INTERDISCIPLINARY CONTEXTUALIZATION IN THE DEVELOPMENT OF INSTRUCTIONAL MATERIAL IN GRADE 7 MATHEMATICS
Bibliographic record
Abstract
This developmental research aimed to create interdisciplinary contextualized instructional material in mathematics for Grade 7 students. The progress was based on the Analyze, Design, Develop, Implement, and Evaluate (ADDIE) Model. The analyze, design, and develop stages were done with the data gathered from observations and interviews of two Grade 7 mathematics teachers, and two department heads from two public schools in Iloilo. The participants suggested to develop an activity book for fourth quarter topics that focused on statistics concepts. For the implementation stage, an activity book was pilot tested in one Grade 7 section composed of 50 students. The evaluation stage involved expert’s rating of the material’s acceptability and the students’ satisfaction. Mean and standard deviation were used in the analysis. The results showed that the developed material was highly acceptable, and the students’ satisfaction was also highly satisfied. The activity book was clearly an appropriate material for interdisciplinary contextualization in the classroom. Experimental studies may be done in order to ascertain the effectiveness of the developed material.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".