Proceedings of the 2025 International Conference on Educational Technology and Management Information Systems (ETMIS 2025)

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Emotional and Critical Evaluation in Dance Appreciation Using Artificial Intelligence

Authors
Zhiwei Jing1, Junjie Zhang2, Guangyao Yin3, Tingting Huang4, *, Xuan Zhang1, *, Libo Zhao5, *, Yayue Gao5, *
1Aesthetic Education Center, Beihang University, Beijing, China
2School of Law, Beihang University, Beijing, China
3Beijing Dance Academy, Beijing, China
4School of Reliability and Systems Engineering, Beihang University, Beijing, China
5School of Humanities and Social Sciences, Beihang University, Beijing, China
*Corresponding author. Email: htt@buaa.edu.cn
*Corresponding author. Email: 11193@buaa.edu.cn
*Corresponding author. Email: libozhao@buaa.edu.cn
*Corresponding author. Email: gao_yayue@buaa.edu.cn
Corresponding Authors
Tingting Huang, Xuan Zhang, Libo Zhao, Yayue Gao
Available Online 23 April 2026.
DOI
10.2991/978-94-6239-630-2_49How to use a DOI?
Keywords
Human-AI collaboration; Dance aesthetics education; Affective computing; Emotional quantification; Large language models
Abstract

This study addresses the limitations of traditional dance aesthetics education in providing personalized feedback and quantifying emotional responses by proposing an AI-integrated analytical framework. Utilizing the DeepSeek model, we analyzed undergraduate critiques of Dynamic Yunnan (Yang Liping) and Swan Lake (Matthew Bourne) through Wundt’s emotional dimensions (pleasure, tension, arousal). Results demonstrated strong alignment between AI-generated emotional scores and student self-assessments, with distinct emotional profiles for each performance: Dynamic Yunnan elicited higher pleasure and arousal, while Swan Lake triggered elevated tension. Notably, tension and arousal intensity enhanced critique quality for Swan Lake, suggesting emotion-cognition synergy in dance appreciation. This framework bridges AI’s quantitative precision with educators’ qualitative insights, offering a pathway to transform subjective art evaluation into data-driven pedagogy.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 International Conference on Educational Technology and Management Information Systems (ETMIS 2025)
Series
Advances in Computer Science Research
Publication Date
23 April 2026
ISBN
978-94-6239-630-2
ISSN
2352-538X
DOI
10.2991/978-94-6239-630-2_49How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Zhiwei Jing
AU  - Junjie Zhang
AU  - Guangyao Yin
AU  - Tingting Huang
AU  - Xuan Zhang
AU  - Libo Zhao
AU  - Yayue Gao
PY  - 2026
DA  - 2026/04/23
TI  - Emotional and Critical Evaluation in Dance Appreciation Using Artificial Intelligence
BT  - Proceedings of the 2025 International Conference on Educational Technology and Management Information Systems (ETMIS 2025)
PB  - Atlantis Press
SP  - 511
EP  - 519
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-630-2_49
DO  - 10.2991/978-94-6239-630-2_49
ID  - Jing2026
ER  -