基于TAM-IDT整合模型的基层公务员AI素养培育路径研究

doi:10.13998/j.cnki.issn1002-1248.25-0325

Abstract

Abstract:

[Purpose/Significance] As digital government accelerates, the artificial intelligence (AI) literacy of grassroots civil servants has become critical to promoting smart government management. Grassroots-level civil servants who possess high levels of digital and AI literacy are indispensable drivers in establishing a digital and smart government. However, significant differences among grassroots civil servants in AI literacy and digital skills adaptation make it difficult for them to fully adapt to the requirements of smart government management. To effectively apply AI technologies in grassroots governance, it is essential for the effective application of AI technologies in grassroots governance to systematically identify its influencing factors and propose targeted cultivation paths, thereby improving public service quality and governance efficiency. [Method/Process] This study integrates the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT) to construct a TAM-IDT analytical framework. Based on empirical research identifying the AI literacy deficiencies of current grassroots civil servants, the TAM-IDT analytical framework systematically examines the impact mechanisms of key variables, perceived usefulness, perceived ease of use, and behavioral attitude, on AI literacy. The framework also proposes stage-based and group-specific cultivation strategies. The study uses local government civil servants as its research sample. It collects data through questionnaires and interviews, and employs structural equation modeling and mediation effect analysis for empirical validation. [Results/Conclusions] The findings reveal that behavioral attitude has a significant positive impact on AI literacy. Perceived usefulness notably enhances behavioral intention, while perceived ease of use has a negative effect on behavioral attitude, suggesting that individuals who perceive greater difficulty may be more motivated to learn. However, one of the highlights of this study is that civil servants who are proficient in AI technology or have used it in their work have a lower desire to learn more about it. Further analysis shows that perceived ease of use positively influences behavioral attitude indirectly through perceived usefulness. Additionally, both cognitive variables indirectly affect AI literacy via behavioral attitude, forming a "cognition-intention-behavior" influence chain. Based on these results and the classification of stages and types of technology adoption using Innovation Diffusion Theory (IDT), a three-dimensional, differentiated AI literacy cultivation strategy called "perception diffusion collaboration" was proposed. This strategy is based on the five elements, stages, and the groups of people involved in innovation diffusion. It offers a theoretical foundation and practical path for improving AI literacy among grassroots civil servants and advancing the modernization of grassroots governance.

Key words: AI literacy, technology acceptance model, grassroots civil servants, innovation diffusion theory, governance modernization

CLC Number:

D630.3

ZHANG Weichong, XU Chen, ZHU Yiran. Cultivation Path of AI Literacy for Grassroots Civil Servants Based on the Integrated TAM-IDT Model[J].Journal of library and information science in agriculture, 2025, (): 1-14.

Figures/Tables 6

Fig.1

Table 1

Table 2

Conceptualization and categorization extraction process and results of semi-structured interviews"

原始访谈资料中的代表性语句	概念化（初始概念）	范畴化（概念范畴）
A01 像办公软件、政务系统这样的数字技术，在日常工作中经常接触	数字技术日常使用频率	数字技术使用频率
A02 像你说的目录生成、交叉引用、写材料时用数据透视表这些更高级的办公软件运用，简单的我们都会用，复杂函数不经常用	办公软件复杂功能掌握程度	数字素养基础能力
A04 在基层治理中引入AI技术，我所了解到的相关政府部门都还没推广使用，只是听过名字	基层治理AI应用场景认知	AI素养认知
A10 AI技术在单位的推广，领导和同事的态度差异大，年轻的同事更愿意学习尝试	AI技术推广态度差异
A14 未来基层工作中AI技术可能会在智慧社区治理扩大规模，普及化地去使用	AI未来应用预判
A03 目前单位已配备智能办公软件，有时会用AI辅助写作，但像你说的使用AI智能数据分析工具，这个就很少，几乎没有	智能办公软件配备及使用情况	AI素养实践
A06 推广AI技术助力基层工作肯定是会遇到一系列的顾虑或难题的	AI技术推广顾虑
A08 在使用AI技术过程中遇到过的技术故障或不兼容问题，比如服务器繁忙等	AI技术应用故障
A07 AI技术对提升工作效率的帮助程度，在智能分类文件工作中体现得较明显	AI效率提升感知	AI素养价值意识
A11 现在学会用AI，肯定能提高我们工作效率，对我们的职业发展也有积极影响，可能会改变职业路径	AI素养职业发展关联
A12 对比传统工作方式，AI辅助下工作质量有提高，但目前变化不很明显	AI工作质量影响
A09 目前基层公务员在AI素养提升上，最缺的资源是理论，很多同事理论知识学不会	AI素养提升资源缺口	AI素养提升需求
A13 参与过AI相关的交流分享会，感受到交流内容对实际工作有一定帮助	AI交流分享效能
A13 未来还是希望能有多一些这方面的培训，教我们一些强实操性的办公技能吧	AI培训需求

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指标	删除项后的平均值	删除项后的方差	删除的项与删除项后的总体的相关性	删除项后的 Cronbach's α系数
AI使用频率	40.977	34.221	0.087	0.907
数字素养基础	41.185	33.229	0.583	0.844
AI使用熟练度	40.921	32.042	0.678	0.837
AI工作准确性评价	40.883	31.011	0.557	0.844
AI素养认知	41.543	34.282	0.285	0.862
AI技术学习速度	40.958	30.962	0.884	0.827
单位AI使用需求	43.053	37.565	-0.024	0.877
AI技术接受速度	41.128	32.336	0.770	0.835
AI工作时效性评价	42.091	31.805	0.738	0.834
提升自身AI素养重要性	40.958	30.962	0.884	0.827
提升AI素养意愿程度	41.158	33.159	0.913	0.836
简便程度	40.996	30.156	0.863	0.824
素养评价	41.158	33.159	0.913	0.836

因子	变量	非标准载荷系数	标准化载荷系数	z	S.E.	P
感知有用性	AI工作准确性评价	1	0.623	-	-	-
	AI工作时效性评价	0.826	0.729	4.609	0.179	0.000***
	提升自身AI素养重要性	1.023	0.926	5.47	0.187	0.000***
	AI使用频率	0.33	0.134	0.962	0.343	0.336
感知易用性	简便程度	1	0.993	-	-	-
行为态度	提升AI素养意愿程度	1	0.995	-	-	-
素养水平	数字素养基础	1	0.597	-	-	-
	AI使用熟练度	1.523	0.826	4.82	0.316	0.000***
	AI素养认知情况	0.804	0.354	2.449	0.328	0.014**
	AI技术学习速度	1.507	0.865	4.965	0.303	0.000***
	素养评价	1.136	0.995	5.389	0.211	0.000***

自变量	因变量	直接效应系数	间接效应系数	总效应系数	中介效应占比/%
感知易用性	行为态度	-0.367**	0.612***	0.245**	71.63
感知易用性	AI素养水平	0.138	0.521***	0.659***	79.06
感知有用性	AI素养水平	0.214**	0.557***	0.771***	72.24

Cultivation Path of AI Literacy for Grassroots Civil Servants Based on the Integrated TAM-IDT Model

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