Feasibility and initial psychometric properties of the observe, reflect, improve children’s learning tool (ORICL) for early childhood services: A tool for building capacity in infant and toddler educators
Bibliographic record
Abstract
Child observation is a critical component of quality pedagogy in early childhood education and care (ECEC). The ORICL (Observe, Reflect, Improve Children’s Learning) tool was co-designed by ECEC researchers, policymakers, leaders, and practitioners to support this work. Educators rate the experiences of individual children, and responses of educators and peers on 118 items across five domains. In this study of the utility of ORICL, the tool was used by 21 educators across 12 ECEC services for a total of 66 children. Descriptive statistical analyses were used to determine how educators used the full range of the ORICL rating scale, and the psychometric properties of the tool were explored. Findings suggest that the ORICL items can be readily observed and rated by educators for children aged under 3 years, the rating scale is appropriate, and there is early evidence to support the domain structure of the tool.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".