Matching Items (2)
Filtering by
- All Subjects: Curriculum
- All Subjects: vernacular
- Creators: Coleman, Grisha
Description
This paper outlines the three research projects that I performed between 2009-present: Slow Movement Training (SMT) lab, Self-education Through Embodied Movement (STEM), and the Athletic Movement Program (AMP). It first evaluates the major issues that spawned each research project, and then provides a framework for understanding the shift in the student-centered physical and mental movement practices that I developed in response to the need for reform. The content will address the personal and professional paradigmatic shift that I experienced through the lens of a practitioner and educator. It will focus heavily on the transitions between each of the projects and finally the emergence of the Athletic Movement Program. The focal point becomes one of community needs, alternate resources and hybrid-online classroom support. The paper concludes with an overview and content comparison between the one-size-fits-all model used within public movement education and Athletic Movement Programs' strengths and challenges.
ContributorsCroitoru, Michael (Author) / Mitchell, John D. (Thesis advisor) / Fitzgerald, Mary (Committee member) / Coleman, Grisha (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis aims to explore the language of different bodies in the field of dance by analyzing
the habitual patterns of dancers from different backgrounds and vernaculars. Contextually,
the term habitual patterns is defined as the postures or poses that tend to re-appear,
often unintentionally, as the dancer performs improvisational dance. The focus lies in exposing
the movement vocabulary of a dancer to reveal his/her unique fingerprint.
The proposed approach for uncovering these movement patterns is to use a clustering
technique; mainly k-means. In addition to a static method of analysis, this paper uses
an online method of clustering using a streaming variant of k-means that integrates into
the flow of components that can be used in a real-time interactive dance performance. The
computational system is trained by the dancer to discover identifying patterns and therefore
it enables a feedback loop resulting in a rich exchange between dancer and machine. This
can help break a dancer’s tendency to create similar postures, explore larger kinespheric
space and invent movement beyond their current capabilities.
This paper describes a project that distinguishes itself in that it uses a custom database
that is curated for the purpose of highlighting the similarities and differences between various
movement forms. It puts particular emphasis on the process of choosing source movement
qualitatively, before the technological capture process begins.
the habitual patterns of dancers from different backgrounds and vernaculars. Contextually,
the term habitual patterns is defined as the postures or poses that tend to re-appear,
often unintentionally, as the dancer performs improvisational dance. The focus lies in exposing
the movement vocabulary of a dancer to reveal his/her unique fingerprint.
The proposed approach for uncovering these movement patterns is to use a clustering
technique; mainly k-means. In addition to a static method of analysis, this paper uses
an online method of clustering using a streaming variant of k-means that integrates into
the flow of components that can be used in a real-time interactive dance performance. The
computational system is trained by the dancer to discover identifying patterns and therefore
it enables a feedback loop resulting in a rich exchange between dancer and machine. This
can help break a dancer’s tendency to create similar postures, explore larger kinespheric
space and invent movement beyond their current capabilities.
This paper describes a project that distinguishes itself in that it uses a custom database
that is curated for the purpose of highlighting the similarities and differences between various
movement forms. It puts particular emphasis on the process of choosing source movement
qualitatively, before the technological capture process begins.
ContributorsIyengar, Varsha (Author) / Xin Wei, Sha (Thesis advisor) / Turaga, Pavan (Committee member) / Coleman, Grisha (Committee member) / Arizona State University (Publisher)
Created2016