Creating tangible cultural learning opportunities for indigenous dance with motion detecting technologies

Abstract

Witnessing and imitating a dance instructor facilitates improved learning opportunities compared with textual, auditory or video reproductions. Learning a complex dance from a verbal description is difficult, as spoken words are slow and cannot encapsulate all the details of a precise maneuver. Unfortunately, in a museum environment, visitors are not afforded the opportunity to become fully immersed in ancient and endangered forms of dance with a live instructor because having instructions inside the museum is not logistically feasible. Instead prerecorded video or paper-based images and notes are presented for perusal. This neither assists in the communication of the importance of this type of cultural heritage nor preserves the performances by passing on skills to future generations. The lack of knowledge transfer in this domain means each year many indigenous dances and their particular movements are lost in time as they become irrelevant and no longer practiced. This is a disgrace as cultural dance represents an expression, social interaction and sometime spiritual representation of a feeling or even an historical narrative in some cultures. It is an important part in understanding a culture, as much as the tangible that remains so highly soughtout by archeologists, yet dance, like other Intangible Cultural Heritage (ICH), without human practice, cannot be preserved in the same manner. To address this issue, we propose herein a system using motion-sensing and gaming technology that can assist in the preservation and knowledge transfer of indigenous dances. GLIDE is an application based on motion detecting technology that targets children in a heritage-related environment in order to create awareness about indigenous dance movements. It will offer kinesthetic clarity and playfulness in a domain very much dominated by flat, non-interactive video content.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 4 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.