Pengembangan Modul Pembelajaran Matematika Materi Pecahan Berbasis Kearifan Lokal Kelas IV SDN 2 Surabaya
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengembangkan modul pembelajaran matematika materi pecahan berbasis kearifan lokal menggunakan desain penelitian Borg and Gall yang terdiri dari 10 langkah disederhanakan menjadi 7 langkah, yaitu (1) melakukan analisis kebutuhan, (2) perencanaan, (3) pengembangan produk awal, (4) pengujian terbatas, (5) revisi hasil uji produk, (6) uji produk utma, (7) revisi produk akhir. Penelitian ini dilakukan pada peserta didik kelas IV dengan jumlah 11 peserta didik. Instrumen penelitian dan pengembanngann ini menggunakan lembar validasi dan angket respon peserta didik. Hasil uji validasi ahli desain media dengan jumlah skor 93 berada pada rentang skor X>83,94 dengan kategori “sangat baik”. Hasil uji validasi ahli materi dengan jumlah skor sebesar 90 berada pada rentang skor X>83,94 dengan kategori “sangat baik”. Hasil dari angket respon peserta didik terhadap kevalidan dan kefektifan penggunaan modul yang dikembangkan mendapatkan skor rata-rata 50,53 dan berada pada rentang 39
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.086 | 0.017 |
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".