First steps in dance data science: Educational design

Yoav Bergner, Shiri Mund, Ofer Chen, Willie Payne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We report results of a design-research effort to develop a culturallyrelevant educational experience that can engage high school dancers in statistics and data science. In partnership with a local high school and members of its step team, we explore quantitative analysis of both visual and acoustic data captured from student dance. We describe prototype visualizations and interactive applications for evaluating pose precision, tempo, and timbre. With educational goals in mind, we have constrained our design to using only interpretable features and simple, accessible algorithms.

Original languageEnglish (US)
Title of host publicationMOCO 2019 - 6th International Conference on Movement and Computing
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450376549
DOIs
StatePublished - Oct 10 2019
Event6th International Conference for Movement and Computing, MOCO 2019 - Tempe, United States
Duration: Oct 10 2019Oct 12 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference6th International Conference for Movement and Computing, MOCO 2019
CountryUnited States
CityTempe
Period10/10/1910/12/19

Keywords

  • Dance analytics
  • Data science
  • Education
  • Motion capture

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Bergner, Y., Mund, S., Chen, O., & Payne, W. (2019). First steps in dance data science: Educational design. In MOCO 2019 - 6th International Conference on Movement and Computing [a14] (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3347122.3347137