The Development of Learning Experience Provision Models That Synergize the Knowledge of Suan Dusit University to Enhance Proper Development of Young Children
Bibliographic record
Abstract
This research article aims to 1) determine the knowledge and experience of early childhood education of Suan Dusit University, and 2) develop and study the effectiveness of learning experience provision models that synergize the knowledge of Suan Dusit University to enhance the proper development of young children according to the 75/75 criteria. Data is obtained from personnel of 87 various agencies of Suan Dusit University, e.g., deans, directors, managers, chairpersons of programs, heads of departments, and 129 students in kindergarten 1, 2, and 3 of La-orutis Demonstration School, Suan Dusit University. The research results consisted of 15 learning experience provision models for young children, such as gravity-powered toys, battery-powered toys, the differences between a toy using force and a toy using a battery, toy caring, and how to play with toys, etc. Every learning experience provision models has a performance rating according to the 75/75 criteria.
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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 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".