Tahap profesionalisme guru sekolah rendah agama jabatan agama islam wilayah persekutuan terhadap amalan perancangan pengajaran
Bibliographic record
Abstract
Kajian ini dijalankan bagi mengenal pasti tahap profesionalisme guru sekolah rendah agama Jabatan Agama Islam Wilayah Persekutuan (JAWI) terhadap amalan perancangan pengajaran. Secara umumnya, reka bentuk kajian ini adalah kajian kuantitatif dan instrumen kajian yang digunakan ialah dalam bentuk set soal selidik. Di samping itu, bilangan sampel kajian yang diambil adalah seramai 274 responden yang terdiri daripada guru-guru Sekolah Rendah Agama (SRA) JAWI di Wilayah Persekutuan Kuala Lumpur. Data kuantitatif ini dianalisis secara deskriptif melalui perisian SPSS, versi 22 untuk mendapatkan kekerapan, peratus, min dan sisihan piawai. Dapatan kajian menunjukkan tahap profesionalisme guru SRA-JAWI di Wilayah Persekutuan Kuala Lumpur berdasarkan amalan perancangan pengajaran berada pada tahap tinggi (M=4.40, SP=0.32). Implikasi kajian ini dapat menjadi panduan kepada guru-guru yang lain dalam usaha menambahbaik amalan perancangan pengajaran dalam bidang masing-masing dan mampu menghasilkan pengajaran yang berkesan dan berkualiti. Sebagai kesimpulannya, kualiti amalan perancangan pengajaran guru SRA-JAWI di Wilayah Persekutuan Kuala Lumpur perlu dikekalkan agar kecemerlangan pendidikan berterusan dan mampu berdaya saing di persada antarabangsa. Kata kunci: Tahap Profesionalisme, Guru Pendidikan Islam, Sekolah Rendah Agama, Amalan Perancangan Pengajaran
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 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".