Cognitive processes in children's reading and attention: The role of working memory, divided attention, and response inhibition
Bibliographic record
Abstract
Children experiencing attention difficulties have documented cognitive deficits in working memory (WM), response inhibition and dual tasks. Recent evidence suggests however that these same cognitive processes are also closely associated with reading acquisition. This paper therefore explores whether these variables predicted attention difficulties or reading among 123 children with and without significant attention problems sampled from the school population. Children were screened using current WM and attention task measures. Three factors explained variance in WM and attention tasks. Response inhibition tasks loaded mainly with central executive measures, but a dual processing task loaded with the visual-spatial WM measures. Phonological loop measures loaded independently of attention measures. After controls for age, IQ and attention-group membership, phonological loop and 'central processing' measures both predicted reading ability. A 'visual memory/dual-task' factor predicted attention group membership after controls for age, IQ and reading ability. Results thus suggest that some of the processes previously assumed to be predictive of attention problems may reflect processes involved in reading acquisition. Visual memory and dual-task functioning are, however, purer indices of cognitive difficulty in children experiencing attention problems.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 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".