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Record W2099749887 · doi:10.15663/wje.v13i1.286

Developing non-verbal ways of knowing in dance: Collaborative school/university action research

2016· article· en· W2099749887 on OpenAlexaff
Clare Henderson, Deborah Fraser, Sue Cheesman, Shirley Tyson

Bibliographic record

VenueWaikato journal of education · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsHamilton Utilities Corporation
Fundersnot available
KeywordsDanceDramaThe artsAction (physics)Theory of multiple intelligencesPsychologyNonverbal communicationDance educationAction researchPedagogyMode (computer interface)SociologyVisual artsCommunicationComputer scienceArt

Abstract

fetched live from OpenAlex

Gardner (1983, 1993) has long argued that education privileges certain intelligences, primarily the linguistic and the logical-mathematical. As the arts tend to emphasise ways of knowing outside these intelligences, their marginalised status is exacerbated. A recent two-year project in eight primary schools on dance, drama, music and visual art found that the non-verbal aspects of each art form warranted serious attention to investigate what it means to learn in the arts. In this paper we describe and discuss the results of an aspect of action research in dance from this larger research project. We demonstrate how movement can be used as the primary expressive mode of communication, as opposed to privileging the spoken word. Through the use of powerpoint and video, we provide an intriguing and innovative model for providing non-verbal feedback and feed forward in the dance classroom.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.158
GPT teacher head0.364
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2016
Admission routes1
Has abstractyes

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