术, 2024, 34(11):5-14.
[28] Liu M, Yang M, Wu ZM, et al. Development,application status and future prospect of large language model agents for education[J]. Mod Educ Technol, 2024, 34(11):5-14.
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