Curriculum Development of Supplementary Substance Curriculum in Working, Occupation, and Technology Learning Substance based on Sufficiency Economy Philosophy for Promoting Primary School Students' Life Skill
Bibliographic record
Abstract
The objectives of this research were: a) to study the situation, problem, and need for establishing the Supplementary Substance Curriculum in Working, Occupation, and Technology Learning Substance based on Sufficiency Economy Philosophy for enhancing one’s life skill, b) to develop the curriculum, c) to study the findings of curriculum usage, and d) to evaluate the curriculum in Instructional Management Technique for developing one’s Life Skill by using the Integrated Instruction, the Cooperative Learning, the Work Project or Learning by Doing, R-C-A Questioning Technique, Instruction being relevant to the objective which was aimed for the students to be able to solve the problem by themselves, develop their personality in awareness, view their own worth as well as the others’ values, have analytical thinking, make decision, and solve the problem creatively, adjust one’s emotion and tension, develop good relationship with the others for adjustment and self-defense in different situations, manage one’s life efficiently, make efficient decision by considering the impact on oneself, society, and environment, be able to apply for usefulness as well as live in society sufficiently, and be happy sustainable throughout the time based on Sufficiency Economy Philosophy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".