Screening for Working Memory Deficits in the Classroom
Bibliographic record
Abstract
OBJECTIVE: The aim of this 18-month longitudinal study was to explore the psychometric properties of the recently developed Working Memory Rating Scale (WMRS) within a general school population of 524 six- to nine-year-old children (259 boys, 265 girls) and with an examination of sex and time differences. METHOD: Teachers completed the WMRS and children completed objective measures of WM and standardized measures of academic achievement. RESULTS: Confirmatory factor analyses indicated a poor fit for the 20 original WMRS items. Post hoc analyses, however, revealed that the factor structure of an alternative five-item short form was strong for both boys and girls and at the two time points, spanning two consecutive academic years. Internal consistency, criterion-related validity, and convergent validity of this alternative five-item WMRS were also excellent. CONCLUSION: The short five-item WMRS may eventually provide teachers with a useful and time-effective method to screen for WM deficits at school.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".