Utilization of Lexical Proficiency Worksheets in Enhancing the Reading Comprehension of Senior High School Students
Bibliographic record
Abstract
This experimental and descriptive study was conducted to enhance the reading comprehension of 177 Grade 11 HUMSS students of Tipas Integrated National High School through the utilization of Lexical Proficiency Worksheets (LPWs) designed and integrated with the Course Reading and Writing Skills given for eight weeks during the 3rd Quarter of the School Year 2021-2022. It is a quantitative type of research that used correlational design and purposive sampling techniques. It used pre and post-test, LPWs and perceptionnaire as research instruments. The study revealed that the pre-assessed level of comprehension skills among respondents before the LPWs’ utilization ranged from non-reader to independent level while the post-assessed level of comprehension skills among respondents ranged from frustration to independent level after the utilization of LPWs. The respondents perceived the quality of designed LPWs as very satisfactory in terms of objectives, content, format and language, usefulness, and satisfactory in terms of instructional delivery. The hypothesis stating that there is no significant difference between the pre and post-assessed level of reading comprehension before and after the utilization of LPWs is not supported. Additionally, the hypothesis stating that there is no significant relationship between the perceived quality of the designed LPWS and the respondents’ reading comprehension is not supported. The designed worksheets contributed a lot towards enhancing the lexical proficiency and comprehension skills of the learners.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".