MATHEMATICAL LITERACY PROFILE OF ELEMENTARY SCHOOL STUDENTS IN INDONESIA: A SCOPING REVIEW
Bibliographic record
Abstract
Mathematical literacy becomed one of skills that had to be mastered by the students in this era. Mathematical literacy could start to be learned in elementary level. This study aimed to describe the research trends of mathematical literacy profile for elementary school students in Indonesia. This study used scoping review research with 5 steps including 1) identifying the initial research questions; 2) identifying relevant studies; 3) study selection; 4) charting and collating the data; and 5) summarizing and reporting the results. The data exploration process was taken through open-access websites such as Google Scholar, ERIC, and Springer using keywords “Literasi Matematika Siswa Sekolah Dasar”, “Mathematical Literacy of Elementary School Students in Indonesia”. The exploration process was also limited publication for 5 last years. The data reduction process was analyzed using the Preferred Reporting of Items for Systematic Review and Meta-Analyses (PRISMA). The study results were classified to the 3 components such as 1) research methodologies trends, 2) mathematical literacy development, and 3) student’s achievement based on mathematical literacy.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".