The Effects of Science Intervention Material in the Academic Performance of Junior High School Students
Bibliographic record
Abstract
The researcher being a science teacher identified problems encountered by the students namely; low mean proficiency scores in science grade 10 during the first quarter examination, lack of interest during discussion and frequent absenteeism among students. The Division mean proficiency score target is 68 but the grade 10 students only obtained a score of 60 which is behind the target of the department. Science intervention material was conceptualized and created by the researcher based on the least mastered competencies. This material was utilized as intervention to address the problem of poor academic performance. The 15 respondents who received the science intervention material obtained M=27.9, SD=3.13 compared to the 15 respondents in the control group who obtained M=14.37, SD=9 demonstrated significantly better scores, t = - 21.29, p = <.00001. Intervention material based on least mastered compe-tencies is an effective method of improving the academic performance of students.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".