Development of Learning Evaluation Technology Using Artificial Intelligence for Remote Dance Sports Education

In this paper, we proposed the development of learning evaluation technology for a remote dance sports education system using artificial intelligence technology. When a student uploads a dance video taken with a camera such as a smartphone to the system, the system automatically analyzes and evaluates the dance movements using artificial intelligence. To verify the reliability of the evaluation scores, we compared and analyzed the scores directly evaluated by the teacher and those evaluated by artificial intelligence. In addition, the algorithm was improved to proceed within the expected computational range when measuring similarity by operation, and the number of connectable nodes was adjusted to reduce clumping when matching data patterns, proving that the matching results were relatively uniform.