The Impact of Mobile Applications on Personalized Learning Paths in Dance Education

Abstract

With the rapid development of smart mobile applications, mobile devices have become an essential learning tool in dance education. Traditional dance teaching methods often fail to effectively meet the individualized learning needs of students, especially in the dynamic learning and feedback of skills. As a result, the design and implementation of personalized learning paths have become a key issue in current dance education. Although existing research has preliminarily explored dance teaching on mobile platforms, problems still exist, such as inaccurate student dance posture assessments and incomplete personalized learning path recommendation mechanisms. Therefore, utilizing mobile application technologies to achieve precise dance posture recognition and evaluation, while providing personalized learning paths for each student, is a critical issue that needs to be addressed. This paper aims to explore the role of mobile applications in optimizing personalized learning paths in dance education. The study consists of two main parts: first, a dance posture evaluation method based on intelligent posture recognition technology is proposed to accurately match personalized learning content based on students’ progress and skill levels. Second, a personalized learning path recommendation system based on collaborative filtering algorithms is designed to help students receive tailored content during their dance learning process. The study demonstrates that combining posture evaluation with content recommendation can significantly improve the personalization and learning outcomes of dance education, providing new technological support and practical applications for intelligent dance teaching.