Efektivitas Model Pembelajaran Project Based Learning dengan Media Stick and Plasticine terhadap Hasil Belajar Matematika Siswa Kelas IV
Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengetahui seberapa besar efektivitas model pembelajaran project based learning dengan media stick and plasticine terhadap hasil belajar Matematika siswa kelas IV SDN Sendangguwo 01 Semarang. Penelitian ini menggunakan pendekatan kuantitatif dengan metode pre-experiment dengan desain penelitian one group pretest posttest design. Sampel penelitian ini adalah seluruh siswa kelas IVB SDN Sendangguwo 01 Semarang yang berjumlah 28 siswa. Teknik pengumpulan data yaitu tes dan dokumentasi. Hasil penelitian dapat dilihat dari hasil uji Wilcoxon dan dihitung dengan N-gain. Uji Wilcoxon digunakan karena hasil uji normalitas diperoleh data tidak berdistribusi normal. Hasil penelitian ini menunjukkan bahwa pada uji Wilcoxon diperoleh nilai Asymp.Sig. (2-tailed) = 0,000<0,05, sehingga Hα diterima. Hasil dari uji N-gain dikategorikan cukup efektif dengan kategori sedang mendapatkan nilai N-gain skor 0,5830 dan N-gain persen dengan hasil nilai 58.3007. Dengan demikian model pembelajaran project based learning dengan media stick and plasticine dikatakan cukup efektif secara signifikan terhadap hasil belajar matematika pada peserta didik kelas IV SDN Sendangguwo 01 Semarang. Peneliti berharap dengan adanya penelitian ini dapat memberikan kontribusi dalam pendidikan.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".