Effects of AI-assisted dance skills teaching, evaluation and visual feedback on dance students' learning performance, motivation and self-efficacy

• Published in: International journal of human-computer studies Vol. 195; p. 103410
• Main Authors: Xu, Liu-Jie, Wu, Jing, Zhu, Jing-Dong, Chen, Ling
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2025
• Subjects: Applications in subject areas; Improving classroom teaching; Pedagogical issues; Teaching/learning strategies; Teaching/learning strategies; Applications in subject areas; Pedagogical issues; Improving classroom teaching
• ISSN: 1071-5819
• DOI: 10.1016/j.ijhcs.2024.103410

•Using AI to improve dancing students' skills, motivation and self-efficacy•Benefits of the electronic dance skills teaching, evaluation and visual feedback (DSTEVF) system•AI technology enables dance students to obtain timely feedback on their performance, and received personalized guidance from dancing instructors•The DSTEVF system can improve teaching efficiency in other disciplines as well Despite the importance of artificial intelligence in education, its effectiveness in this field requires more empirical research for corroborating evidence. In this study, a dance skills teaching, evaluation, and visual feedback (DSTEVF) system was developed based on AI technology and applied in a dance classroom. Forty participants from a vocational school studying dance were randomly divided into two groups: DSTEVF-based learning (experimental group, n = 19) and traditional teaching (control group, n = 21). The DSTEVF-based learning approach significantly improved students’ dance skills and self-efficacy. However, there was no significant effect on students’ motivation. Students with higher levels of motivation and self-efficacy benefitted more from DSTEVF-based learning than those with lower levels. Evidently, it is possible to establish a smart classroom by applying DSTEVF to the teaching activities of dance education, physical education, and other disciplines.