Reconstructing Dance Education in the Digital Era: Integrating Artificial Intelligence and Motion Capture for Innovative Talent Development

Abstract

 It is in the nature of the digital transformation of dance education as a fundamental reconstructive imperative and not superficial use of technology. The systematic review considers the way in which artificial intelligence and motion capture technologies are transforming the talent development in performing arts education by evaluating 13 peer-reviewed studies. Based on the case studies of China, India, Singapore, Europe, and North America, such as the DSTEVF system, ReAL-T platform, Smart Steps framework, WhoDo project, and Moveally AI platform, this paper explores technical architectures, education results, and policy frameworks to regulate the technology integration. Results show that AI-motion capture technologies influence positively dance performance and self-efficacy (moderate to substantial effects), but provoke serious issues of preservation of embodied knowledge, transformation of professional identity of the teacher and equity of access. The analysis has a value to educational theory by re-conceptualizing the body-technology relation of postdigital pedagogy, and also provides comparative policy information to institutions that must make their way through this change.