Technology acceptance mediates associations between pre-service physical education teachers’ AI-TPACK and study engagement and behavioral intentions in digital teaching

Against the backdrop of artificial intelligence (AI) reshaping the educational landscape, the digital transformation of physical education has placed greater demands on preservice physical education teachers’ (PSPETs’) capacity to integrate technology. However, research remains limited on the effects of pres-ervice physical education teachers’ artificial intelligence technological pedagogical content knowledge (PSPETs AI-TPACK) on their study engagement (SE) and behavioral intentions (BI) in digital teaching, as well as on the role played by technology acceptance (TA) in these relationships.This study involved 1,144 undergraduate and postgraduate students enrolled in physical education, physical education teaching, or physical education and training programmes at five higher education institutions in Guangzhou, Guangdong Province. Using adapted scales, data were collected on PSPETs AI-TPACK, TA, SE, and BI.

Structural equation modelling (SEM) was then employed to examine the relationships among these variables and the mediating effects. The findings showed that PSPETs AI-TPACK significantly and positively predicted both SE and BI in digital teaching. TA played a significant partial mediating role in the relationships between PSPETs AI-TPACK and SE, and between PSPETs AI-TPACK and BI.

These results indicate that PSPETs AI-TPACK can promote PSPETs’ SE and BI both directly and indirectly by enhancing their TA. This study extends the theoretical understanding of the relationships between PSPETs AI-TPACK and SE and BI in digital physical education teaching, while also providing empirical evidence for improving preservice physical education teacher education in higher education institutions. Higher education institutions should incorporate AI-based instructional design and practice into physical education teacher education curricula, implement tiered and progressive technology training, create authentic digital teaching contexts, and enhance PSPETs’ TA through resource provision and exemplary applications.

These measures can, in turn, strengthen PSPETs’ SE and BI in using AI technologies to support physical education teaching. I am deeply grateful to my advisor, Professor Yaqin Ren, for her mentorship and trust in my research. Funding for this project was provided by the National Social Science Fund Post-Doctoral Support Program (24FTYB008), the Ministry of Education Humanities and Social Sciences Research Planning Project (25YJA890046), and the Guangdong Provincial Educational Science Planning Project (Higher Education Special Program): Research on the Formation Mechanism and Cultivation Pathways of Digital Teaching Competency for PE Normal Students.

This study is supported by the following projects: Post-funded General Project of the National Social Science Fund of China (Grant No. 24FTYB008, Project Title: Research on the Physical Education Academic Proficiency Test System in Middle Schools in China); the Ministry of Education Humanities and Social Sciences Research Planning Project (Grant No. 25YJA890046, Project Title: A Study on the Mechanisms for the Transformation and Upgrading of School Physical Education Empowered by Digital Technology and the Governance of Ethical Risks); Guangdong Provincial Educational Science Planning Project (Higher Education Special Program): Research on the Formation Mechanism and Cultivation Pathways of Digital Teaching Competency for PE Normal Students. School of Physical Education, Guangzhou Sport University, Guangzhou, China The authors declare no competing interests. This study obtained ethical approval from the Ethics Application Committee of Guangzhou Sport University (Registration number: 2026LCLL-003) before conducting the survey.

The participants provided their written informed consent to participate in this study. All methods were carried out in accordance with relevant guidelines and regulations. Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.