TINGKAT LITERASI DIGITAL MAHASISWA KEGURUAN DALAM MENGHADAPI ERA REVOLUSI INDUSTRI 4.0
Bibliographic record
Abstract
Literasi digital merupakan suatu kemampuan soft skill yang selayaknya dimiliki mahasiswa guna menghadapi era revolusi industri 4.0. Sehubungan dengan hal tersebut, penelitian ini bertujuan untuk mengidentifikasi tingkat literasi digital mahasiswa keguruan dilihat dari aspek persepsi terhadap literasi digital, keterpaparan terhadap penggunaan teknologi digital, dan harapan terhadap pengembangan literasi digital. Penelitian ini merupakan penelitian lapangan (field research) yang bersifat kuantitatif. Populasi dalam penelitian ini adalah seluruh mahasiswa keguruan pada Prodi PGMI Fakultas Tarbiyah Institut Agama Islam (IAI) Muhammadiyah Bima, berjumlah 128 orang. Sampel dipilih dengan menggunakan teknik stratified random sampling sehingga diperoleh 30 mahasiswa sebagai sampel penelitian. Hasil penelitian menunjukan bahwa tingkat literasi digital mahasiswa keguruan Prodi PGMI Fakultas Tarbiyah Institut Agama Islam (IAI) Muhammadiyah Bima dilihat dari aspek persepsi terhadap literasi digital berada pada kategori sedang (63%), aspek keterpaparan terhadap teknologi digital menempati kategori rendah (33%), dan untuk aspek harapan terhadap pengembangan literasi digital masuk pada kategori sedang (42%).
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.202 | 0.072 |
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".