Evaluation of Principal Role on Building Teachers’ Competence in Man Kendari, Southest Sulawesi, Indonesia
Bibliographic record
Abstract
This study aims at analyzing the evaluation of principal’s role in training teachers’ competence in MAN 1 Kendari, Southeast Sulawesi Kendari. Subjects in this study are principals and teachers of MAN I Kendari. The research used descriptive method with qualitative approach. All the data collected by observation, interview and documentation and analyzed by data collection, data reduction, data presentation and conclusion. The result showed that the evaluation of principal role in building teachers’ competence run well. In addition, the principal role as a leader trained the cooperation among administrators in the school, teachers and students’ parents relates to students’ education whether in the school or out of the school and socialization activities done by the teachers through teachers’ group working (Kelompok Kerja Guru / KKG) to improve teachers’ competence. As educator, the principal attempted to train the pedagogic competence and professional in terms of facilitating teachers to actively participate in KKG in order to improve teachers’ ability in classroom management. In addition, as the supervisor, the principal trained teachers’ pedagogic and personal in the classroom supervision activities, conducting meeting relates to the outcome of learning and instruction, arranging its scenario and the interaction process among teacher and students in the classroom.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".