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Record W1538528645

Discussion on Primary School Music Teaching: How to Increase Students’ Enthusiasm for Learning Music

2015· article· en· W1538528645 on OpenAlexvenueno aff
Jin Wang

Bibliographic record

VenueCross-cultural communication · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsEnthusiasmMusic educationClass (philosophy)Mathematics educationPsychologyMusicologyPedagogyComputer scienceSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

This article analyzes how to inspire primary students to learn music actively. To improve the enthusiasm of learning music among primary students plays an important role in the development of music education in our country, but most primary school students are not interested in music class. The core of music education is aesthetics. A good music education can stimulate the rapid development of the pupils’ brain, and improve their ability of music appreciation. Music educators should enhance primary students’ interest in music class in order to mobilize them to learn music actively. Therefore, music educators should constantly improve their own musicianship, explore the rules of teaching, and improve teaching methods, help create a good ambiance in the class, make the students learn music relaxed and cheerfully, which multiplies the efficiency of class teaching, so that the goal of cultivation will be achieved.

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 categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0030.001
Open science0.0010.000
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 head0.105
GPT teacher head0.343
Teacher spread0.238 · 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.

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

Citations2
Published2015
Admission routes1
Has abstractyes

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