UPAYA PENGEMBANGAN LITERASI SAINS SISWA BERBASIS E-BOOK
Bibliographic record
Abstract
Penulisan artikel ini bertujuan untuk memaparkan hasil analisis berupa kajian literatur pada hasil penelitian mengenai media pembelajaran sains berbasis e-book. Berbagai survei menunjukkan bahwa literasi di indinesia masih rendah. Salah satu penyebabnya adalah kurangnya buku. Penelitian ini dilakukan dengan metode kajian literatur untuk menganalisis keunggulan buku elektronik dalam upaya meningkatkan literasi di Indonesia. Kajian ini difokuskan kepada aspek- aspek: (1) literasi mahasiswa di Indonesia, (2) insfrastruktur dan pemanfaatan buku elektronik. Hasil kajian menunjukkan bahwa buku elektronik dapat dimanfaatkan untuk mendorong peningkatan literasi sains dan literasi digital, khususnya unrtuk generasi z. selain itu, buku elektronik juga memiliki banyak keunggulan diantaranya lebih menarik, lebih mudah didistribusikan, dapat diakses dimana saja, dan lebih mudah diperbanyak atau digandakan. Pemanfaatan buku elektronik sebagai sarana peningkatan literasi di indinesia didukung pemerintah dalam menyiapkan atau mengembangkan bahan bacaan digital dan pemerataan akses internet ke seluruh wilayah.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.191 | 0.067 |
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".