PELATIHAN PEMBUATAN PERANGKAT AJAR SILABUS DAN RPP SMK PGRI 1 LIMAU
Bibliographic record
Abstract
Planning can provide guidelines for the implementation of learning, so that it is right on target and effective. One of the goals of educational planning that is very meaningful made by teachers as educational directors is the Syllabus and Learning Implementation Plans and Plans (RPP). Teachers of SMA/Vocational High School (SMK) PGRI 1 Limau are the right target for community service activities considering that the school has not had sufficient technical training. The purpose of this dedication activity is to train and motivate teachers to be able to develop the perfect syllabus and lesson plans. The lesson plan (RPP) is a more specialized planning tool than the syllabus. This educational implementation plan is designed to guide teachers in teaching so that they are not far from educational goals. Recognizing the importance of planning this lesson, teachers should not teach without planning. There is also feedback that shows that the training is suitable with the needs of increasing teacher professionalism and is optimistic that the training can be achieved. Supporting energy for training in the form of space or supporting facilities is sufficient so that the training can run easily, well, on time, and fun. Participants are very supportive of further training. Keywords: Building teacher professionalism with syllabus training, lesson plans, 2013 curriculum.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.066 | 0.016 |
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".