Project AGIMaT (Activity, Games, and Interactive and Manipulative Toys) in Teaching Selected Topics in Mathematics 3
Bibliographic record
Abstract
The researchers from Calero-Lanang Elementary School conducted a study to address the problem of incomplete mastery of several concepts in Mathematics experienced by the school for about three years. To address this, they devised "Project AGIMaT," which engaged learners in selected topics in Mathematics 3 using activity, games, interactive and manipulative toys. The study utilized a descriptive comparative design involving 32 Grade 3 pupils from Calero-Lanang Elementary School, and selected topics based on the least mastered skills reported within three years. Participants were subjected to the use of AGIMaT from the second quarter up to the third quarter, and the standard Quarterly Test was used for assessment. The study found that Project AGIMaT increased the mastery in Multiplication and Division and Dissimilar Fractions, with the mean percentage of mastery increasing from 71.15% to 81.51% and from 71.45% to 83.07%, respectively.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".