Effects of coaching on educators’ vocabulary-teaching strategies during shared reading
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to investigate whether an emergent literacy professional development program enhanced educators' use of vocabulary-teaching strategies during shared reading with small groups of pre-schoolers. METHOD: Thirty-two pre-school educators and small groups of pre-schoolers from their classrooms were randomly assigned to experimental or comparison groups. The 15 educators in the experimental group received four in-service workshops as well as five individualized classroom coaching sessions. The comparison group received only the workshops. Each educator was video-recorded reading a storybook to a small group of pre-schoolers at pre-test and post-test. The videos were transcribed and coded to yield measures of the vocabulary-teaching strategies and children's vocabulary-related talk. RESULT: The findings revealed that the children in the experimental group engaged in significantly more vocabulary-related talk relative to the comparison group. A non-significant trend in the data indicated that educators in the experimental group used more vocabulary-teaching strategies at post-test. The educators' familiarity with children's authors and book titles at pre-test was a significant predictor of their outcomes. CONCLUSION: These findings suggest that an emergent literacy professional development program that includes coaching can enhance children's participation in vocabulary-related conversations with their educators.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".