Author(s)

Song Yufang ¹, Sun Lin ¹

Affiliation(s)

¹ Department of General Education, Liaoning University of International Business and Economics, Dalian, Liaoning, 116052, China

Corresponding Author

Song Yufang

ABSTRACT

In the training of dance and gymnastics in universities, the application of artificial intelligence (AI) has injected innovative impetus into the development of curriculum activities. Leveraging the intelligent advantages of AI, it is possible to reconstruct the dance and gymnastics training system, accurately capture the characteristics of students' dance movements, and generate visual data to provide teachers with differentiated training guidance schemes. In dance and gymnastics training, AI can assist throughout the process and provide real-time data feedback, offering inspiration for teachers and students in movement creation and choreography. In addition, teachers should make good use of AI tools to construct a scientific evaluation system, formulate more reasonable and transparent rules for dance and gymnastics competitions, and conduct comprehensive evaluations from multiple aspects such as technical completion, artistic expression, and synchronicity through an intelligent scoring system, effectively improving the objectivity and fairness of competitions. Focusing on the characteristics of dance and gymnastics in universities, teachers should fully leverage the educational advantages of AI to promote the formation of a new training model featuring "data-driven, personalized customization, real-time interaction, and intelligent evaluation", further enhancing the quality and efficiency of dance and gymnastics training and achieving a deep integration of physical education and aesthetic education.

KEYWORDS

College Sports; Artificial Intelligence; Aerobic Dance; Sports Training; Intelligent Assistance

CITE THIS PAPER

Song Yufang, Sun Lin, Research on the Application of Artificial Intelligence in Dance and Gymnastics Training in Colleges and Universities. Adult and Higher Education (2025) Vol. 7: 68-72. DOI: http://dx.doi.org/10.23977/aduhe.2025.070411.

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