Gather, Read, Organize, Practice, Enhance (GROPE) Strategy: Its effect on the Mathematical performance of Grade 3 learners
Bibliographic record
Abstract
Mathematics is very influential in developing learners’ analytical, critical thinking, and problem-solving skills. As one of the most difficult subjects for the primary grades, an innovative teaching strategy for Grade 3 Mathematics was designed to improve students’ mastery through structured problem-solving techniques, vocabulary development, interactive activities, drills, and enhancement tasks. To get the significant difference and effect size, a paired t-test and Cohen’s D formula were used using the mean score of the pretest and posttest. The formative assessment scores were transformed into mean percentage scores and aligned to the given tables for achievement levels. Based on the results, the achievement level of the Grade 3 learners in the third quarter of Math 3 is proficient, based on the given formative assessments. There is a mastered level of the Grade 3 learners in the third quarter of Math 3 after using the GROPE Strategy and as indicated in all learning competencies. There is a significant difference in the mastery level of the Grade 3 Learners in the third quarter of Mathematics 3, as supported by the large effect size. The majority of the learners experience a worthwhile learning the subject through the GROPE strategy, together with engagement with other learners and involvement of parents. It is further recommended that the GROPE strategy must be integrated in all quarters for all problem-solving activities in Mathematics 3 so that learners can be familiarized. Adoption of the GROPE strategy implementation among learners to ensure its application. GROPE strategy will be integrated as part of the teaching delivery of the lesson, for more action research to be done. Feedback mechanism with psychosocial support to the learners must be displayed so that their eagerness to learn is sustained in solving problems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".