Actionable companion · Assessment and evidence of learning

From evidence to district action: Generative AI in physical education and health: a narrative review and conceptual framework for interdisciplinary thematic learning

AI-assisted editorial implementation guide. The district actions are proposed applications, not findings or recommendations attributed to the original authors. No additional peer review is asserted.

Evidence and context

Confirm the study population, setting and task before applying its findings to your district.

Original authors’ abstract, reproduced under the linked source license:

Abstract 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. Keywords: conceptual framework, generative artificial intelligence, interdisciplinary thematic learning, narrative review, physical education and health

A 90-day district pilot

1. Days 1–15 · Appraise. Have the curriculum lead and a teacher read the methods and limitations. Record the study design, sample, comparator, outcomes and evidence gaps. Define a local question that the study can help inform.
2. Days 16–30 · Design. Redesign one low-stakes assessment: require a first attempt, an AI-assisted revision, a source-check log and a short oral explanation. Use the same rubric for the comparison task. Name an accountable owner and set the baseline, success threshold and budget before implementation.
3. Days 31–60 · Test. Start with a small voluntary cohort, preserve an accessible non-AI route and require teacher review. Use synthetic or de-identified examples; approve data handling and tool terms through district processes.
4. Days 61–90 · Decide. Blind-score reasoning, factual accuracy and unaided transfer on a fresh task. Record suspected misconduct separately from demonstrated evidence. Compare with baseline, document uncertainty and stop or revise if learning worsens, access is unequal or critical errors persist.

The board decision brief

Report the learning problem, evidence quality, participating population, total cost including review time, measured benefit, errors, access differences and remaining uncertainties. Make a dated recommendation to stop, revise or expand. A positive perception survey alone does not establish learning improvement.

Attribution and reuse

Gewenjin Zhu; Xi Dai; Suqi Jiang; Zili Wang; Mengyuan Liang; Yuchen Pan; Yuliu Tao. Generative AI in physical education and health: a narrative review and conceptual framework for interdisciplinary thematic learning. Frontiers in Public Health (2026-06-03). https://doi.org/10.3389/fpubh.2026.1842782

Companion prepared 2026-10-30. Original authorship and DOI are preserved. The abstract is an attributed source extract; the implementation plan is new AI-assisted editorial material, offered under the same CC BY 4.0 license. This guide has not undergone independent peer review.