Pengembangan Lembar Kerja Siswa Berbasis Group Investigation untuk Memfasilitasi Kemampuan Penalaran Matematis Siswa SMP
Bibliographic record
Abstract
Penelitian ini mengembangkan suatu media pembelajaran berupa lembar kerja siswa berbasis group investigation. Pengembangan LKS berbasis Group Investigation ini bertujuan untuk memfasilitasi kemampuan penalaran matematis siswa pada materi segitiga. Model pengembangan yang diterapkan adalah model ADDIE. Subjek penelitian ini adalah siswa kelas VII.8 SMPN 4 Siak Hulu, yang berjumlah 35 orang. Pengumpulan data dilakukan menggunakan angket dan tes. Analisis terhadap data yang diperoleh dari angket menunjukkan bahwa LKS berbasis Group Investigation telah valid dan praktis untuk digunakan. Hasil uji t menyimpulkan bahwa LKS ini efektif untuk memfasilitasi kemampuan penalaran matematis siswa. LKS berbasis Group Investigation ini dapat digunakan sebagai media pembelajaran bagi siswa kelas VII pada materi segitiga.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.104 | 0.014 |
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".