Variation in quality of interactions offered to infants, toddlers and preschoolers in homebased childcares
Bibliographic record
Abstract
Research aims This presentation explores the variation in quality of interactions offered to infants, toddlers and preschoolers in home-based childcare. Relationship to previous research In early childhood education, high quality interactions promote children's development (e.g. Britto et al., 2017). However, little is known about the nature of quality of interactions in home-based childcare (Ang et al., 2016), especially when it comes to infants and toddlers as opposed to preschoolers (Ackerman, 2021; Banghart et al., 2020). What are the variation in quality of interactions in the context of a multiage group? \n \nTheoretical and conceptual framework In early childhood education, interactions between educators and children are among the most influential processes for children's development and learning (Cadima et al., 2020; Araujo et al., 2019; Sabol et al., 2013). The Teaching Through Interactions Framework (see Hamre et al., 2013 for a summary), presents the theoretical and empirical rational underlying high�quality interactions. In general, high-quality interactions must be warm, meaningful, sensitive, and \nstimulating (Hamre and Pianta, 2001; Sokolovic et al., 2021). Some studies indicate that the quality of interactions offered to 0-3-year-olds appears lower there the one offered to groups of children aged 3-5 years (Halle et al., 2012; Lahiti, 2015; Fenech, 2010; Vermeer, 2016), Methodology and methods Drawn from a larger sample of 37 home-based childcares, this study concerns the 8 home-based childcares (Montreal, Canada) attended by infants, toddlers and preschoolers. Interactions in each childcare were \nvideotaped for 3 hours during a single visit in the fall 2019 and were scored using the CLASS tool, versions Infant (Hamre & al., 2014), Toddler (La Paro et al., 2012) and Pre-K (Pianta et al., 2008). Observers completed 6 observation cycles (observing 15 to 20 minutes, scoring 10 minutes), alternating between versions of the tool as recommended by Teachstone (Teachstone, 2020). Ethical considerations: At recruitment, providers and families were informed about the project and standard ethical considerations and signed a consent form agreeing to participate. The research assistant had the directive to adapt the camera angle if a child did not want to be filmed. Findings, discussions While datas are still being analyzed, the results will present and compare the CLASS scores obtained with the Infant, Toddler and Pre-K versions of the tool for a better understanding of the variation in the quality of interactions in home-based childcare. Discussion stresses the pros and cons of the observation procedure for observing quality of interactions in multiage groups. We will address how to support children' development, especially infants, through initial and ongoing training of providers. Implications : \nThese findings have implications for home-based childcare providers' training, as well as policy, since many monitoring systems to ensure quality and accountability are starting to include home-based childcare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".