EVALUATING THE IMPACT OF AI ON DANCE PEDAGOGY

Authors

  • Mr. Manas Kumar Swain Assistant Professor, Department of Computer Science and Information Technology, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India
  • S. Simonthomas Department of Computer Science and Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation (DU), Chennai, Tamil Nadu, India
  • Mona Sharma Assistant Professor, School of Business Management, Noida International University, India
  • Preetjot Singh Centre of Research Impact and Outcome, Chitkara University, Rajpura 140417, Punjab, India
  • Nishant Kulkarni Department of Mechanical Engineering, Vishwakarma Institute of Technology, Pune 411037, Maharashtra, India
  • Dr. Rajesh Dev Assistant Professor, Department of Sociology, Parul University, Vadodara, Gujarat, India

DOI:

https://doi.org/10.29121/shodhkosh.v6.i5s.2025.6912

Keywords:

Artificial Intelligence, Dance Pedagogy, Pose Estimation, Embodied Learning, Human–AI Interaction, Personalized Feedback

Abstract [English]

The Artificial Intelligence (AI) applied to dance pedagogy is a revolutionary innovation in the process of movement competencies instruction, rehearsal, and assessment. This paper assesses how the AI-based instructional systems affect dance education by comparing them to the existing learning theory, principles in motor learning, and the kinesthetic intelligence. The proposed framework, based on constructivism, embodied cognition, and experiential learning, will make AI an intelligent educational companion as opposed to a substitute of human instructors. To examine the movement accuracy, time coordination, and quality of expression, AI technologies that consist of computer vision-based pose estimation, machine learning-based skill evaluation, and sensor-based motion capture are used. A mixed-methodology is used which implies dance students and teachers of different styles and levels of expertise. The data is gathered by video recordings, wearable devices, questionnaires, and semi-structured interviews, which allows quantifying and qualifying it. The AI models are trained to give personalized feedback, identify the movement errors, and give adaptive learning paths, both in real-time and offline learning. Comparative analysis demonstrates that AI-assisted learning results in definitive conclusions of movement accuracy, time, and expressiveness in comparison to conventional pedagogy. Moreover, learners are found to be more engaged, they are more self-aware, and autonomous in practice sessions. The results show that AI systems that are pedagogically aligned can be used to facilitate reflective learning, promote individualized instruction, and supplement teacher-led dance learning.

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Published

2025-12-28

How to Cite

Swain, M. K., S. Simonthomas, Sharma, M., Singh, P., Kulkarni, N., & Dev, R. (2025). EVALUATING THE IMPACT OF AI ON DANCE PEDAGOGY. ShodhKosh: Journal of Visual and Performing Arts, 6(5s), 109–119. https://doi.org/10.29121/shodhkosh.v6.i5s.2025.6912