Profile of teacher-child interaction quality in groups of three-year-old children in Quebec and France
Bibliographic record
Abstract
Early childhood is widely regarded as a critical period for children’s development and academic success (April et al. 2018; Bouchard et al. 2017). In fact, the child’s brain development is highly affected by new experiences (Simard et al. 2013; Yoshikawa et al. 2013), making high-quality educational environments paramount in fostering children’s success in life. Even though educational quality encompasses several variables, a meta-analysis by Sabol et al. (2013) found that adult-child interaction was the best predictor of children’s later outcomes. However, research also shows that educational childcare services (ECS) around the world rarely offer high interaction quality environments (Slot, 2018; Tayler et al., 2016). Hence, several nations have set up quality assessment practices (OCDE, 2015). In the French speaking community, Quebec and France have developed such practices, but show different cultural, political and social contexts that can lead to discrepancies in how interaction quality is actually applied in their ECS. To explore this possibility, a study by Author et al. (2019) was conducted and found that interaction quality in Quebec’s ECS was significantly higher than in France’s ECS. However, their analysis was based on a variable-centered approach using means, which may create an inadequate representation of reality (Haccoun and Cousineau 2010). Using a secondary analysis of data (Author et al. 2019), this study thus aimed at identifying latent profiles of adult-child interaction quality in groups of three-year-old children in Quebec early childhood centers and French kindergarten classrooms, as measured by the CLASS Pre-K. This study also aimed to explore existing associations between identified interaction quality profiles and structural characteristics (staff qualifications, ages, group size). Latent profile analyses showed three interaction quality profiles in Quebec, with most of the participants (52,5 %) in the highest-quality profile, and four interaction quality profiles in France, with participants almost evenly distributed between profiles. These results suggest more homogenous teacher training in Quebec than in France. The scores of the three CLASS Pre-K domains associated with identified profiles show a higher average interaction quality in Quebec compared with France. As for characteristics of structural quality, our analyses suggest that only the group size variable is significantly associated with scores of interaction quality, and exclusively so with the “medium-quality” (MQ-FR) and “medium-low quality with emphasis on classroom organization” (MLQ-CO) profiles in France. Thus, group size of French kindergarten classrooms associated with the MQ-FR profile is significantly lower than the group size of French classrooms associated with the MLQ-CO profile. This suggests that, in French kindergartens context, group size reduction could allow groups associated with the MLQ-CO profile to find themselves in the MQ-FR profile. The highest French interaction quality profile could then account for more than 50% of the sample, which would be a significant improvement in the average quality of kindergartens. Other studies are nonetheless required in order to confirm this hypothesis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".