Using AI-based feedback in dance education - a literature review

This paper presents a literature review with an in-depth examination of 17 selected works focusing on the utilization of pose estimation and deep learning models within the domain of dance and movement learning. To address the overarching question regarding the potential implications and utilization of these technologies in teaching movement in dance, the selected literature is systematically analyzed across four key categories: study design/research activity, applied technology and functions, system output in regard to visualization and feedback and study results. Through this structured analysis, recurring themes and patterns within the literature are identified inductively. Subsequently, the findings are synthesized and interpreted, facilitating discussion and connections with existing research. This systematic examination offers insights into the multifaceted role of AI-based technologies in dance education, paving the way for informed pedagogical practices and future research endeavors in this domain.