PEMBELAJARAN KONSTRUKTIVISTIK MENINGKATKAN CARA BERPIKIR DIVERGEN SISWA SD
Bibliographic record
Abstract
Penelitian ini bertujuan untuk menemukan model pembelajaran konstruktivistik yangefektif untuk mengembangkan cara berpikir divergen dan konvergen siswa SD. Metodepenelitian yang digunakan untuk mencapai tujuan tersebut adalah pendekatan R&D(Research and Development) model Borg and Gall. Hasil penelitian adalah; 1) pembelajarandi SD Sleman Iebih dominan mengembangkan cara berpikir konvergen daripada caraberpikir divergen, 2) model pembelajaran yang sering diterapkan guru adalah modelpembelajaran ekspositori, yang menjadikan metode ceramah sebagai metode utama, 3)penerapan model pembelajaran konstruktivistik mampu meningkatkan cara berpikirdivergen dan konvergen siswa SD, 4) penerapan model pembelajaran konstruktivistikmampu meningkatkan aktivitas belajar siswa SD, 5) penerapan model pembelajarankonstruktivistik mampu meningkatkan hasil belajar siswa SD, dan 6) sistem evaluasiportofolio mampu meningkatkan aktivitas belajar siswa SD
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".