Examining the Factor Structure and Psychometric Properties of the Test of Visual-Perceptual Skills
Bibliographic record
Abstract
This study examines psychometric properties and factor structure of the Test of Visual-Perceptual Skills (nonmotor) (TVPS), a measure developed to assess children with school-related learning difficulties. Following a descriptive retrospective study design, clinic record data were compiled for a convenience sample of 294 children. While measure use was generally supported, findings indicate areas wherein the measure lacks psychometric soundness. Item analysis using point biserial correlations showed a low relationship between some items and subscale scores. Coefficient alpha showed acceptable internal consistency for group totals by subscale but only 3 of 7 by age group. Correlations between TVPS scores and criterion variables followed the pattern expected of a measure of visual perception. Confirmatory factor analysis did not support use of a unitary TVPS PQ score. Exploratory factor analysis supported some, albeit not all of the subscales, as measuring distinct visual-perceptual skills.
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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 | 0.012 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".