Development of Geography Text Books Used by Senior High School Teachers Case Study at East Java-Indonesia
Bibliographic record
Abstract
The aim of this study was to analyze the geography text book for: (1) identify and describe the errors in the organization of geography textbooks, and (2) identify and describe the content of the textbook standard errors of geography. The text book is currently being used by teachers of Senior High School in East Java. To analyze the contents of the textbook errors using indicators blend of organizing textbook of Beck and McKeown and content standard textbooks of National Education Standards Agency of the Republic of Indonesia. Data collected by survey techniques against various geography text books used by teachers in Malang, East Java Province. The results showed that the errors found in the textbook Geography: first, errors in organizing textbook includes: (1) aside that overwhelm the purpose amounted of 28.69%, (2) inagequate examples and comparisons amounted of 30.65%, (3) poorly odered components of an explanation of 22.85% and, (4) inadequate explanation of 17:35%. Second, the standard error of the contents of the textbook includes: (1) exposure draft of 54.80%, (2) exposure of the facts of 57.10%, (3) exposure generalization of 28.60%, (4) the use of language of 21.40%, and (5) the effective functioning media amounted of 59.50%. Found media functionality in geography text book shows the worst, which is equal of 59.50. It would be bad for the implementation of the national curriculum in 2013 that is currently being used by teachers. Describing the content of bad geography textbooks in the exposure draft (error of 54.80%) and the fact (error of 57.10%) will result in a weak student mastery of concepts and facts in learning geography material at the Senior High School.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".