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Artificial intelligence in dance education: Dance for students with special educational needs

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  • Hu, Mengyu
  • Wang, Jingyi

Abstract

Participation in inclusive dance can have positive results for different groups of people with special needs, including those with mobility impairments. The purpose of study is to analyze the level of physical development and psychomotor skills of students with developmental disorders of the musculoskeletal system at different stages of inclusive dance classes. A model of a teacher using a Bayesian network has been developed to assess the level of physical fitness at different stages of training. The study involved 30 participants. There were two groups of students aged 17–19. Group 1included students engaged in inclusive dance classes for six months while Group 2 consisted of students having attended 2–3 classes before the study. The students were interviewed. In terms of the level of physical fitness, significant differences were revealed between Group 1 and Group 2 in favor of Group 1. Regular inclusive dance classes help to improve students' physical fitness and, consequently, their overall coordination of movements. Improvement in overall physical health should be explored more deeply in further research.

Suggested Citation

  • Hu, Mengyu & Wang, Jingyi, 2021. "Artificial intelligence in dance education: Dance for students with special educational needs," Technology in Society, Elsevier, vol. 67(C).
    • Handle: RePEc:eee:teinso:v:67:y:2021:i:c:s0160791x21002591
    DOI: 10.1016/j.techsoc.2021.101784
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    References listed on IDEAS

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    1. Nazareno, Luísa & Schiff, Daniel S., 2021. "The impact of automation and artificial intelligence on worker well-being," Technology in Society, Elsevier, vol. 67(C).
    2. de Neufville, Robert & Baum, Seth D., 2021. "Collective action on artificial intelligence: A primer and review," Technology in Society, Elsevier, vol. 66(C).
    3. Buhmann, Alexander & Fieseler, Christian, 2021. "Towards a deliberative framework for responsible innovation in artificial intelligence," Technology in Society, Elsevier, vol. 64(C).
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    Cited by:

    1. Jian Kim & Jooyeon Jin & Aeryung Hong, 2022. "Creative Intercorporeality in Collaborative Work of Choreographers with and without Disabilities: A Grounded Theory Approach," IJERPH, MDPI, vol. 19(9), pages 1-13, May.
    2. Subhasis Bera & Ishita Bera & Dil Rahut, 2026. "AI adoption among young Indians: an analysis using a MIMIC model," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 13(1), pages 1-23, December.
    3. Zhao, Yong, 2022. "Teaching traditional Yao dance in the digital environment: Forms of managing subcultural forms of cultural capital in the practice of local creative industries," Technology in Society, Elsevier, vol. 69(C).
    4. Wang, Zheng, 2024. "Artificial intelligence in dance education: Using immersive technologies for teaching dance skills," Technology in Society, Elsevier, vol. 77(C).
    5. Esraa Hussein & Menatalla Hussein & Maha Al-Hendawi, 2025. "Investigation into the Applications of Artificial Intelligence (AI) in Special Education: A Literature Review," Social Sciences, MDPI, vol. 14(5), pages 1-19, May.

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