The Mapping of Core Competence of National Exam in South Central Timor
Bibliographic record
Abstract
The purpose of this study were to determine the mapping of core competencies of National Examination in several subjects at senior high school (SMA/MA) in South Central Timor (TTS) and to understand causes and find solutions for the local government South East Timor (NTT) in managing their education system. This study was also expected to boost the ranking of high school graduation (SMA/MA) in NTT. The numbers of sample that conduct in this research were 22 schools, taken by using stratified random sampling technique by considering the characteristics of the proportion of the population in the area of study. The approach used is a descriptive research that trying to find data in each competency tested in 2009 and 2010 and analyzed by using the mapping of the standard competencies. The procedures of research are the study documentation, implementation of teacher ability test, questionnaire, Focused Group Discussion (FGD) and observation. The results showed: there are two factors that cause low achievement in basic competency examination subjects: Firstly, static factors, the problem is not the existence of (a) the science laboratory, (b) the school library, (c) the field laboratory, (d) English language laboratories, small amount school operational funds, the low participation of school committees. Secondly, dynamic factors, that consist of ; the low cognitive teachers because teachers are not teaching subjects in related to their home-based academic, lack of innovation in learning and lack of practice hours for students Therefore, the planned a model of problem solving are; (1) increasing teachers community programs (MGMPs) through the coaching program to supports the students in achieving passing grade standard, (2) improving the monitoring of learning in the classroom, (3) assisting teachers in classroom learning process by improving qualification of the teachers. This study should be continued in the form of community service that can involve all stakeholders i.e.; school principals, teachers, school committees and community.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".