Penerapan Problem Based Learnin (Pbl) Dalam Kurikulum Berbasis Kompetensi
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Salah satu metode pembelajaran yang dapat diterapkan dalam Kurikulum Berbasis Kompetensi adalah Problem Based Learning. Donald Woods McMaster merupakan orang yang pertama kali memperkenalkan istilah PBL, dan Fakultas Kedokteran Universitas McMaster, Ontario Kanada merupakan institusi kedokteran yang memperkenalkan PBL dalam dunia pendidikan. Ada empat prinsip penting dalam pembelajaran PBL, yaitu : pembelajaran merupakan suatu proses konstruktif. (Learning should be a constructive process), pembelajaran merupakan suatu proses yang dimotori oleh keinginan dari dalam diri sendiri (Learning should be a self directed process), pembelajaran merupakan suatu proses yang dimotori oleh keinginan dari dalam diri sendiri (Learning should be a self directed process) dan pembelajaran merupakan sesuatu yang diberikan kontekstual (Learning should be a contextual process). Salah satu metode yang digunakan dalam melaksanakan PBL adalah seven jumps tutorial. Metode ini terdiri dari tujuh langkah yang disusun sistematis sehingga diskusi mahasiswa tentang suatu masalah dapat berjalan dengan optimal dan mencapai tujuan baik sesuai karakteristik PBL Keywords : KBK, PBL, seven jumps
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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 it