Crafting an English Ebook for the Merdeka Curriculum: Insights from Indonesian High School Teachers
Bibliographic record
Abstract
Need analysis is an essential component of Research & Development (R&D) and cannot be separated from the process as a whole. This study analyzed the need for an English ebook model based on the Merdeka curriculum for Indonesian Senior High Schools. Using a descriptive qualitative approach, the study investigated the requirements for the research purpose. Data were collected through questionnaires from 68 English Senior High School teachers in Pandeglang, Banten Province, Indonesia, and analyzed qualitatively. The findings revealed that almost all English teachers agreed that the English coursebook should reflect the Merdeka curriculum, with a preference for interactive ebook formats. Both students and teachers expressed a need for an introductory English ebook as a learning medium in the classroom. Specifically, teachers emphasized the importance of incorporating local content and interactive elements. These findings provide a foundation for developing an English ebook model based on the Merdeka curriculum, tailored to the needs of Indonesian Senior High School students and aligned with current educational trends.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".