The Development of Chorus Motivation Scale (CMS) for Prospective Music Teacher
Bibliographic record
Abstract
The purpose of this study was to develop a Chorus Motivation Scale (CMS) that is tested in terms of reliability and construct validity by determining the student perceptions of effective motivation strategies in Chorus training in Turkish Music Teacher Training Model. In order to develop a Chorus Motivation Scale, Questionnaire-Effective Motivation Strategies in Chorus Training was applied to second-year, third-year, and fourth-year students who study at Music Teacher Training departments of nine different state universities from seven geographical regions in Turkey (N=794). Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were conducted in accordance with new/initial scale development procedures. Analysis of the data reveals a good structure model comprising reliable factors. Confirmatory factor analyses indicated that a model including factors representing the dimensions Leadership, director/student attention, achievement and anxiety was the best fit. The four-factor model yielded RMSEA and SRMR values (≤.05) demonstrating an excellent fit and CFI value with an adequate fit to the data. Cronbach’s alpha and initial-final reliability results indicated good to excellent consistency across all CMS subscales, with coefficients ranging from .64 to .90.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".