Differentiated Instruction based on Pupils' Learning Style Preferences: The Effects on their Numeracy Level
Bibliographic record
Abstract
The study assessed the effectiveness of differentiated instruction in enhancing the numeracy skills of the Grade 3 Diamond pupils at Sta. Maria Elementary School during the Third Quarter of SY 2019-2020. The study involved twenty-seven (27) pupils who served as participants during the 6-week administration. As evidenced by their mean scores, it was revealed that the entire group of five learning styles showed improvement in their numeracy level. During the study, it was found that the majority of the participants were multimodal learners, with two or more combined modalities. Confidence levels as well as collaborative working skills of the learners were improved. The numeracy skills of Grade 3 pupils, as measured by their pre-test and post-test scores, improved after the administration of differentiated instruction, as shown by the results. The test of Significant Difference on the numeracy levels of pupils before and after their exposure to the intervention is reported to be highly significant, except for the visual learners, as the computed p-value for this LS is not less than the 0.01 level of significance. After concluding the findings of the study: the researcher recommended the following: (1) curriculum planners and developers may be mindful of determining the needs of both teachers and learners especially those with different learning styles; (2) mathematics educators should continue the search for teaching strategies that can maximize and enhance the pupils' numeracy level; (3) Parents should cooperate with the teachers in improving the numeracy level of their children and (4) Future researchers may conduct other studies relevant to the intervention.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".