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Record W3022464810 · doi:10.21009/jpud.141.07

The Impact of the Whole Language Approach Towards Children Early Reading and Writing in English

2020· article· en· W3022464810 on OpenAlex

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aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
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Bibliographic record

VenueJPUD - Jurnal Pendidikan Usia Dini · 2020
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)LinguisticsPsychologyWhole languageEnglish languageComputer scienceMathematics educationPhilosophy

Abstract

fetched live from OpenAlex


 
 
 This study aims to determine the effect of the whole language approach to the ability to read and write in English in early stages of children aged 5-6 years in one of the kindergartens in the Yogyakarta Special Region. The population in this study were 43 children who were in the age range of 5-6 years in the kindergarten. Twenty-nine participants were included in the experimental class subjects as well as the control class with posttest only control group design. Observation is a way to record data in research on early reading and writing ability. The results of Multivariate Anal- ysis of Covariance (Manova) to the data shows that 1) there is a difference in ability between the application of the whole language approach and the conventional approach to the ability to read the beginning of English; 2) there is a difference in ability between applying a whole language approach and a conventional approach to writing English beginning skills; 3) there is a difference in ability between the whole language approach and the conventional approach to the ability to read and write the beginning in English
 Keywords: Whole language approach, Early reading, Early writing, Early childhood
 Reference
 
 
 
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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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.023
GPT teacher head0.310
Teacher spread0.287 · 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