AI-Powered Assessment of Motor Development: Using Platforms Like KineticAI to Analyze Fundamental Movement Skills in Children.

The aim of this study is to examine the precision, dependability, and relevance of AI-based evaluations in contrast to conventional human evaluations. In all, 200 7–8-year-old students from urban and suburban schools participated in the study. Based on movement speed, accuracy, and smoothness, Kinet...

Descripción completa

Detalles Bibliográficos
Publicado en:	Perceptual & Motor Skills Vol. 133; no. 2; pp. 276 - 299
Autores principales:	Guo, Jing Xuan, Zhang, Gao Hua, Zhang, You Ming
Formato:	Artículo
Publicado:	Sage Publications Inc. Apr2026
Materias:	Motor ability Suburbs Elementary schools Artificial intelligence Sex distribution Socioeconomic factors Child development Metropolitan areas Psychometrics Analysis of variance Children Multitrait multimethod techniques Random forest algorithms Pearson correlation (Statistics) T-test (Statistics) Research funding Research evaluation Running Questionnaires Descriptive statistics Support vector machines Intraclass correlation Statistical reliability Artificial neural networks Body movement Jumping Machine learning Confidence intervals Data analysis software Sensitivity & specificity (Statistics) Postural balance Physical activity Motion capture (Human mechanics)
Acceso en línea:	Ver este registro en EBSCOhost