Pengembangan Alat Model Pembelajaran Inkuiri pada Mata Kuliah Kalkulus Lanjut
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengembangkan perangkat pembelajaran yang relevan dengan karakteristik peserta didik di Program Studi Pendidikan Matematika. Pengembangan perangkat dalam penelitian ini menggunakan model pembelajaran Inquiry pada mata kuliah Kalkulus Lanjut. Melihat situasi dunia bahkan Indonesia saat ini yang sedang dilanda pandemi COVID-19, maka semua kegiatan pembelajaran dilakukan secara offline dan online (dalam jaringan). Alat pembelajaran ini dirancang untuk digunakan dalam situasi pembelajaran online dan offline. Jenis penelitian yang digunakan adalah penelitian pengembangan yaitu pengembangan produk berupa perangkat pembelajaran. Ada 3 perangkat pembelajaran yang dikembangkan yaitu Bahan Ajar (BA), Lembar Kerja Siswa (LKM) dan Rencana Pembelajaran Semester (RPS) yang akan digunakan dalam proses belajar mengajar. Perangkat pembelajaran yang dihasilkan diharapkan dapat membantu siswa dalam proses pembelajaran untuk meningkatkan kemampuan berpikir kritis, kreatif dan pemecahan masalah. Pengembangan perangkat pembelajaran ini terdiri dari beberapa tahapan, yaitu: (1) Difine, (2) Design, (3) Develop. Penelitian ini telah mencapai tahap definisi dan desain.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.007 |
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".