First steps in dance data science: Educational design

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.

Publication
Proceedings of the 6th International Conference on Movement and Computing (MOCO 2019)

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