Pendidikan dan Pengajaran Mata Pelajaran Sejarah di Sekolah di Malaysia (The Learning and Teaching of History In Malaysian Schools)
Bibliographic record
Abstract
The decision of the Malaysian government to make it compulsory for students to pass History at the Sijil Pelajaran Malaysia level in 2012 has attracted a positive response from Malaysian people. General public opinion on making history compulsory seems favourable on all sides of the social and political spectrum, but there remain many questions to be answered regarding the content of the history syllabus. Certain quarters have pushed for a re-evaluation of the syllabus that includes, amongst other things, the history of each Malaysian race and its leaders. This paper provides a comparison of the successes and failures of history education in developed countries including Britain, Australia and Canada, to consider whether Malaysia can learn from their experiences. It also provides an evaluation of Malaysia’s history syllabus at Form Five level, particularly in terms of what should properly constitute Malaysian history, as well as exploring the relevance of history teaching to the country’s educational objectives. Finally, it explores problems of teaching history at school level.
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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 | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".