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Record W2104512693 · doi:10.1177/0305735614528833

The efficacy of singing in foreign-language learning

2014· article· en· W2104512693 on OpenAlexaff
Arla Good, Frank Russo, Jennifer Sullivan

Bibliographic record

VenuePsychology of Music · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsWestern UniversityToronto Metropolitan University
Fundersnot available
KeywordsSingingPsychologyRecallContext (archaeology)LinguisticsForeign languageMelodyFirst languageSpoken languageCognitive psychologyHistoryLiteratureMathematics educationArt

Abstract

fetched live from OpenAlex

This study extends the popular notion that memory for text can be supported by song to foreign-language learning. Singing can be intrinsically motivating, attention focusing, and simply enjoyable for learners of all ages. The melodic and rhythmic context of song enhances recall of native text; however, there is limited evidence that these benefits extend to foreign text. In this study, Spanish-speaking Ecuadorian children learned a novel English passage for 2 weeks. Children in a sung condition learned the passage as a song and children in the spoken condition learned the passage as an oral poem. Children were tested on their ability to recall the passage verbatim, pronounce English vowel sounds, and translate target terms from English to Spanish. As predicted, children in the sung condition outperformed children in the spoken condition in all three domains. The song advantage persevered after a 6-month delay. Findings have important implications for foreign language instruction.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.042
GPT teacher head0.334
Teacher spread0.292 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations97
Published2014
Admission routes1
Has abstractyes

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