The Problems of Applying Student Centered Syllabus of English in Vocational High Schools in Kendal Regency
Bibliographic record
Abstract
This study was descriptive qualitative study aimed to investigate the problems of applying student centered syllabus in vocational high schools in Kendal regency, Central Java, Indonesia. The subjects of the study were twenty English teacher in vocational high schools in Kendal. The data were collected through observations, questionnaires, and interviews. The collected data further were analyzed using inductive analysis in which the researchers looked for the pattern of the data and the meaning of the data. Based on the data, there are three points concluded. The first was the English teaching and learning process in vocational high schools in Kendal had applied the student-centered syllabus. The second, in designing the students-centered syllabus the teachers found difficulties in having a model of the student-centered syllabus as a guideline in adapting and designing their own syllabus, describing the learning indicators, and formulating learning activities alligned with the student-centered learning. The third, the teachers faced difficulties in terms of encouraging their students to participate actively during the teaching and learning, and requiring a lot of time in implementing the student-centered syllabus. Thus, even though the teachers had already applied the student-centered syllabus in their teaching, they still found difficulties in implementing it. In conclusion, they need a model of student-centered syllabus for being a guideline in designing their syllabus and workshops to train them the ways to implement the student-centered syllabus successfully in their teaching.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".