Sustained Attention and Its Relationship to Fluid Intelligence and Working Memory in Children
Bibliographic record
Abstract
<p>Understanding individual differences in intelligence remains an interesting research question, even with more than a century of empirical research and large numbers of models and theories. We know that working memory (WM) is able to explain substantial amounts of variance in fluid intelligence in both children and adults, but we also know that it is not the only predictor of intelligence. There are many other information-processing mechanisms that have been studied. Results in adult samples seem to indicate that sustained attention—the ability to maintain attention on a specific task over an extended period of time—is strongly related to fluid intelligence. There is little research on this topic in childhood, but the available data seems to converge with results from adult samples. The aim of the present study was to assess sustained attention and its relationship to fluid intelligence and WM in children. Additionally, we wanted to explore whether sustained attention contributes to the prediction of intelligence over and above WM. A sample of 125 ten-year olds was assessed using tests of fluid intelligence, sustained attention and WM. The results showed that, as expected, WM and fluid intelligence were significantly related. Surprisingly however, sustained attention was not related to fluid intelligence or WM. Using results from previous studies and theoretical considerations, we concluded that sustained attention may not be directly related to fluid intelligence in childhood, but rather that it may be a more distal factor influencing information processing in more unstructured learning situations and hence impacting academic achievement.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".