Relationship between body functions and Arabic handwriting performance at different acquisition stages
Bibliographic record
Abstract
BACKGROUND.: The written languages and handwriting acquisition stages place different demands on the writer. Therefore, the relationship between body functions and handwriting performance may vary in different languages and acquisition stages; yet these demands have not been studied in the Arabic language. PURPOSE.: We examined the relationship between linguistic, visual-motor integration (VMI), and motor coordination (MC) functions and Arabic handwriting at two handwriting acquisition stages. METHOD.: This study used a cross-sectional and correlative design. Second- ( n = 54) and fourth-grade ( n = 59) students performed tasks examining reading, handwriting automaticity, VMI, MC, and copying a text. FINDINGS.: Handwriting automaticity significantly explained the variance in handwriting speed in both grades, in addition to the VMI in second grade and the MC in fourth grade. Enhanced performance in the VMI increased the likelihood of having good legibility in second but not in fourth grade. IMPLICATIONS.: Similar to other languages, the body functions related to Arabic handwriting vary at the different acquisition stages. Handwriting evaluation should be adjusted to students' acquisition stage.
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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 | 0.005 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".