Internal representation of movement in children with developmental coordination disorder: a mental rotation task
Bibliographic record
Abstract
Recent studies show that children with developmental coordination disorder (DCD) have difficulties in generating an accurate visuospatial representation of an intended action, which are shown by deficits in motor imagery. This study sought to test this hypothesis further using a mental rotation paradigm. It was predicted that children with DCD would not conform to the typical pattern of responding when required to imagine movement of their limbs. Participants included 16 children with DCD and 18 control children; mean age for the DCD group was 10 years 4 months, and for controls 10 years. The task required children to judge the handedness of single‐hand images that were presented at angles between 0° and 180° at 45° intervals in either direction. Results were broadly consistent with the hypothesis above. Responses of the control children conformed to the typical pattern of mental rotation: a moderate trade‐off between response time and angle of rotation. The response pattern for the DCD group was less typical, with a small tradeoff function. Response accuracy did not differ between groups. It was suggested that children with DCD, unlike controls, do not automatically enlist motor imagery when performing mental rotation, but rely on an alternative object‐based strategy that preserves speed and accuracy. This occurs because these children manifest a reduced ability to make imagined transformations from an egocentric or first‐person perspective.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".