964
Views
0
CrossRef citations to date
0
Altmetric
Winner of the 2017 Doug Risner Prize for Emerging Dance Researchers

Somatics, Transfer Theory, and Learning

Six Case Studies

, MFA
Pages 164-175 | Published online: 05 Nov 2018
 

ABSTRACT

This mixed methods study investigates the juncture of dance science, somatics, and contemporary modern dance training, and how they intertwine with learning processes and skill execution through transfer theory. The effects of a novel somatics training program are analyzed through six case studies using data reduction and interpretation of interviews, questionnaires and journals, and quantitative scoring data. During entry and exit processes, collegiate participants learned two phrases by video containing the same spinal coordination patterns with contrasting choreographic intents: Phrase A fluid and sustained, and Phrase B, dynamically enhanced. Participants’ video-recorded performances of each phrase were scored by a judging panel. The results show dancers’ participation in the eight-week somatic training workshop with a focus on the spine yielded growth in learning and skill execution in all participants. This growth was exhibited in two outcomes, overall skill improvement and partial skill improvement, suggesting transfer of learning varies across individuals.

Notes

1. Names reported are pseudonyms chosen by participants.

2. The study was approved by the Institutional Review Board to involve Human Subjects.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 101.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.