Pengembangan EMODI (E-Modul Interaktif) Materi Akhlak Terpuji dalam Pembelajaran Agama Islam Kelas 6 SD
Bibliographic record
Abstract
Pemanfaatan teknologi sebagai pendukung pembelajaran dirasa masih kurang terutama pada mata pelajaran agama Islam di SD. Kemajuan teknologi menghadirkan permasalahan yang menyangkut akhlak terpuji yang semakin hilang. Sehingga pemanfaatan teknologi dalam pembelajaran agama Islam perlu dihadirkan, salah satunya melalui penggunaan EMODI (E-Modul Interaktif) materi akhlak terpuji di kelas 6 SD. Penelitian ini menggunakan model Design and Development (D&D) atau desain dan pengembangan, dengan prosedur penelitian menurut Peffers, dkk, yaitu: Identify the problem motivating the research, Describe the objectives, Design and develop the artifact, Subject the artifact to testing, Evaluate the results of testing, and Communicate those results. Hasil dari penelitian ini berdasarkan sudut pandang dari 8 guru dan 10 siswa sebagai pengguna atau ahli lapangan. Produk ini mendapatkan kategori “sangat baik” berdasarkan data yang telah dikumpulkan melalui google form. Sehingga penggunaan EMODI dapat dinyatakan layak untuk digunakan dalam kegiatan pembelajaran Pendidikan Agama Islam pada materi akhlak terpuji di kelas 6.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.051 | 0.013 |
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".