The Role of Supporting for Learning of Subject in School by Jigsaw Method and Utilizing School Library-Collaboration of School Library and School Music Education(music appreciation)
Bibliographic record
Abstract
In this study, a music class at a junior high school introduces coordinated activity by the collaboration between a teacher and school library (the Jigsaw Method) in music appreciation. The research investigates what kind of changes the students show through such a type of lesson that they experience for the first time. From the point of teacher’s view, the study reveals the evaluation of this lesson support, and what sort of issues it contains. As a result, the lesson support of the school librarian that introduces the book materials and the Jigsaw Method, the teachers obtain a sense of accomplishment more than they expected in the area of learning attitudes and learning contents of the students. Therefore, this research concludes that it is obvious that they have effectiveness in the learning support program which introduces the active learning into the learning support by school library.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".