Capturing traces of the dance learning process

My thesis focuses on designing interactive tools to understand and support dance learning from videos. I show how we can capture and save traces of dancers’ embodied knowledge and use them to design interactive tools that support dance learning.

PDF -- HAL

Jury members:

Président :

Michel-Ange Amorin (Université Paris-Saclay, Professeur)

Rapporteurs :


Céline Latulipe (Associate professor, University of Manitoba)
Jacob Buur (Professeur, University of Southern Denmark)

Examinateurs :


Sylvie Gibet (Professeur, Université de Bretagne Sud)
Lian Loke (Associate professor, University of Sydney)

Directrice :

Wendy Mackay (Professeur, Université Paris-Saclay - INRIA)

Coencadrante :

Sarah Fdili Alaoui (Maître de conférence, Université Paris-Saclay)

Coencadrant :

Baptiste Caramiaux (Chargé de recherche, Sorbonne univeristé - CNRS

Cite as :

Jean-Philippe Riviere. Capturing traces of the dance learning process. Human-Computer Interaction [cs.HC]. Université Paris-Saclay, 2020. English. ⟨NNT : 2020UPASG054⟩. ⟨tel-03121577⟩

Motor Learning Dance Segmentation MoveOn Artifacts Partnership Embodied Interaction Embodied knowledge
Abstract:

This thesis focuses on designing interactive tools to understand and support dance learning from videos. Dancers’ learning practice represents a rich source of information for researchers interested in designing systems that support motor learning. Indeed, dancers embody a wide range of skills that they reuse during new dance sequences learning. However, these skills are in part the result of embodied implicit knowledge.

In this thesis, I argue that we can capture and save traces of dancers’ embodied knowledge and use them to design interactive tools that support dance learning. My approach is to study real-life dance learning tasks in individual and collaborative settings. Based on the findings from all the studies, I discuss the challenge of capturing embodied knowledge to support dancers’ learning practice. My thesis highlights that although dancers’ learning processes are diverse, similar strategies emerge to structure their learning process. I discuss the challenges of capturing embodied knowledge and bring new perspectives to design of video-based learning tools.


Some Pictures :
1 / 8
2 / 8
3 / 8
4 / 8
5 / 8
6 / 8
7 / 8
8 / 8

Thèse de doctorat de l’Université Paris-Saclay École doctorale n°580, Sciences et technologies de l’information et de la communication (STIC) Spécialité de doctorat: Interaction Homme-Machine Thèse présentée et soutenue à Orsay, le 11/12/2020, par Jean-Philippe Rivière