Developing non-verbal ways of knowing in dance: Collaborative school/university action research
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".