Assessing Digital Literacy Among Nursing Faculty Under the Artificial Intelligence-Enhanced Technological Pedagogical Content Knowledge Framework: Cross-Sectional Survey Analysis.

IF 5
JMIR nursing Pub Date : 2026-06-11 DOI:10.2196/88016
Junyu Zhao, Xiaomin Hua, Rong Hu, Chu Chen, Wanxin Wu, Yaming Zhang, Yuhe Zhang, Aijing Wu, Yu Zhang
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引用次数: 0

Abstract

Background: Digital literacy has become a core competence for nursing faculty to adapt to the digital transformation of education, improve teaching quality, and cultivate innovative nursing talents.

Objective: This study aimed to investigate the digital literacy status and influencing factors among nursing faculty in colleges and universities in Fujian province, China.

Methods: A cross-sectional survey analysis was conducted among 339 participants from July 2023 to June 2024 by selecting nursing faculty from 3 medical universities and 5 colleges in Fujian province. A general information questionnaire and a teacher digital literacy questionnaire (designed based on the artificial intelligence-enhanced technological pedagogical content knowledge theoretical model) were used to conduct the survey. The questionnaires included the following dimensions: an intelligent integration ethics layer (digital social responsibility), attention to the moral boundaries of applying technology; an awareness layer (digital awareness), the willingness to actively adapt to technological changes; a knowledge layer (digital technology knowledge and skills), mastery of the integration point of intelligent tools and subject teaching; an ability layer (digital application), the ability to design intelligent teaching plans; and a thinking layer (professional development; innovative thinking for the critical integration of technology). Statistical analysis included descriptive statistics, a 1-way ANOVA, Pearson correlation analysis, and multiple linear regression (using SPSS 28.0 software).

Results: The overall digital literacy of the nursing faculty was at a medium level (mean score 101.92, SD 16.47), with the highest score in digital awareness (mean 20.21, SD 9.43) and the lowest score in digital technology knowledge and skills (mean 9.68, SD 2.92). For the dimension of digital technology knowledge and skills, both age (β=-.142; P=.009) and years of teaching (β=-.147; P=.006) were significant negative predictors. Regarding digital application, age was found to be a significant negative predictor (β=-0.124; P=.02) but teaching experience was a positive predictor (β=0.123, P=.02). Similarly, age also had a significant negative impact on the professional development dimension (β=-.153; P=.005) and the overall digital literacy level (β=-.136; P=.01).

Conclusions: The digital literacy of nursing faculty is at a medium level, with especially low scores in technical knowledge. Age and teaching experience are key influencing factors. Recommendations to promote balanced development of awareness and skills include providing targeted training for senior faculty, integrating courses with clinical practice, optimizing the allocation of digital resources, promoting interdisciplinary cooperation, and strengthening ethical and safety training.

人工智能增强技术教学内容知识框架下护理教师数字素养评估:横断面调查分析。
背景:数字素养已成为护理教师适应教育数字化转型、提高教学质量、培养创新型护理人才的核心竞争力。目的:了解福建省高校护理教师数字素养现状及影响因素。方法:采用横断面调查方法,于2023年7月至2024年6月对福建省3所医科大学和5所高等专科学校的护理师资进行调查分析。采用一般信息问卷和教师数字素养问卷(基于人工智能增强技术教学内容知识理论模型设计)进行调查。问卷包括以下几个维度:智能整合伦理层(数字社会责任)、对应用技术的道德边界的关注;意识层(数字意识),积极适应技术变革的意愿;有知识层(数字技术知识与技能),掌握智能工具与学科教学的结合点;具备能力层(数字化应用),设计智能化教案的能力;和思维层(专业发展;创新思维为关键集成技术)。统计分析包括描述性统计、单因素方差分析、Pearson相关分析和多元线性回归(使用SPSS 28.0软件)。结果:护理教师整体数字素养处于中等水平(平均得分为101.92,SD为16.47),数字意识得分最高(平均得分为20.21,SD为9.43),数字技术知识技能得分最低(平均得分为9.68,SD为2.92)。在数字技术知识和技能维度上,年龄(β=- 0.142; P= 0.009)和教学年限(β=- 0.147; P= 0.006)是显著的负向预测因子。在数字应用方面,年龄是显著的负向预测因子(β=-0.124, P= 0.02),教学经验是显著的正向预测因子(β=0.123, P= 0.02)。同样,年龄对专业发展维度(β=- 0.153; P= 0.005)和整体数字素养水平(β=- 0.136; P= 0.01)也有显著的负向影响。结论:护理教师的数字素养处于中等水平,技术知识得分尤其低。年龄和教学经验是主要影响因素。促进意识和技能平衡发展的建议包括为高级教师提供有针对性的培训,将课程与临床实践相结合,优化数字资源的配置,促进跨学科合作,加强道德和安全培训。
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CiteScore
5.20
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0.00%
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审稿时长
16 weeks
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