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Co-Designing Multimodal Systems for Accessible Remote Dance Instruction

Published: November 12, 2025 | arXiv ID: 2511.09658v2

By: Ujjaini Das , Shreya Kappala , Meng Chen and more

BigTech Affiliations: University of California, Berkeley

Potential Business Impact:

Helps blind dancers learn moves using sound and touch.

Business Areas:
Human Computer Interaction Design, Science and Engineering

Videos make exercise instruction widely available, but they rely on visual demonstrations that blind and low vision (BLV) learners cannot see. While audio descriptions (AD) can make videos accessible, describing movements remains challenging as the AD must convey what to do (mechanics, location, orientation) and how to do it (speed, fluidity, timing). Prior work thus used multimodal instruction to support BLV learners with individual simple movements. However, it is unclear how these approaches scale to dance instruction with unique, complex movements and precise timing constraints. To inform accessible remote dance instruction systems, we conducted three co-design workshops (N=28) with BLV dancers, instructors, and experts in sound, haptics, and AD. Participants designed 8 systems revealing common themes: staged learning to dissect routines, crafting vocabularies for movements, and selectively using modalities (narration for movement structure, sound for expression, and haptics for spatial cues). We conclude with design recommendations to make learning dance accessible.

Country of Origin
🇺🇸 United States

Page Count
16 pages

Category
Computer Science:
Human-Computer Interaction