THE EFFECT OF CO-OP APPROACH IN IMPROVING VISUAL MOTOR INTEGRATION SKILLS IN CHILDREN WITH LEARNING DISABILITY
Bibliographic record
Abstract
The importance of visual perception, motor coordination and visual motor integration (VMI) skills for school achievements has been shown in various studies. Cognitive orientation to daily occupational performance or CO-OP is an evidence-based approach that has been effective in children with developmental coordination disorder and autism spectrum. The present study evaluated the effect of CO-OP approach in improving VMI skills in children with learning disability. Sample of 58 children were included in the study. National Centre for Learning Disabilities (NCLD) Checklist was used as a screen tool and pre and post intervention Beery VMI and Canadian Occupational Performance Measures (COPM) was used as outcome measures.Occupational therapy program using CO-OP approach, based on each childs individualized goals. children were thought global strategy of GO-PLAN-DO-CHECK the sessions were conducted for 12 weeks one hour a day three times a week. After 12 weeks post assessment was done using t test. There significant difference in pre and post CO-OP intervention. p-value was found to be less than 0.0001 for VMI, COPM performance and satisfaction whereas, there was significant difference in motor coordination and visual perception component of Beery VMI. The result shows that CO-OP approach is effective in improving visual motor integration skills of children with learning disability.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".