Attentional Factors Involved in Learning in the First Grade
Bibliographic record
Abstract
In the school population, attentional problems are one of the most frequent causes of failure in learning; sometimes these take the form of a specific deficit and in other cases an attention disorder occurs in comorbidity with a learning disorder. It seems crucial to focus on what peculiar characteristics of attention are involved in basic learning in order to contribute to the diagnostic order and to arrange paths of development. This research aims to verify the weight of the different components of attention involved in the outcomes of the first stages of learning. A total of 69 children (34 males and 35 females, aged 6.4±1.1 years and 7.3±1.2 years respectively) in first grade, participated in the study. The results of the correlational analysis carried out show that there are specific significant relationships between the various components of attention and performance in reading, writing and calculation. In particular, visual attention appears to be the aspect most involved in the initial development of the learning of these three abilities. Factorial analysis shows a single factor involved in the learning of reading, writing and calculation: “Rapid Visual Attention”. The processes identified in the factor are: Selective Attention, Visual Selective Attention, Shifting Focus, Focused Attention, Planning and Inhibition. This factor is characterised by speed in Selective/Sustained Visual Attention and this explains the role of attention in success in reading, writing and calculation in the early stages of school learning. The Rapid Visual Attention Factor contributes to rapidity in reading, speed in writing and numerical knowledge in first grade children, confirming the causal relationship between visual attention and initial learning in this age group. This “Rapid Visual Attention” Factor may be crucial in accounting for the comorbidity between Attention Deficit Hyperactivity Disorder and Learning Disabilities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".