Assessment of the Physical Literacy Environment in Early Childhood Classrooms
Bibliographic record
Abstract
This study aims to assess the physical literacy environment in 30 early childhood classrooms servicing 4- to 6-year-old children. A high-quality literacy environment that includes a variety of materials and resources is an important part of children’s emergent literacy, as research shows their use supports oral and written language development (Dynia et al., 2018; Yang et al., 2023). Observations were conducted using the Early Language and Literacy Classroom Observation Pre-K (ELLCO Pre-K; Smith et al., 2008) and the Literacy Environment Checklist (Smith et al., 2002), along with qualitative observational data and photographs of the classrooms. Overall, results show a low or basic level of quality of the physical literacy environment. Classrooms lack quality features such as a wide variety of books, writing materials in learning centers, accessible environmental prints, and representations of children’s diversity in reading materials. This level of quality is not considered sufficient to adequately support the language development of 4- to 6-year-old children, particularly those from disadvantaged backgrounds (Cunningham, 2010). These findings underline the importance of teachers’ professional development to better support emergent literacy through the physical environment of early childhood classrooms.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".