Personal and Social Determinants of School Leaders' Behavioural Intention to Use Generative Artificial Intelligence

IF 5.7 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2026-06-05 DOI:10.1002/jcal.70274

Masoumeh Kouhsari, Junjun Chen

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引用次数: 0

Abstract

Background

The emergence of generative artificial intelligence (GAI) tools such as ChatGPT is reshaping discussions of digital transformation in schools across China and Hong Kong, drawing increasing attention to the role of school leaders in AI-related decision-making. Despite growing interest in AI integration in education, limited research has examined the factors influencing school leaders' intentions to use GAI.

Objectives

This study investigates how personal factors (trust in AI and AI anxiety) and job-related factors (digital social support and digital social pressure) influence school leaders' behavioural intention to use GAI, and to examine the mediating roles of perceived usefulness and perceived ease of use in these relationships.

Methods

Using data from 400 school leaders in China and Hong Kong, this study applied structural equation modelling (SEM) to test how personal and job-related factors and the mediating roles of perceived usefulness and perceived ease of use shape behavioural intention to use GAI.

Results and Conclusions

Trust in AI positively predicted school leaders' intentions to use GAI, whereas AI anxiety showed no direct effect; digital social pressure had a negative impact, and digital social support influenced intention only indirectly through perceived usefulness and ease of use, highlighting the importance of personal and job-related factors for effective AI integration in schools.

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学校领导使用生成式人工智能行为意向的个人和社会决定因素

ChatGPT等生成式人工智能（GAI）工具的出现，正在重塑中国和香港各地学校对数字化转型的讨论，使人们越来越关注学校领导在人工智能相关决策中的作用。尽管人们对人工智能在教育中的整合越来越感兴趣，但有限的研究调查了影响学校领导使用人工智能意愿的因素。本研究探讨了个人因素（对人工智能的信任和人工智能焦虑）和工作相关因素（数字社会支持和数字社会压力）如何影响学校领导使用人工智能的行为意向，并考察了感知有用性和感知易用性在这些关系中的中介作用。方法利用来自中国和香港的400名学校领导的数据，运用结构方程模型（SEM）来检验个人和工作相关因素以及感知有用性和感知易用性的中介作用如何影响使用GAI的行为意愿。结果与结论对人工智能的信任正向预测学校领导使用人工智能的意愿，而人工智能焦虑无直接影响；数字社会压力具有负面影响，数字社会支持仅通过感知有用性和易用性间接影响意向，突出了个人和工作相关因素对学校有效人工智能整合的重要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

9.70

自引率

6.00%

发文量

116

期刊介绍： The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope