Variations in Arabic Reading Skills between Normally Achieving and at Risk for Reading Disability Students in Second and Fourth Grades
Bibliographic record
Abstract
The study investigated variations in Arabic reading skills between normally achieving students and students at risk for reading disability in second and fourth grades. Using a cross-sectional design the study tested the effect of gender, grade level, and student condition on the variation of Arabic reading skills. Participants were 381 Arabic speaking children from second and fourth grades. Participants included both normally achieving students and students who were referred to the Learning Disabilities Unit in elementary schools in Oman. Dependent measures of the study included letter sound identification (LSI), word decoding (WD), phonological awareness (PA) through blending and segmentation, word recognition (WR), reading comprehension (RC), and listening comprehension (LC) in Arabic. Multivariate analysis indicated that gender, grade level and student condition had an effect on variation of reading skills. Additionally, the interaction effect of grade level and student condition as well as the combination of the three independent variables showed similar effects. Significant reading skills varied according to gender, grade level and student condition in addition to the interaction effects. WD, LSI and LC were significant as a result of the interaction effects. The results are discussed in relation to the characteristics of the Arabic language orthography.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".