Supplementary file 1_Teacher-reviewed generative AI action-analysis materials for university dance training: action understanding, body awareness, feedback uptake, and revised performance.pdf

Mixed-effects and repeated-measures ordinal models were used to account for repeated action-unit records.</p>Results<p>Teacher-reviewed GenAI action-analysis materials were associated with higher revised training quality than conventional teacher text cues (estimate = 5.09, 95% CI [4.14, 6.03]), higher action understanding (estimate = 1.97, 95% CI [1.62, 2.32]), and higher immediate body awareness (estimate = 0.36, 95% CI [0.28, 0.43]).

A long-format phase-by-material sensitivity model also showed a larger initial-to-revised change under the GenAI condition (interaction = 1.68, 95% CI [1.01, 2.34]). In the process model, initial performance had the largest standardized coefficient, while action understanding, immediate body awareness, and feedback adoption remained positive predictors of revised training quality.</p>Discussion<p>Teacher-reviewed GenAI action-analysis materials were associated with stronger revised performance and more favorable learning-process indicators than conventional teacher text cues.

The findings suggest that GenAI-supported action analysis may be useful when incorporated into teacher-mediated dance instruction, particularly as a structured aid for interpreting feedback and refining movement attempts.</p>