Principals Projections on the Malaysian Secondary School Future Curriculum
Bibliographic record
Abstract
Study on future is involving a time-span to observe future alternatives as well as to identify the greatest events that are mostly like to occur in future while to assist the policy-makers and curriculum-designers to make decision. Longstreet and Shane (1993) however, emphasized that future planning does not mean to change what currently we already possessed instead of focusing on future-probabilities and the obtained-impacts in better future developments. The first basis, according to Saedah Siraj (2008a), is: future is a changing phenomenon compared to present day. The second, human creates something today and in future with what is planned, future-planning is arranged based on values and belief and the future begins from the present moment. Meanwhile, curriculum, or as clarify by Saedah Siraj (2001), is planning or designing education program. In this regards, the principals' projections on the types of future curriculums and curriculum contents at secondary schools in Malaysia would be the central discussion of this article. This study including earlier studies of Saedah Siraj and Mohd Paris Saleh (2003) and Saedah Siraj and Faridah Abdullah (2005) involved future planning/designing education program or as affirms by Saedah Siraj (2008a) is Future Curriculum. In general, the study goal is an attempt to attain consensus of the principals' projections on the types of future curriculums and curriculum contents at secondary schools in Malaysia where the study findings will also be discussed.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".