Bibliographic record
Abstract
Pembelajaran Berbasis Penyelidikan (Inquiry-Based Learning/IBL) merupakan pendekatan pedagogis yang menekankan peran aktif siswa dalam menemukan dan memahami konsep melalui penyelidikan. Pendekatan ini bertujuan untuk mengembangkan keterampilan berpikir kritis, pemecahan masalah, serta kemandirian belajar. Dalam pembelajaran berbasis penyelidikan, siswa tidak hanya menerima informasi secara pasif, tetapi juga dilatih untuk bertanya, mengamati, mengajukan hipotesis, mengumpulkan data, serta menarik kesimpulan sendiri. Artikel ini mengulas konsep dasar pembelajaran berbasis penyelidikan, ciri-cirinya, tahapan pelaksanaan, serta manfaatnya dalam meningkatkan pemahaman dan keterampilan siswa. Berbagai teori dan model inkuiri yang dikembangkan oleh para ahli seperti John Dewey, Jerome Bruner, dan pendekatan Alberta Learning dijelaskan untuk memberikan perspektif yang lebih luas dalam implementasi IBL di lingkungan pendidikan. Hasil kajian menunjukkan bahwa pembelajaran berbasis penyelidikan tidak hanya mampu meningkatkan keterampilan akademik, tetapi juga membekali siswa dengan kemampuan berpikir analitis dan kreatif yang sangat diperlukan di era modern.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.049 | 0.022 |
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".