Bibliographic record
Abstract
This study examined the level of academic performance in Science of Grade 5 learners in Dungan Elementary School, Cluster I, Division of Mabalacat City during the first quarter of School Year 2023–2024. Using a quantitative-descriptive research design, the study analyzed the learners’ first-quarter Science ratings to determine their overall achievement and identify specific areas of weakness. Frequency, percentage, and weighted mean were employed to describe the performance profile, while expert evaluation was used to determine the acceptability of the proposed support instructional materials. Results showed that the first-quarter achievement rate in Science was 81.75%, interpreted as an average level of performance, indicating that most learners have a basic yet adequate grasp of key scientific concepts and skills. However, notable learning gaps were found in understanding properties of materials, changes in materials, and designing useful products from recyclable solid and liquid materials. In response, contextualized support instructional materials were developed for Grade 5 Science and subsequently evaluated by experts in terms of content, quality of presentation, and physical make-up. The materials obtained weighted means ranging from 3.50 to 3.78 across all criteria, with an overall weighted mean of 3.59, qualitatively described as very acceptable. These findings suggest that the proposed instructional materials are pedagogically sound and potentially effective in addressing learners’ difficulties in Science, particularly in content areas requiring higher-order thinking and application. The study recommends the adoption and wider try-out of the materials, sustained administrative support for teachers’ material development initiatives, and the conduct of similar studies in other grade levels and contexts to validate and extend the results. Overall, the study underscores the crucial role of well-designed instructional materials in raising Science achievement and supporting competency-based instruction in the elementary classroom.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".