MétaCan
Menu
Back to cohort
Record W3047577815 · doi:10.25071/1916-4467.40546

Applications of Music Within the Neurolinguistic Approach in a German Bilingual School

2020· article· en· W3047577815 on OpenAlexaffvenue
Lisa Anderson

Bibliographic record

VenueJournal of the Canadian Association for Curriculum Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistic Education and Pedagogy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMemorizationGermanPronunciationGrammarMusicalComputer sciencePsychologyLinguisticsMathematics educationVisual arts

Abstract

fetched live from OpenAlex

This paper presents a study exploring applications of music within the Neurolinguistic Approach (Germain, 2018) to enhance second or additional language teaching in a Kindergarten to Grade 6 German bilingual school. Each participating teacher was interviewed about how they employ music in the classroom, how they create musical resources for teaching language, and what benefits and challenges they have experienced from its use. One of the key findings is that teachers use songs as oral models to teach both the implicit grammar of the target language and accurate pronunciation. Furthermore, teachers are adapting existing musical resources and creating their own to provide rich texts for classroom activities to help establish routines, to aid in emotional regulation and to facilitate the memorization of difficult concepts. Finding age-appropriate materials that are suitable for the skill levels of their students remains the greatest challenge. As one of the first studies to study music with the Neurolinguistic Approach, the findings suggest that this music-integrated approach has the potential to facilitate second language teaching.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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 head0.065
GPT teacher head0.314
Teacher spread0.249 · 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 designNot applicable
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

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Association for Curriculum StudiesSame topicLinguistic Education and PedagogyFrench-language works237,207