Generative AI in physical education and health
A narrative review and conceptual framework for interdisciplinary thematic learning
Bibliographic Data
| ID | 22082166 |
|---|---|
| Authors | Gewenjin Zhu (Soochow University), Xi Dai (0000-0002-1610-3392, Soochow University), Suqi Jiang (Soochow University), Zili Wang (0000-0002-5003-3092, Soochow University), Mengyuan Liang (0000-0002-7848-9411, Soochow University), Yuchen Pan (0000-0001-9260-4562, Soochow University), Yuliu Tao (Soochow University, corresponding author) |
| Year | 2026 |
| Volume | 14 |
| Pages | 1842782-1842782 |
| Publication date | 2026-06-03 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2026.1842782 |
| PMID | 42317995 |
| OpenAlex | W7163404881 |
| Language | EN |
| References cited | 72 |
Generative artificial intelligence (GenAI) has created new possibilities for teaching and learning, yet its pedagogical role in physical education and health (PEH) remains underdeveloped. Current AI-related research in PEH has largely focused on performance-oriented and technical applications, such as motion analysis, skill evaluation, and training monitoring, with less attention to curriculum design, interdisciplinary learning, and teacher-mediated pedagogical use. This narrative review synthesizes literature on GenAI in PEH and related interdisciplinary or thematic learning contexts to examine how GenAI may support interdisciplinary thematic learning in PEH. The review highlights an emerging shift from AI as a technical or analytical tool toward GenAI as a pedagogical resource for lesson planning, assessment design, feedback, inquiry support, and knowledge integration. Based on this synthesis, the study proposes a pedagogical framework that positions GenAI as a teacher-mediated resource for connecting bodily practice, health knowledge, reflective inquiry, and social participation. The framework includes four core dimensions: curriculum and goal alignment, content organization and task design, inquiry and learning process support, and assessment and adaptive adjustment. It also emphasizes human-AI collaboration, teacher judgment, embodied observation, and ethical use as necessary conditions for meaningful implementation. The review suggests that GenAI may support PEH when it is integrated carefully into pedagogically designed, context-sensitive, and health-promoting learning processes. Future empirical research, particularly design-based studies and classroom interventions, is needed to test and refine the framework in authentic PEH settings
Conceptual framework · Curriculum · Embodied cognition · Generative grammar · Narrative · Physical education · Thematic analysis · Artificial Intelligence in Healthcare and Education · Children's Physical and Motor Development · Physical Education and Pedagogy
Future research recommendations for transforming higher education with generative AI
Embracing the future of Artificial Intelligence in the classroom
The emergent role of artificial intelligence, natural learning processing, and large language models in higher education and research
Designing assessments in the generative AI era
Application of digital-intelligent technologies in physical education
Exploring Decision-Making Competence in Sugar-Substitute Choices
Becoming human with technology
The paradox of experience
From policy ambition to classroom practice
How does generative AI learning support affect vocational college students’ employability? – An empirical analysis based on latent profiles and interdisciplinary learning chain pathways
The impact of Generative AI (GenAI) on practices, policies and research direction in education
A Checklist for Using Generative Artificial Intelligence to Create Lesson Plans in K–12 Physical Education
Beyond the Basics
Creating Assessments Using Artificial Intelligence
Evolving Professionalism in the AI Era
Unlocking Educational Potential
Using Artificial Intelligence and the Teach-SAN-TA Model for All Domains of Learning
The impact of generative AI on health professional education
Enhancing Badminton Rule Learning Through a GPT ‐Integrated Line Bot
Promoting Interdisciplinary Learning With Generative AI Through Self‐Regulated Scaffolding
Promoting AI literacy in social work education
Emotion‐Aware AI in Physical Education
Help of ChatGPT about math skills on the subjects of social studies
Students' use patterns of generative artificial intelligence during problem‐solving in an intelligent learning system
Examining interactive AI-supported learning environments
Fostering preservice teachers’ interdisciplinary curriculum development through generative AI-mediated knowledge-building practices
Searching for the alternative
Digital feedback via free ChatGPT within the reciprocal teaching style
A qualitative case study of primary classroom teachers’ perceived value of physical education in New Zealand
Physical education and health curriculum reform in China
Comparing AI-assisted and traditional tactical instruction
| Citation velocity | historical |
|---|---|
| Highly cited | No |