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Record W2124605940 · doi:10.20360/g2k88j

Using Singing and Movement to Teach Pre-reading Skills and Word Reading to Kindergarten Children: An Exploratory Study

2014· article· en· W2124605940 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueLanguage and Literacy · 2014
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsSingingReading (process)PsychologyLiteracyIdentity (music)Movement (music)LinguisticsPhonological awarenessSyllableChoirWord (group theory)ArtPedagogyAcoustics

Abstract

fetched live from OpenAlex

Kindergarten classrooms were randomly assigned to a songs group (n = 44) that used choral singing and movement to teach phonological skills, letter-sounds, and word reading, or to a control group (n = 49) where children received their regular language and literacy programs for equal amounts of time. The songs group teaching involved choral singing and movements created for the project to teach phonological skills, letter-sounds, and word reading. Children preferred songs that were quick to learn, had strong or soothing rhythms, and incorporated movements. Children in the songs group had increased letter-sounds, medial phoneme identity and word reading compared to children in the control group. Children in both groups made equal gains in rhyming and identifying phonemes in initial and final positions. Songs group children also read new words not presented in the songs program. Initial and medial phoneme identity and letter-sound knowledge made independent contributions to word 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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
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
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.316
Teacher spread0.305 · 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