Observer et évaluer la qualité des interactions enseignant.e/enfants à l'école maternelle en Belgique pour soutenir le développement langagier des enfants de 4 ans : une étude exploratoire
Bibliographic record
Abstract
Early childhood education is a privileged context for children to develop their language and communication abilities (Dickinson, 2011). More specifically, it is demonstrated that the quality of the interactions between teachers and children plays a protective role on language and communication development for more vulnerable children (Burchinal et al. 2010; Simard et al. 2013). The current study explores the quality of interactions in kindergarten in the French-speaking part of Belgium (second year for children of 4-5 years old). Observations took place in 17 classes, using the CLASS® Pre-K (Classroom Assessment Scoring System®, Pianta et al. 2008). Similar to other international investigations, our results show heterogeneity in the scores of the different classes. But overall, emotional support and classroom organization reach medium to high quality level, while instructional support shows a low average score. Some dimensions of the instructional support vary as a function of the teacher/children ratio and the type of activity. This exploratory study enables a reflection about language development support in early childhood education and raises questions about creative ways to optimize it.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".