Abstract
Currently, rhythmic gymnastics teaching mainly focuses on traditional techniques and cannot break through issues such as blind spots in the coordination training between apparatus and body. In the academic field, research results are still dominated by single aspects such as new rules and event analysis. ADAMS technology can provide an innovative path to solve the above problems in rhythmic gymnastics teaching and scientific research. Based on the analysis of the advantages of ADAMS simulation technology and the theoretical basis for artificial intelligence technology to adapt to educational paradigms, this paper first uses ADAMS software to model the rhythmic gymnastics hoop through steps including model import, material definition, constraint relationship establishment, driving and force application, and simulation setting. It then conducts simulation of the vertical hoop thrown upward at two different angles (30 degrees and 45 degrees) and makes a comparative analysis of the counterclockwise and clockwise rotations of the vertical hoop thrown upward at the same angle. Furthermore, it carries out teaching experiments to explore the practical application of artificial intelligence technology in the teaching of upward throwing of the vertical hoop in rhythmic gymnastics, and draws the following conclusions: (1) The choice of projection angle has a differential impact on movement efficiency: a 30° projection angle is more suitable for basic standardized training due to its stable trajectory and moderate displacement, while a 45° projection angle is more conducive to enhancing artistic expression by virtue of its advantage in air retention. (2) Rotation direction has a significant impact on technical efficiency: clockwise rotation strengthens the spatiotemporal consistency of apparatus throwing and catching, while counterclockwise rotation optimizes the fluency of movement connection. Combined training can meet the requirements for innovative scoring. (3) ADAMS technology significantly improves teaching effectiveness through accurate trajectory prediction and mechanical analysis. Experimental data confirm that it is superior to traditional teaching methods in terms of skill mastery, interest stimulation, and satisfaction. It is suggested that efforts should be made to construct an intelligent teaching closed-loop system based on ADAMS technology and promote a dual-track model of "scientific quantification-artistic expression", which is conducive to the scientific and intelligent development of physical education and art courses in colleges and universities.