Reading Anxiety in Arabic University Students
Bibliographic record
Abstract
Reading anxiety measures are newly available in English, but none is available in Arabic. The goals of the present study were to adapt the English Reading Anxiety in College Students (RACS) scale to Arabic-speaking college students (RACS-Arabic), evaluate its reliability and other psychometric properties in comparison to the English US sample, and assess its relation to self-assessments of reading ability and measured reading ability. A sample of 226 undergraduate university Arabic-speaking students completed measures of reading anxiety, general and social anxiety, reading self-concept, perception of reading ability, and reading skills. Results showed the brief 10-item RACS-Arabic demonstrated high reliability. Factor loadings were compared to the original RACS English US sample, suggesting reading anxiety in Arabic to be more about reading out loud in front of people and less about not understanding what is read. Results also indicated that reading anxiety was a significant predictor of reading self-concept and self-perception of reading ability after controlling for general and social anxiety, demonstrating the reading-specific nature of reading anxiety. Unlike the English US sample, which demonstrated small but significant associations between reading anxiety and reading fluency, no significant correlation was observed in this sample between RACS-Arabic and oral vowelized word reading efficiency. Future research is needed to explore the relationship between reading anxiety and different measures of Arabic reading ability.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".