To teach creativity (or not) in early childhood arts curriculum: a case study in Chinese Beijing kindergartens
Bibliographic record
Abstract
This paper draws from a cross-cultural study of young children’s arts curricula. The initial phase of the original study consisted of a comparison of the intended arts curriculum for 5–6 year old children in China and Australia. This was followed by a survey in Beijing exploring 88 contemporary early childhood educators’ beliefs about children’s arts education. A case study of the enacted curriculum took place across three kindergartens in Beijing. The data was coded and analysed using grounded theory methodology. The research presented in this paper reported a diverse understanding of children’s creativity among the participant EC educators; it revealed that a pedagogical dilemma of demonstration remains as a challenge to early childhood arts educators. This study provided qualitative descriptions and examples of Chinese Beijing children’s arts education in this era of globalisation. Utilising Foucault’s (1991. “Governmentality.” In The Foucault Effect: Studies in Governmentality, edited by G. Burchell, C. Gordon, and P. Miller, translated by R. Braidotti, 87–104. London: Harvester Wheatsheaf) theory of governmentality as a critical lens to view the issues in this field, the study broadened perspectives regarding the education philosophy and practices of early childhood arts curriculum, in particular, for the cultivation of young children’s creativity.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".