The Main Methodological Approaches to the Personal-Creative Development of Elementary School Pupils in the Process of Music Education
Bibliographic record
Abstract
In the article the importance of personal and creative development of elementary school pupils in the process of teaching music is actualized.The views of scientists on this problem are investigated and generalized.The author's understanding of the creativity of elementary school pupils is presented.The issue of aesthetic orientation of pupils' creative activity in the process of learning music is emphasized.The role of pedagogical leadership in the educational process for the development of creative abilities of elementary school pupils is emphasized.The main methodological approaches to the personal-creative development of elementary school pupils in the process of teaching music are considered.Applying a personal approach contributes to the identification and disclosure of the personal potential of pupils, the establishment of subject-subject relationships.It is noted that the creativity of students is manifested in educational activities, so for the personal and creative development of younger students in the process of teaching music is important to use the activity approach.An integrated approach provides students with a holistic picture of the world, solving musical and creative tasks with the knowledge of all subjects of the aesthetic cycle and other subjects. Key words: music teaching,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".