Komparasi Tujuan dan Standar Kurikulum Social Studies Sekolah Dasar Kanada dan Indonesia
Bibliographic record
Abstract
The curriculum has a strategic role in supporting teachers in carrying out the learning process and students in skills skills. Curriculum changes that have occurred in several countries such as Japan, South Korea, the United States, and Canada have shown encouraging results. It is proven that the implementation of the curriculum has brought changes, improvements and enhancements to the quality of education in the country. Based on studies conducted, the Social Science curriculum in Canada was created and developed based on subjects. The objectives of Canadian Primary School Social Studies are to provide an understanding of the basic concepts of Social Studies, develop the skills, strategies and habits of thought necessary for effective inquiry and communication, as well as to apply basic Social Science concepts, to a variety of learning tasks, and impart skills. to relate and apply the social studies obtained through social studies to the world outside the classroom. Meanwhile, the goal of elementary school social science in Indonesia is to lay the foundation of intelligence, knowledge, personality, noble morals, and skills to live independently and follow further education. The curriculum in Social Sciences Grades 1 to 6 in Canada, organizes learning in a set of basic concepts, namely systems and structures, interaction and interdependence, environment, change and sustainability, culture, and governance.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".