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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".