Manajemen Pengembangan Kurikulum Berbasis Madrasah di MTs Ma’arif NU Kota Malang
Bibliographic record
Abstract
Curriculum development has a very crucial role in the education process, especially in the learning process. The achievement of learning depends on the management of curriculum development that carried out in each school. This study aims to determine the management of madrasa-based curriculum development that carried out at MTs Ma'arif NU Malang City. This research used descriptive qualitative method through interviews, observation, and documentation. The subjects studied were curriculum documents that had been developed, the subjects interviewed were the head of the madrasa, vice of curriculum, and teacher representatives. The results showed that the management of curriculum development at MTs Ma'arif NU Malang City includes planning, implementation, and evaluation. The implementation of the curriculum is carried out in macro and micro. Macro implementation by the curriculum development team, by the head of the madrasa and the vice of the curriculum to design selective programs such as aswaja deed and tahfidz programs. While the implementation of the micro curriculum is carried out by each subject teacher, which is the activity of developing the curriculum in the learning process. Starting from the lesson plans outlined in the RPP, the learning process using creative and varied learning methods, to the assessment process. Evaluation activities are carried out every mid-semester and are also carried out directly when the teacher is experiencing problems during the implementation process.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".