A Study on Developing Learning Strategies in Violin Education
Bibliographic record
Abstract
This study was conducted for the purpose of developing a valid and reliable learning strategies scale for students receiving violin education in Departments of Music at Fine Arts High Schools. The scale was applied to 391 violin students receiving education in the 11th and 12th grades in Departments of Music at Fine Arts High Schools in the provinces of Ankara, Eskişehir, Kayseri, Konya, Kırıkkale, Sivas, Niğde, Adana, Mersin, Isparta, Hatay, Osmaniye, İzmir, Aydın, Denizli, Kütahya, Manisa, Muğla, Bursa, İstanbul, Balıkesir, Çanakkale, Edirne, Tekirdağ, Samsun, Trabzon, Ordu, Bolu, Tokat, Malatya, Erzurum and Van. The 5-point Likert scale consists of 67 items. The data obtained after applying the scale were transferred to the SPSS Package Software. Explanatory factor analysis was then carried out on the basis of the data. As a result of the explanatory factor analysis, it was determined that the scale had six factors. In addition, the Cronbach’s alpha internal consistency coefficient of the scale was found to be 0.966.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".