Xiong Peng, Zhang Yuanyuan
School of Economics and Management, Hubei Engineering University, Xiaogan, China.
Department of English Language and Literature, Pukyong National University, Busan, South Korea.
Disabil Rehabil Assist Technol. 2025 Sep 23:1-19. doi: 10.1080/17483107.2025.2561927.
This study investigates how Technological Pedagogical Content Knowledge (TPACK) influences Artificial Intelligence Acceptance (AIA) among Chinese university English teachers, focusing on the dual mediating roles of organisational support and self-efficacy. Drawing on structural equation modelling of survey data from 153 instructors, the results show that TPACK significantly predicts AIA, with self-efficacy accounting for this relationship. Drawing on a structural equation model analysis of survey data from 153 English instructors, we demonstrate that TPACK significantly predicts AIA, and self-efficacy played an explanatory role in this relationship. Organisational support further mediates the pathway from AI-Technical Knowledge (AI-TK) to TPACK, highlighting institutional mechanisms that strengthen teachers' pedagogical capacity for AI integration. Three critical pathways are identified: (1) a direct TPACK → AIA trajectory, (2) an AI-TK → OS → TPACK → AIA institutional chain and (3) a TPACK → SE → AIA motivational loop. Positioning AI as a form of assistive technology, the findings highlight its role in enhancing teachers' instructional capacity while promoting accessibility, personalised scaffolding and inclusive opportunities for diverse learners. By integrating Human-Computer Interaction (HCI) and assistive technology perspectives, the study reframes TPACK as interaction readiness, organisational support as a socio-technical affordance, and self-efficacy as interaction efficacy. This interdisciplinary framing highlights that AI acceptance is not only a matter of knowledge and psychology, but also of designing human-AI collaborations that promote usability, accessibility and inclusive pedagogy. The results offer actionable implications for AI training programs, highlighting the importance of integrating technical upskilling with organisational mechanisms.
本研究调查了技术教学内容知识（TPACK）如何影响中国大学英语教师对人工智能的接受度（AIA），重点关注组织支持和自我效能的双重中介作用。基于对153名教师的调查数据进行结构方程建模，结果表明TPACK能显著预测AIA，自我效能在这种关系中起作用。基于对153名英语教师的调查数据进行结构方程模型分析，我们证明TPACK能显著预测AIA，且自我效能在这种关系中起解释作用。组织支持进一步中介了从人工智能技术知识（AI-TK）到TPACK的路径，突出了强化教师人工智能整合教学能力的制度机制。确定了三条关键路径：（1）直接的TPACK→AIA轨迹，（2）AI-TK→OS→TPACK→AIA制度链，以及（3）TPACK→SE→AIA动机循环。将人工智能定位为一种辅助技术形式，研究结果突出了其在提高教师教学能力方面的作用，同时促进了多样化学习者的可及性、个性化支架搭建和包容性机会。通过整合人机交互（HCI）和辅助技术视角，本研究将TPACK重新定义为交互准备度，将组织支持重新定义为社会技术可供性，将自我效能重新定义为交互效能。这种跨学科的框架突出表明，人工智能接受不仅是知识和心理问题，还涉及设计促进可用性、可及性和包容性教学法的人机合作。研究结果为人工智能培训项目提供了可操作的启示，突出了将技术技能提升与组织机制相结合的重要性。
