Grade 9 Students' Least Mastered Reading Skills: Basis for Developing and Evaluating E-Supplementary Learning Materials
Bibliographic record
Abstract
This study aimed to determine the least mastered reading skills of Grade 9 students which served as basis for developing and evaluating e-supplementary learning materials at Francisco P. Felix Memorial National High School, Cainta, Rizal during the school year 2021– 2022.The study used the descriptive method of research with two data gathering instruments. The first data gathering instrument used in this study was the Summative test for the First to Third Quarter administered during the school year 2019-2020. The test results were used as bases for identifying the least mastered reading skills in English. The other data gathering instrument was the Questionnaire used to evaluate the developed e-supplementary reading learning materials by the 30 students, 30 English teachers, and 30 English expert respondents using the criteria on appropriateness, authenticity, clarity, comprehensibility, usefulness, and technical quality. The statistical tools used to treat the data were the percentage, ranking, weighted mean, and the analysis of variance (ANOVA).The findings revealed that the identified least mastered reading skills of Grade 9 based on their summative test served as basis for the topics included in the developed e-supplementary reading learning materials. The students, teachers, and expert respondents evaluated the e-supplementary reading learning materials as Very Highly Acceptable (VHA) in terms of appropriateness, authenticity, clarity, comprehensibility, usefulness, and technical quality. Likewise, there were no significant differences in the evaluations of the three groups of respondents on the developed e-supplementary reading learning materials.The respondents offered comments and suggestions to further improve the developed e-reading material.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".