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Record W6982682678

Is Parental Support Necessary for Children’s Piano Learning and What Implications Can Piano Teachers Take Away from this Finding?

2020· article· en· W6982682678 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Commons - DU (University of Denver) · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsPianoPiano pedagogyMusicalMusical instrumentWork (physics)Music education
DOInot available

Abstract

fetched live from OpenAlex

This article examines how Chinese and North American Caucasian children differ in terms of their work ethic, motivation, and parental influences in their piano learning.The authors took an experimental study comparing 50 Chinese and 100 North American Caucasian children by using the Survey of Musical Interests (SMI) developed by the Piano Pedagogy Research Laboratory at the University of Ottawa.The self-report questionnaire includes two components -one completed by the child and the other completed by one of the child's parents.The results show that Chinese children are more interested in practicing compared to Caucasians.Moreover, they practice nearly twice as much and are more motivated to play the piano.The authors suggest that the findings may lead to the success of Chinese musicians.It is a valuable source for my paper in that it addresses the importance of parental involvement in children's piano learning and what outcomes it brings to the children's success in piano in the future.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.216
Teacher spread0.177 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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