Developing Culture-Based Teaching Material on Human Reproductive System Materials Class XI Senior High School
Bibliographic record
Abstract
This study aimed to investigate the development of textbooks and also to figure out their validity, practicality, and effectiveness, in indonesain education system. In the case of textbook validation, it is performed by three validators. In order to measure the practicality of the textbooks, it was tested in 3 high schools in the year 2022/2023 through student response questionnaires and teacher response questionnaires. Mexanwhile, the effectiveness of textbooks was tested in class XI first-grade students of three high schools in Banda Aceh in the year 2022/2023. Based on the results of the trials that have been carried out, it was concluded that the textbooks have met a very valid category with an average value of 4,032 by relying on the criteria table validity (4≤M<5). For the practicality of textbooks, it can be seen that 92.59% of the students gave vastly positive responses, and 95% of the teachers gave very positive responses in relation to the textbooks used for learning. Furthermore, to find out the effectiveness of textbooks can be seen in the student learning outcomes test. There are 47 students in total, 39 students were declared complete (passed) and 8 students were declared incomplete (did not pass) with the average percentage of the number of students who achieved a minimum completion score of 75 was 83 %. Based on the results of this study, indicated that the textbooks developed were valid, practical, and effective to be used in order to support the teaching and learning process.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".