“It’s important to have windows so you can get sunlight”: Understanding children’s perceptions of quality in early childhood education and care settings
Bibliographic record
Abstract
Across the globe young children are increasingly spending time in early childhood education and care (ECEC) settings. Exposure to ECEC settings is associated with positive developmental outcomes when they are of high quality. Quality rating and improvement systems (QRIS) measure and improve the quality of children’s experiences in ECEC settings. However, they rarely include children’s perspectives directly. This is at least in part due to the challenges associated with interviewing young children, and a lack of guidance on how to utilise their feedback. This study employed photovoice methodology to understand children’s preferences and perspectives related to their experiences in their ECEC setting. We then qualitatively mapped children’s responses onto a classroom level, measure of quality as a way of understanding overlap in children’s perspectives on quality in ECEC and those held by professionals in the field. Twenty-one children were interviewed from five ECEC programmes in Halifax, Canada. Children largely reported that their favourite parts of care included (1) materials/activities; (2) descriptions of the uses of physical spaces in their ECEC settings; and (3) other characteristics. Qualitative differences were found in children’s preferences based on their care setting. Some children preferred activities in designated areas, whereas other children preferred materials. Interestingly, few children stated preferences for socialising with peers or educators. The potential of this method for eliciting children’s input on their experiences and implications for policy and practice are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".