Penerapan Model Pembelajaran Discovery Learning Untuk Meningkatkan Hasil Belajar Siswa Pada MataPelajaran IPA Kelas V SDN 124 Batuasang Kecamatan Herlang Kabupaten Bulukumba
Bibliographic record
Abstract
T his research is a classroom action research that aims to increase learning outcomes IPA by applying discovery learning model . The approach used in this study is qualitative with the type of research is Class Action Research (PTK) is recycled/ cycles that include planning, execution, observation, and reflection. The data analysis used is qualitative . The results showed that there are increases in learning both on the activities of teachers and students as well as student learning outcomes. From this research can be concluded that teacher teaching activities and student learning activities are increase, student learning outcomes in cycle I not yet in the category enough, in cycle II student learning outcomes have increased are in good category and the application of discovery learning learning model in science subjects can improve the learning outcomes of fifth grade V SDN 124 Batuasang Kecamatan Herlang Kabupaten Bulukumba.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".