From Performers to Creators: Understanding Retired Women's Perceptions of Technology-Enhanced Dance Performance

2026-01-31

AI Summary

This study addresses the challenge faced by over 100 million older Chinese female dancers who struggle to enhance their stage performance using existing interactive dance technologies due to limited resources and age-related declines in physical and cognitive capabilities. Through co-design workshops, the research integrates an interactive dance system with large language model (LLM)-driven AIGC video generation to explore age-inclusive creative support pathways. The project introduces age-appropriate design strategies—including low-barrier keyword input, motion-aligned visual feedback, and participatory scaffolding—that significantly reduce technological entry barriers and empower non-professional older dancers to transition from passive performers to active co-creators. Findings demonstrate enhanced creative autonomy and expressive capacity among participants, while establishing a novel paradigm for designing creative technologies tailored to older adults.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Multiagent Systems: Teamwork

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Over 100 million retired women in China engage in dance, but their performances are constrained by limited resources and age-related decline. While interactive dance technologies can enhance artistic expression, existing systems are largely inaccessible to non-professional older dancers. This paper explores how interactive dance technologies can be designed with an age-sensitive approach to support retired women in enhancing their stage performance. We conducted two workshops with community-based retired women dancers, employing interactive dance and LLM-powered video generation probes in co-design activities. Findings indicate that age-sensitive adaptations, such as low-barrier keyword input, motion-aligned visual effects, and participatory scaffolds, lowered technical barriers and fostered a sense of authorship. These features enabled retired women to empower their stage, transitioning from passive recipients of stage design to empowered co-creators of performance. We outline design implications for incorporating interactive dance and artificial intelligence-generated content (AIGC) into the cultural practices of retired women, offering broader strategies for age-sensitive creative technologies.

Problem

• interactive dance technology
• age-sensitive design
• retired women dancers
• artistic expression
• technology accessibility

Innovation

• age-sensitive design
• interactive dance technology
• AIGC
• co-creation
• LLM-powered video generation