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Record W3137240938 · doi:10.1080/03004430.2021.1885391

Vocabulary enrichment using an E-book with and without kindergarten teacher’s support among LSES children

2021· article· en· W3137240938 on OpenAlex
Ofra Korat, Shifra Atishkin, Ora Segal-Drori

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarly Child Development and Care · 2021
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsVocabularyPsychologyClass (philosophy)Vocabulary developmentMathematics educationIntervention (counseling)Preschool educationDevelopmental psychologyLinguisticsTeaching methodComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

We examined an intervention in kindergarten using an e-book for vocabulary enrichment. In programme (a), the children read the e-book with a dictionary and the teacher’s support. In programme (b), the children read the e-book with the dictionary independently. In programme (c), the children read the e-book without a dictionary (control). The participants included 103 children (aged 5–6) from LSES families. They read the e-book in the kindergarten class six times. The children were tested pre, post 1 and post 2, on story focal words at the receptive, explanation and production level. Children who read the e-book with the dictionary and the teacher’s support learned more words than those, who read the e-book with the dictionary independently, and more than the control. Achievements were maintained after one month. Children with an initial low level progressed more than those with a high level. The findings and their implications are discussed.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.012
GPT teacher head0.256
Teacher spread0.244 · 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