Development of Labyrinth Media to Stimulate Prosocial Behavior Skills of 5-6 years old Children in Purwakarta
Bibliographic record
Abstract
This study aims to produce a valid labyrinth learning media to improve the ability of prosocial behavior in children aged 5-6 years. This research is a development research with the development model used by Sugiyono. In this study, researchers only used 7 (seven) stages, namely knowing problems and potential, data collection, product design, design validation, design revision, product trials and product manufacturing. The next stage was not carried out due to cost and time constraints. The data collection technique used is a questionnaire, where the questionnaire is validated by material experts, media experts and educators. The type of data generated is quantitative and qualitative data. The average percentage result of the pretest conducted on 3 children is 10.6%, proving that the child's condition is still in the undeveloped stage. Then the posttest was carried out, namely the condition after the child was given the labyrinth media, the average percentage result of this posttest was 14.6% which proved that the child experienced a change in condition to develop as expected. So it can be concluded that the Labyrinth media to improve the ability of prosocial behavior of children aged 5-6 years has met the criteria for validity.
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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) | 0.003 | 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".