Bibliographic record
Abstract
This study analyzed the effectiveness of Step Buddy in improving the basic skills in a dance of Senior High School students. This study addresses the competency code PEH11FH-IIo-t-17, which is to organize sports events for a target health issue or concern. This study used an experimental method and underwent four steps. First, the researcher assessed the learner’s 1st quarter performance and determined the learners who need assistance and those who have potential in dancing. Second, the top ten highest performance grades for the 1st quarter were considered as peer tutors by the researcher. Then, the tutors and tutees met during their vacant time and the researcher monitored the tutoring session. After the said tutorial, the researcher compared the grades of the tutees in the 1st quarter and 2nd quarter to whether there is an increase in their level of performance. The mean score of the 1st and 2nd quarter performance task grades are both analyzed in this research. Overall, the use of Step Buddy can be used effectively to enhance students' ability to enhance skills in dancing. Therefore, there was a significant difference between the 1st and 2nd quarter performance task grades of the students.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".