Improving Preschool Educators' Interactive Shared Book Reading: Effects of Coaching in Professional Development
Bibliographic record
Abstract
PURPOSE: The objective of this study was to examine the effects of coaching by speech-language pathologists on educators' interactive shared book reading, children's participation in shared reading, and children's language development. METHOD: Thirty-two educators and small groups of preschoolers were randomly assigned to experimental and comparison groups. The experimental group (n = 15) received 4 in-service workshops plus 5 individualized coaching sessions. The comparison group received only the 4 workshops. Participants were video-recorded during a shared book reading activity with a small group of children at pretest and posttest. The video recordings were transcribed and coded to yield measures of conversations, educators' questions, and children's responses. The mean length of utterances of the children's responses was also calculated. RESULTS: There were no significant Time × Group interaction effects for the number and length of shared reading conversations or for the number of participants in these conversations. However, significant Time × Group interactions were observed for the use of educators' experiential reasoning questions, children's experiential reasoning responses, and the mean length of utterances of children's responses. CONCLUSION: These results suggest that coaching increases educators' use of inferential questions, enhancing an interactive shared-reading strategy that had a direct impact on the children's quality and complexity of language.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".