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Record W2803726429 · doi:10.1080/10888438.2018.1466890

Instruction Matters to the Development of Phoneme Awareness and Its Relationship to Akshara Knowledge and Word Reading: Evidence from Sinhala

2018· article· en· W2803726429 on OpenAlexaff
Marasinghe A. D. K. Wijaythilake, Rauno Parrila, Tomohiro Inoue, Sonali Nag

Bibliographic record

VenueScientific Studies of Reading · 2018
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsReading (process)Phonological awarenessPhonemic awarenessAssociation (psychology)Word (group theory)Computer scienceWord recognitionLinguisticsPsychology

Abstract

fetched live from OpenAlex

We examined whether global instruction of complex akshara and explicit phoneme-level instruction of akshara impact the development of phoneme awareness and its association with akshara knowledge and word reading accuracy. The participants were 100 Sinhala-speaking children from Grades 4 and 5 in Sri Lanka. Phoneme awareness showed stronger growth and a significant relationship with word reading accuracy and akshara knowledge only after children received explicit phoneme-level instruction in akshara construction. Both word reading accuracy and akshara knowledge predicted phoneme awareness, but the opposite was not true. The results suggest that phoneme awareness in Sinhala is sensitive to the method of reading instruction, and contrary to the studies in alphabetic languages, it does not have a bidirectional relationship with reading.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.126
GPT teacher head0.390
Teacher spread0.264 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations14
Published2018
Admission routes1
Has abstractyes

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