Preschool teachers’ use of research-informed literacy-promoting practices: implications for teacher training
Bibliographic record
Abstract
This study examined preschool teachers’ use of the ten research-informed literacy promoting practices included in Michigan’s Essential Instructional Practices for Early Literacy for Prekindergarten (hereon, Essentials Pre-K). We also explored the relationship between the use of Essentials Pre-K and early language and literacy quality in preschool classrooms as measured by the Early Language and Literacy Classroom Observation or ELLCO Pre-K. Thirty prekindergarten classrooms from four counties in Michigan were observed. When teachers implemented the Essentials Pre-K, they naturally grouped the ten recommended practices into three major clusters. These naturally-occurring clusters largely overlapped with the statewide Essentials Pre-K training developed by literacy experts. We also found that when teachers implemented the Essentials Pre-K practices in line with how they were designed, their classrooms scored higher on ELLCO Pre-K. Findings support Michigan’s Essentials Pre-K as highly promising in guiding early childhood teachers in their literacy-promoting instructions, with implications for teacher training.
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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 | 0.007 | 0.019 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".