PERAN GURU DALAM PEMANFAATAN MEDIA PEMBELAJARAN DITINJAU DARI PRESPEKTIF PENDIDIKAN PROGRESIF
Bibliographic record
Abstract
Globalisasi menuntut tersedianya SDM yang mampu bersaing secara global, dan untuk itu pemerintah telah melakukan berbagai upaya untuk meningkatkan kualitas SDM kita. Depdiknas melalui serangkaian upayanya seperti pengesahan UU No. 20/2003 tentang Sistem Pendidikan Nasional, Penerapan Manajemen Peningkatan Mutu Berbasis Sekolah (MPMBS), penerapan perguruan tinggi negeri sebagai Badan Hukum Milik Negara (BHMN) pengembangan kurikulum berbnasis kompetensi (Kurikulum 2004) DAN LAIN sebagainya, yang kesemuanya itu dinmaksudkan untuk meningkatkan kualitas SDM Indonesia. Peningkatan kualitas SDM melalui pendidikan tentu tak bisa dilepaskan dari peran guru, yang bertanggungjawab atas terselenggaranya suatu proses pembelajaran yang baik dan bisa dipertanggungjawabkan. Demikian pula dengan kemajuan teknologi yang berkembang secara pesat, maka peran media pembelajaran juga semakin penting guna memberikan alternative sumber belajar bagi peserta didik yang menurut konsep pendidikan progresif harus aktif belajar dengan pengalaman langsung dan dengan menggunakan berbagai sumber belajar, karena guru kini tidak lagi menjadi pusat kegiatan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.068 | 0.010 |
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".