A Qualitative Observation Tool for Folding, Writing, and Cutting in School-Aged Children: Hands-On!
Bibliographic record
Abstract
Background. Fine motor skills such as folding, writing, and cutting are daily activities of children, yet reliable, valid tools to qualitatively assess these skills remain limited. Purpose. To develop the Hands-On! observation tool and evaluate its reliability and validity in assessing fine motor skills in 5- to 10-year-old children. Method. Hands-On! was created using literature review and expert feedback to determine intratask components for folding, writing, and cutting. The sample included 178 typically developing children ( M age 8.06 ± 1.58 years, 47.8% boys). Inter- and intraobserver reliability were measured, alongside concurrent (duration and errors DCDDaily) and construct validity (age, sex) for each task. Findings. Moderate to very strong interobserver (folding 84.5%–84.9%, writing 81.8%–86.0%, cutting 75.4%–83.8%) and intraobserver reliability (folding 92.8%, writing 91.7%, cutting 93.7%) were found. Concurrent validity was supported by moderate to strong correlations between qualitative scores for folding (ρ duration = 0.624, ρ folds = −0.441) and cutting (ρ duration = 0.335, ρ errors = 0.377) with DCDDaily metrics, though no significant correlation was found for writing. Construct validity was supported for folding and cutting, with age and sex explaining 22.1% and 14.1% of the variance. Conclusion. Hands-On! is a reliable and valid qualitative observation tool for assessing fine motor skills in children, enhancing assessment practices, and informing effective interventions.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".