Bibliographic record
Abstract
Across Canada, the arts disciplines - dance, drama, music and visual arts - are integral to the school curriculum. However, there is neither a consensus on the knowledge and instructional skills required of practitioners to effectively implement arts lessons, nor agreement on approaches to teaching the arts in teacher education and professional development programs. In this paper, I discuss a policy Delphi undertaken for the purpose of developing a curricular image for the arts in a faculty of education. My motivation for this study derives from previous research which indicates that effectively designed and delivered arts education programs can enhance teachers' confidence and willingness to the arts in their own classrooms. Findings from this study indicate that elementary teachers need a level of comfort with the arts to teach them. They require the expertise to apply generic instructional skills in the arts, a desire to play and experiment with artistic processes, an appreciation of the importance of the arts, and an understanding of basic arts concepts. Specialist secondary arts teachers should foster creativity in their classrooms. They require expertise in two arts disciplines and a broad knowledge of the others, an understanding of outcomes-based learning and how to organize appropriate activities, and an ability to motivate and inspire young people to participate in the arts. Teacher educators need to re-focus the arts curriculum to emphasize personal expertise, comfort level, creativity, experimentation, and conceptual knowledge across the arts disciplines. Professional development programs in the arts should emphasize outcomes-based learning, generic instructional strategies, integration, and assessment strategies.
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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 | 0.041 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".