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Record W2157969583 · doi:10.1177/1468798413478261

Enhancing preschool educators’ ability to facilitate conversations during shared book reading

2013· article· en· W2157969583 on OpenAlexaff
Trelani Milburn, Luigi Girolametto, Elaine Weitzman, Janice Greenberg

Bibliographic record

VenueJournal of Early Childhood Literacy · 2013
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCoachingShared readingReading (process)PsychologyProfessional developmentPedagogyMathematics educationControl (management)Early childhood educationDevelopmental psychologyLiteracyComputer scienceLinguistics

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate whether professional development enhanced educators’ use of conversational strategies during shared book reading with small groups of preschoolers. Twenty preschool educators and small groups of children from each of their classrooms were randomly assigned to the experimental or control group. The 10 educators in the experimental group received instruction in shared book reading strategies as well as individual classroom coaching sessions. Each educator was video-recorded reading two storybooks to a small group of preschoolers at pretest and posttest. The video-recordings were transcribed and coded to yield the measures of the book-related talk. The findings revealed that the educators in the experimental group used a greater number of open questions, responsive statements and different words compared to the control group. The educators and children in the experimental group also maintained longer book-related conversations and had more conversations that were five or more turns in length compared to the control group. These findings suggest that professional development that includes group instruction and individual coaching can enhance educators’ ability to facilitate book-related conversations with preschool-age children.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.013
GPT teacher head0.272
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations94
Published2013
Admission routes1
Has abstractyes

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