Using Augmented Reality to Enhance Immersive Learning Experiences in Dance Education

With the widespread adoption of information technology, the internet, and mobile devices, there has been a significant transformation in learning methods and teaching approaches. In the field of sports dance education, leveraging modern technology to innovate teaching methods and tools can provide richer and more diverse learning experiences while fostering students' comprehensive abilities. This study follows the mechanism by which augmented reality technology enhances dance learning outcomes, utilizing the OpenCV image algorithm library to obtain depth images of dance movements. A random decision forest is employed to classify human body parts, thereby generating a human motion skeleton. Using the obtained data, a dance teaching platform based on augmented reality technology is established. The cosine similarity function is employed to estimate the dance posture of the left arm, for example. By comparing the posture correlation parameters between standard dance movements and the tested dance movements, the mean differences between the two sets of parameters are -0.00154, 0.01537, and 0.00372, indicating that augmented reality technology effectively estimates dance movement postures. A survey was conducted to assess students' satisfaction with the dance education model using augmented reality technology. The mean satisfaction scores for the course, teaching, platform, expectations, perception, and overall satisfaction were 4.3283, 4.4639, 4.0534, 4.4854, 4.4822, and 4.414, respectively, all above 4 points. The course was generally well-received by students, and they expressed a strong willingness to continue learning under this teaching model.